diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/_meta.json b/sdk/machinelearning/azure-mgmt-machinelearningservices/_meta.json
index 216b79b26570..9b461a0e2fcf 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/_meta.json
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/_meta.json
@@ -1,11 +1,11 @@
{
- "commit": "b32e1896f30e6ea155449cb49719a6286e32b961",
+ "commit": "747d3f08c1cd50b8994b8e77e242d522872e475c",
"repository_url": "https://github.com/Azure/azure-rest-api-specs",
"autorest": "3.9.2",
"use": [
- "@autorest/python@6.2.7",
+ "@autorest/python@6.4.8",
"@autorest/modelerfour@4.24.3"
],
- "autorest_command": "autorest specification/machinelearningservices/resource-manager/readme.md --generate-sample=True --include-x-ms-examples-original-file=True --python --python-sdks-folder=/home/vsts/work/1/azure-sdk-for-python/sdk --use=@autorest/python@6.2.7 --use=@autorest/modelerfour@4.24.3 --version=3.9.2 --version-tolerant=False",
+ "autorest_command": "autorest specification/machinelearningservices/resource-manager/readme.md --generate-sample=True --include-x-ms-examples-original-file=True --python --python-sdks-folder=/mnt/vss/_work/1/s/azure-sdk-for-python/sdk --use=@autorest/python@6.4.8 --use=@autorest/modelerfour@4.24.3 --version=3.9.2 --version-tolerant=False",
"readme": "specification/machinelearningservices/resource-manager/readme.md"
}
\ No newline at end of file
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_configuration.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_configuration.py
index 12c43638a412..a128695e54fd 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_configuration.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_configuration.py
@@ -6,7 +6,6 @@
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, TYPE_CHECKING
from azure.core.configuration import Configuration
@@ -15,11 +14,6 @@
from ._version import VERSION
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
-
if TYPE_CHECKING:
# pylint: disable=unused-import,ungrouped-imports
from azure.core.credentials import TokenCredential
@@ -35,14 +29,14 @@ class MachineLearningServicesMgmtClientConfiguration(Configuration): # pylint:
:type credential: ~azure.core.credentials.TokenCredential
:param subscription_id: The ID of the target subscription. Required.
:type subscription_id: str
- :keyword api_version: Api Version. Default value is "2022-10-01". Note that overriding this
+ :keyword api_version: Api Version. Default value is "2023-04-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: str
"""
def __init__(self, credential: "TokenCredential", subscription_id: str, **kwargs: Any) -> None:
super(MachineLearningServicesMgmtClientConfiguration, self).__init__(**kwargs)
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", "2022-10-01")
+ api_version: str = kwargs.pop("api_version", "2023-04-01")
if credential is None:
raise ValueError("Parameter 'credential' must not be None.")
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_machine_learning_services_mgmt_client.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_machine_learning_services_mgmt_client.py
index feffb8cfc3ed..690ca6db66e4 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_machine_learning_services_mgmt_client.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_machine_learning_services_mgmt_client.py
@@ -37,6 +37,17 @@
PrivateEndpointConnectionsOperations,
PrivateLinkResourcesOperations,
QuotasOperations,
+ RegistriesOperations,
+ RegistryCodeContainersOperations,
+ RegistryCodeVersionsOperations,
+ RegistryComponentContainersOperations,
+ RegistryComponentVersionsOperations,
+ RegistryDataContainersOperations,
+ RegistryDataVersionsOperations,
+ RegistryEnvironmentContainersOperations,
+ RegistryEnvironmentVersionsOperations,
+ RegistryModelContainersOperations,
+ RegistryModelVersionsOperations,
SchedulesOperations,
UsagesOperations,
VirtualMachineSizesOperations,
@@ -75,6 +86,36 @@ class MachineLearningServicesMgmtClient: # pylint: disable=client-accepts-api-v
:ivar workspace_connections: WorkspaceConnectionsOperations operations
:vartype workspace_connections:
azure.mgmt.machinelearningservices.operations.WorkspaceConnectionsOperations
+ :ivar registry_code_containers: RegistryCodeContainersOperations operations
+ :vartype registry_code_containers:
+ azure.mgmt.machinelearningservices.operations.RegistryCodeContainersOperations
+ :ivar registry_code_versions: RegistryCodeVersionsOperations operations
+ :vartype registry_code_versions:
+ azure.mgmt.machinelearningservices.operations.RegistryCodeVersionsOperations
+ :ivar registry_component_containers: RegistryComponentContainersOperations operations
+ :vartype registry_component_containers:
+ azure.mgmt.machinelearningservices.operations.RegistryComponentContainersOperations
+ :ivar registry_component_versions: RegistryComponentVersionsOperations operations
+ :vartype registry_component_versions:
+ azure.mgmt.machinelearningservices.operations.RegistryComponentVersionsOperations
+ :ivar registry_data_containers: RegistryDataContainersOperations operations
+ :vartype registry_data_containers:
+ azure.mgmt.machinelearningservices.operations.RegistryDataContainersOperations
+ :ivar registry_data_versions: RegistryDataVersionsOperations operations
+ :vartype registry_data_versions:
+ azure.mgmt.machinelearningservices.operations.RegistryDataVersionsOperations
+ :ivar registry_environment_containers: RegistryEnvironmentContainersOperations operations
+ :vartype registry_environment_containers:
+ azure.mgmt.machinelearningservices.operations.RegistryEnvironmentContainersOperations
+ :ivar registry_environment_versions: RegistryEnvironmentVersionsOperations operations
+ :vartype registry_environment_versions:
+ azure.mgmt.machinelearningservices.operations.RegistryEnvironmentVersionsOperations
+ :ivar registry_model_containers: RegistryModelContainersOperations operations
+ :vartype registry_model_containers:
+ azure.mgmt.machinelearningservices.operations.RegistryModelContainersOperations
+ :ivar registry_model_versions: RegistryModelVersionsOperations operations
+ :vartype registry_model_versions:
+ azure.mgmt.machinelearningservices.operations.RegistryModelVersionsOperations
:ivar batch_endpoints: BatchEndpointsOperations operations
:vartype batch_endpoints:
azure.mgmt.machinelearningservices.operations.BatchEndpointsOperations
@@ -120,6 +161,8 @@ class MachineLearningServicesMgmtClient: # pylint: disable=client-accepts-api-v
azure.mgmt.machinelearningservices.operations.OnlineDeploymentsOperations
:ivar schedules: SchedulesOperations operations
:vartype schedules: azure.mgmt.machinelearningservices.operations.SchedulesOperations
+ :ivar registries: RegistriesOperations operations
+ :vartype registries: azure.mgmt.machinelearningservices.operations.RegistriesOperations
:ivar workspace_features: WorkspaceFeaturesOperations operations
:vartype workspace_features:
azure.mgmt.machinelearningservices.operations.WorkspaceFeaturesOperations
@@ -129,7 +172,7 @@ class MachineLearningServicesMgmtClient: # pylint: disable=client-accepts-api-v
:type subscription_id: str
:param base_url: Service URL. Default value is "https://management.azure.com".
:type base_url: str
- :keyword api_version: Api Version. Default value is "2022-10-01". Note that overriding this
+ :keyword api_version: Api Version. Default value is "2023-04-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: str
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
@@ -146,7 +189,7 @@ def __init__(
self._config = MachineLearningServicesMgmtClientConfiguration(
credential=credential, subscription_id=subscription_id, **kwargs
)
- self._client = ARMPipelineClient(base_url=base_url, config=self._config, **kwargs)
+ self._client: ARMPipelineClient = ARMPipelineClient(base_url=base_url, config=self._config, **kwargs)
client_models = {k: v for k, v in _models.__dict__.items() if isinstance(v, type)}
self._serialize = Serializer(client_models)
@@ -169,6 +212,36 @@ def __init__(
self.workspace_connections = WorkspaceConnectionsOperations(
self._client, self._config, self._serialize, self._deserialize
)
+ self.registry_code_containers = RegistryCodeContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_code_versions = RegistryCodeVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_component_containers = RegistryComponentContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_component_versions = RegistryComponentVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_data_containers = RegistryDataContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_data_versions = RegistryDataVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_environment_containers = RegistryEnvironmentContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_environment_versions = RegistryEnvironmentVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_model_containers = RegistryModelContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_model_versions = RegistryModelVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
self.batch_endpoints = BatchEndpointsOperations(self._client, self._config, self._serialize, self._deserialize)
self.batch_deployments = BatchDeploymentsOperations(
self._client, self._config, self._serialize, self._deserialize
@@ -202,6 +275,7 @@ def __init__(
self._client, self._config, self._serialize, self._deserialize
)
self.schedules = SchedulesOperations(self._client, self._config, self._serialize, self._deserialize)
+ self.registries = RegistriesOperations(self._client, self._config, self._serialize, self._deserialize)
self.workspace_features = WorkspaceFeaturesOperations(
self._client, self._config, self._serialize, self._deserialize
)
@@ -235,5 +309,5 @@ def __enter__(self) -> "MachineLearningServicesMgmtClient":
self._client.__enter__()
return self
- def __exit__(self, *exc_details) -> None:
+ def __exit__(self, *exc_details: Any) -> None:
self._client.__exit__(*exc_details)
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_serialization.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_serialization.py
index 2c170e28dbca..842ae727fbbc 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_serialization.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_serialization.py
@@ -38,7 +38,22 @@
import re
import sys
import codecs
-from typing import Optional, Union, AnyStr, IO, Mapping
+from typing import (
+ Dict,
+ Any,
+ cast,
+ Optional,
+ Union,
+ AnyStr,
+ IO,
+ Mapping,
+ Callable,
+ TypeVar,
+ MutableMapping,
+ Type,
+ List,
+ Mapping,
+)
try:
from urllib import quote # type: ignore
@@ -48,12 +63,14 @@
import isodate # type: ignore
-from typing import Dict, Any, cast
-
from azure.core.exceptions import DeserializationError, SerializationError, raise_with_traceback
+from azure.core.serialization import NULL as AzureCoreNull
_BOM = codecs.BOM_UTF8.decode(encoding="utf-8")
+ModelType = TypeVar("ModelType", bound="Model")
+JSON = MutableMapping[str, Any]
+
class RawDeserializer:
@@ -277,8 +294,8 @@ class Model(object):
_attribute_map: Dict[str, Dict[str, Any]] = {}
_validation: Dict[str, Dict[str, Any]] = {}
- def __init__(self, **kwargs):
- self.additional_properties = {}
+ def __init__(self, **kwargs: Any) -> None:
+ self.additional_properties: Dict[str, Any] = {}
for k in kwargs:
if k not in self._attribute_map:
_LOGGER.warning("%s is not a known attribute of class %s and will be ignored", k, self.__class__)
@@ -287,25 +304,25 @@ def __init__(self, **kwargs):
else:
setattr(self, k, kwargs[k])
- def __eq__(self, other):
+ def __eq__(self, other: Any) -> bool:
"""Compare objects by comparing all attributes."""
if isinstance(other, self.__class__):
return self.__dict__ == other.__dict__
return False
- def __ne__(self, other):
+ def __ne__(self, other: Any) -> bool:
"""Compare objects by comparing all attributes."""
return not self.__eq__(other)
- def __str__(self):
+ def __str__(self) -> str:
return str(self.__dict__)
@classmethod
- def enable_additional_properties_sending(cls):
+ def enable_additional_properties_sending(cls) -> None:
cls._attribute_map["additional_properties"] = {"key": "", "type": "{object}"}
@classmethod
- def is_xml_model(cls):
+ def is_xml_model(cls) -> bool:
try:
cls._xml_map # type: ignore
except AttributeError:
@@ -322,7 +339,7 @@ def _create_xml_node(cls):
return _create_xml_node(xml_map.get("name", cls.__name__), xml_map.get("prefix", None), xml_map.get("ns", None))
- def serialize(self, keep_readonly=False, **kwargs):
+ def serialize(self, keep_readonly: bool = False, **kwargs: Any) -> JSON:
"""Return the JSON that would be sent to azure from this model.
This is an alias to `as_dict(full_restapi_key_transformer, keep_readonly=False)`.
@@ -336,8 +353,13 @@ def serialize(self, keep_readonly=False, **kwargs):
serializer = Serializer(self._infer_class_models())
return serializer._serialize(self, keep_readonly=keep_readonly, **kwargs)
- def as_dict(self, keep_readonly=True, key_transformer=attribute_transformer, **kwargs):
- """Return a dict that can be JSONify using json.dump.
+ def as_dict(
+ self,
+ keep_readonly: bool = True,
+ key_transformer: Callable[[str, Dict[str, Any], Any], Any] = attribute_transformer,
+ **kwargs: Any
+ ) -> JSON:
+ """Return a dict that can be serialized using json.dump.
Advanced usage might optionally use a callback as parameter:
@@ -384,7 +406,7 @@ def _infer_class_models(cls):
return client_models
@classmethod
- def deserialize(cls, data, content_type=None):
+ def deserialize(cls: Type[ModelType], data: Any, content_type: Optional[str] = None) -> ModelType:
"""Parse a str using the RestAPI syntax and return a model.
:param str data: A str using RestAPI structure. JSON by default.
@@ -396,7 +418,12 @@ def deserialize(cls, data, content_type=None):
return deserializer(cls.__name__, data, content_type=content_type)
@classmethod
- def from_dict(cls, data, key_extractors=None, content_type=None):
+ def from_dict(
+ cls: Type[ModelType],
+ data: Any,
+ key_extractors: Optional[Callable[[str, Dict[str, Any], Any], Any]] = None,
+ content_type: Optional[str] = None,
+ ) -> ModelType:
"""Parse a dict using given key extractor return a model.
By default consider key
@@ -409,8 +436,8 @@ def from_dict(cls, data, key_extractors=None, content_type=None):
:raises: DeserializationError if something went wrong
"""
deserializer = Deserializer(cls._infer_class_models())
- deserializer.key_extractors = (
- [
+ deserializer.key_extractors = ( # type: ignore
+ [ # type: ignore
attribute_key_case_insensitive_extractor,
rest_key_case_insensitive_extractor,
last_rest_key_case_insensitive_extractor,
@@ -518,7 +545,7 @@ class Serializer(object):
"multiple": lambda x, y: x % y != 0,
}
- def __init__(self, classes=None):
+ def __init__(self, classes: Optional[Mapping[str, Type[ModelType]]] = None):
self.serialize_type = {
"iso-8601": Serializer.serialize_iso,
"rfc-1123": Serializer.serialize_rfc,
@@ -534,7 +561,7 @@ def __init__(self, classes=None):
"[]": self.serialize_iter,
"{}": self.serialize_dict,
}
- self.dependencies = dict(classes) if classes else {}
+ self.dependencies: Dict[str, Type[ModelType]] = dict(classes) if classes else {}
self.key_transformer = full_restapi_key_transformer
self.client_side_validation = True
@@ -602,7 +629,7 @@ def _serialize(self, target_obj, data_type=None, **kwargs):
if xml_desc.get("attr", False):
if xml_ns:
ET.register_namespace(xml_prefix, xml_ns)
- xml_name = "{}{}".format(xml_ns, xml_name)
+ xml_name = "{{{}}}{}".format(xml_ns, xml_name)
serialized.set(xml_name, new_attr) # type: ignore
continue
if xml_desc.get("text", False):
@@ -626,8 +653,7 @@ def _serialize(self, target_obj, data_type=None, **kwargs):
serialized.append(local_node) # type: ignore
else: # JSON
for k in reversed(keys): # type: ignore
- unflattened = {k: new_attr}
- new_attr = unflattened
+ new_attr = {k: new_attr}
_new_attr = new_attr
_serialized = serialized
@@ -656,8 +682,8 @@ def body(self, data, data_type, **kwargs):
"""
# Just in case this is a dict
- internal_data_type = data_type.strip("[]{}")
- internal_data_type = self.dependencies.get(internal_data_type, None)
+ internal_data_type_str = data_type.strip("[]{}")
+ internal_data_type = self.dependencies.get(internal_data_type_str, None)
try:
is_xml_model_serialization = kwargs["is_xml"]
except KeyError:
@@ -777,6 +803,8 @@ def serialize_data(self, data, data_type, **kwargs):
raise ValueError("No value for given attribute")
try:
+ if data is AzureCoreNull:
+ return None
if data_type in self.basic_types.values():
return self.serialize_basic(data, data_type, **kwargs)
@@ -1161,7 +1189,8 @@ def rest_key_extractor(attr, attr_desc, data):
working_data = data
while "." in key:
- dict_keys = _FLATTEN.split(key)
+ # Need the cast, as for some reasons "split" is typed as list[str | Any]
+ dict_keys = cast(List[str], _FLATTEN.split(key))
if len(dict_keys) == 1:
key = _decode_attribute_map_key(dict_keys[0])
break
@@ -1242,7 +1271,7 @@ def _extract_name_from_internal_type(internal_type):
xml_name = internal_type_xml_map.get("name", internal_type.__name__)
xml_ns = internal_type_xml_map.get("ns", None)
if xml_ns:
- xml_name = "{}{}".format(xml_ns, xml_name)
+ xml_name = "{{{}}}{}".format(xml_ns, xml_name)
return xml_name
@@ -1266,7 +1295,7 @@ def xml_key_extractor(attr, attr_desc, data):
# Integrate namespace if necessary
xml_ns = xml_desc.get("ns", internal_type_xml_map.get("ns", None))
if xml_ns:
- xml_name = "{}{}".format(xml_ns, xml_name)
+ xml_name = "{{{}}}{}".format(xml_ns, xml_name)
# If it's an attribute, that's simple
if xml_desc.get("attr", False):
@@ -1332,7 +1361,7 @@ class Deserializer(object):
valid_date = re.compile(r"\d{4}[-]\d{2}[-]\d{2}T\d{2}:\d{2}:\d{2}" r"\.?\d*Z?[-+]?[\d{2}]?:?[\d{2}]?")
- def __init__(self, classes=None):
+ def __init__(self, classes: Optional[Mapping[str, Type[ModelType]]] = None):
self.deserialize_type = {
"iso-8601": Deserializer.deserialize_iso,
"rfc-1123": Deserializer.deserialize_rfc,
@@ -1352,7 +1381,7 @@ def __init__(self, classes=None):
"duration": (isodate.Duration, datetime.timedelta),
"iso-8601": (datetime.datetime),
}
- self.dependencies = dict(classes) if classes else {}
+ self.dependencies: Dict[str, Type[ModelType]] = dict(classes) if classes else {}
self.key_extractors = [rest_key_extractor, xml_key_extractor]
# Additional properties only works if the "rest_key_extractor" is used to
# extract the keys. Making it to work whatever the key extractor is too much
@@ -1471,7 +1500,7 @@ def _classify_target(self, target, data):
Once classification has been determined, initialize object.
:param str target: The target object type to deserialize to.
- :param str/dict data: The response data to deseralize.
+ :param str/dict data: The response data to deserialize.
"""
if target is None:
return None, None
@@ -1486,7 +1515,7 @@ def _classify_target(self, target, data):
target = target._classify(data, self.dependencies)
except AttributeError:
pass # Target is not a Model, no classify
- return target, target.__class__.__name__
+ return target, target.__class__.__name__ # type: ignore
def failsafe_deserialize(self, target_obj, data, content_type=None):
"""Ignores any errors encountered in deserialization,
@@ -1496,7 +1525,7 @@ def failsafe_deserialize(self, target_obj, data, content_type=None):
a deserialization error.
:param str target_obj: The target object type to deserialize to.
- :param str/dict data: The response data to deseralize.
+ :param str/dict data: The response data to deserialize.
:param str content_type: Swagger "produces" if available.
"""
try:
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_vendor.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_vendor.py
index 9aad73fc743e..bd0df84f5319 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_vendor.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_vendor.py
@@ -5,6 +5,8 @@
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
+from typing import List, cast
+
from azure.core.pipeline.transport import HttpRequest
@@ -22,6 +24,7 @@ def _format_url_section(template, **kwargs):
try:
return template.format(**kwargs)
except KeyError as key:
- formatted_components = template.split("/")
+ # Need the cast, as for some reasons "split" is typed as list[str | Any]
+ formatted_components = cast(List[str], template.split("/"))
components = [c for c in formatted_components if "{}".format(key.args[0]) not in c]
template = "/".join(components)
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_version.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_version.py
index e32dc6ec4218..e5754a47ce68 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_version.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/_version.py
@@ -6,4 +6,4 @@
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-VERSION = "2.0.0b1"
+VERSION = "1.0.0b1"
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/_configuration.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/_configuration.py
index 88eada53ff68..f012a758393b 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/_configuration.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/_configuration.py
@@ -6,7 +6,6 @@
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, TYPE_CHECKING
from azure.core.configuration import Configuration
@@ -15,11 +14,6 @@
from .._version import VERSION
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
-
if TYPE_CHECKING:
# pylint: disable=unused-import,ungrouped-imports
from azure.core.credentials_async import AsyncTokenCredential
@@ -35,14 +29,14 @@ class MachineLearningServicesMgmtClientConfiguration(Configuration): # pylint:
:type credential: ~azure.core.credentials_async.AsyncTokenCredential
:param subscription_id: The ID of the target subscription. Required.
:type subscription_id: str
- :keyword api_version: Api Version. Default value is "2022-10-01". Note that overriding this
+ :keyword api_version: Api Version. Default value is "2023-04-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: str
"""
def __init__(self, credential: "AsyncTokenCredential", subscription_id: str, **kwargs: Any) -> None:
super(MachineLearningServicesMgmtClientConfiguration, self).__init__(**kwargs)
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", "2022-10-01")
+ api_version: str = kwargs.pop("api_version", "2023-04-01")
if credential is None:
raise ValueError("Parameter 'credential' must not be None.")
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/_machine_learning_services_mgmt_client.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/_machine_learning_services_mgmt_client.py
index 4c1c840cfff5..0240f80e8769 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/_machine_learning_services_mgmt_client.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/_machine_learning_services_mgmt_client.py
@@ -37,6 +37,17 @@
PrivateEndpointConnectionsOperations,
PrivateLinkResourcesOperations,
QuotasOperations,
+ RegistriesOperations,
+ RegistryCodeContainersOperations,
+ RegistryCodeVersionsOperations,
+ RegistryComponentContainersOperations,
+ RegistryComponentVersionsOperations,
+ RegistryDataContainersOperations,
+ RegistryDataVersionsOperations,
+ RegistryEnvironmentContainersOperations,
+ RegistryEnvironmentVersionsOperations,
+ RegistryModelContainersOperations,
+ RegistryModelVersionsOperations,
SchedulesOperations,
UsagesOperations,
VirtualMachineSizesOperations,
@@ -75,6 +86,36 @@ class MachineLearningServicesMgmtClient: # pylint: disable=client-accepts-api-v
:ivar workspace_connections: WorkspaceConnectionsOperations operations
:vartype workspace_connections:
azure.mgmt.machinelearningservices.aio.operations.WorkspaceConnectionsOperations
+ :ivar registry_code_containers: RegistryCodeContainersOperations operations
+ :vartype registry_code_containers:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryCodeContainersOperations
+ :ivar registry_code_versions: RegistryCodeVersionsOperations operations
+ :vartype registry_code_versions:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryCodeVersionsOperations
+ :ivar registry_component_containers: RegistryComponentContainersOperations operations
+ :vartype registry_component_containers:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryComponentContainersOperations
+ :ivar registry_component_versions: RegistryComponentVersionsOperations operations
+ :vartype registry_component_versions:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryComponentVersionsOperations
+ :ivar registry_data_containers: RegistryDataContainersOperations operations
+ :vartype registry_data_containers:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryDataContainersOperations
+ :ivar registry_data_versions: RegistryDataVersionsOperations operations
+ :vartype registry_data_versions:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryDataVersionsOperations
+ :ivar registry_environment_containers: RegistryEnvironmentContainersOperations operations
+ :vartype registry_environment_containers:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryEnvironmentContainersOperations
+ :ivar registry_environment_versions: RegistryEnvironmentVersionsOperations operations
+ :vartype registry_environment_versions:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryEnvironmentVersionsOperations
+ :ivar registry_model_containers: RegistryModelContainersOperations operations
+ :vartype registry_model_containers:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryModelContainersOperations
+ :ivar registry_model_versions: RegistryModelVersionsOperations operations
+ :vartype registry_model_versions:
+ azure.mgmt.machinelearningservices.aio.operations.RegistryModelVersionsOperations
:ivar batch_endpoints: BatchEndpointsOperations operations
:vartype batch_endpoints:
azure.mgmt.machinelearningservices.aio.operations.BatchEndpointsOperations
@@ -123,6 +164,8 @@ class MachineLearningServicesMgmtClient: # pylint: disable=client-accepts-api-v
azure.mgmt.machinelearningservices.aio.operations.OnlineDeploymentsOperations
:ivar schedules: SchedulesOperations operations
:vartype schedules: azure.mgmt.machinelearningservices.aio.operations.SchedulesOperations
+ :ivar registries: RegistriesOperations operations
+ :vartype registries: azure.mgmt.machinelearningservices.aio.operations.RegistriesOperations
:ivar workspace_features: WorkspaceFeaturesOperations operations
:vartype workspace_features:
azure.mgmt.machinelearningservices.aio.operations.WorkspaceFeaturesOperations
@@ -132,7 +175,7 @@ class MachineLearningServicesMgmtClient: # pylint: disable=client-accepts-api-v
:type subscription_id: str
:param base_url: Service URL. Default value is "https://management.azure.com".
:type base_url: str
- :keyword api_version: Api Version. Default value is "2022-10-01". Note that overriding this
+ :keyword api_version: Api Version. Default value is "2023-04-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: str
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
@@ -149,7 +192,7 @@ def __init__(
self._config = MachineLearningServicesMgmtClientConfiguration(
credential=credential, subscription_id=subscription_id, **kwargs
)
- self._client = AsyncARMPipelineClient(base_url=base_url, config=self._config, **kwargs)
+ self._client: AsyncARMPipelineClient = AsyncARMPipelineClient(base_url=base_url, config=self._config, **kwargs)
client_models = {k: v for k, v in _models.__dict__.items() if isinstance(v, type)}
self._serialize = Serializer(client_models)
@@ -172,6 +215,36 @@ def __init__(
self.workspace_connections = WorkspaceConnectionsOperations(
self._client, self._config, self._serialize, self._deserialize
)
+ self.registry_code_containers = RegistryCodeContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_code_versions = RegistryCodeVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_component_containers = RegistryComponentContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_component_versions = RegistryComponentVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_data_containers = RegistryDataContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_data_versions = RegistryDataVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_environment_containers = RegistryEnvironmentContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_environment_versions = RegistryEnvironmentVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_model_containers = RegistryModelContainersOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+ self.registry_model_versions = RegistryModelVersionsOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
self.batch_endpoints = BatchEndpointsOperations(self._client, self._config, self._serialize, self._deserialize)
self.batch_deployments = BatchDeploymentsOperations(
self._client, self._config, self._serialize, self._deserialize
@@ -205,6 +278,7 @@ def __init__(
self._client, self._config, self._serialize, self._deserialize
)
self.schedules = SchedulesOperations(self._client, self._config, self._serialize, self._deserialize)
+ self.registries = RegistriesOperations(self._client, self._config, self._serialize, self._deserialize)
self.workspace_features = WorkspaceFeaturesOperations(
self._client, self._config, self._serialize, self._deserialize
)
@@ -238,5 +312,5 @@ async def __aenter__(self) -> "MachineLearningServicesMgmtClient":
await self._client.__aenter__()
return self
- async def __aexit__(self, *exc_details) -> None:
+ async def __aexit__(self, *exc_details: Any) -> None:
await self._client.__aexit__(*exc_details)
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/__init__.py
index 0065485916d9..4967e3af6930 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/__init__.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/__init__.py
@@ -15,6 +15,16 @@
from ._private_endpoint_connections_operations import PrivateEndpointConnectionsOperations
from ._private_link_resources_operations import PrivateLinkResourcesOperations
from ._workspace_connections_operations import WorkspaceConnectionsOperations
+from ._registry_code_containers_operations import RegistryCodeContainersOperations
+from ._registry_code_versions_operations import RegistryCodeVersionsOperations
+from ._registry_component_containers_operations import RegistryComponentContainersOperations
+from ._registry_component_versions_operations import RegistryComponentVersionsOperations
+from ._registry_data_containers_operations import RegistryDataContainersOperations
+from ._registry_data_versions_operations import RegistryDataVersionsOperations
+from ._registry_environment_containers_operations import RegistryEnvironmentContainersOperations
+from ._registry_environment_versions_operations import RegistryEnvironmentVersionsOperations
+from ._registry_model_containers_operations import RegistryModelContainersOperations
+from ._registry_model_versions_operations import RegistryModelVersionsOperations
from ._batch_endpoints_operations import BatchEndpointsOperations
from ._batch_deployments_operations import BatchDeploymentsOperations
from ._code_containers_operations import CodeContainersOperations
@@ -32,6 +42,7 @@
from ._online_endpoints_operations import OnlineEndpointsOperations
from ._online_deployments_operations import OnlineDeploymentsOperations
from ._schedules_operations import SchedulesOperations
+from ._registries_operations import RegistriesOperations
from ._workspace_features_operations import WorkspaceFeaturesOperations
from ._patch import __all__ as _patch_all
@@ -48,6 +59,16 @@
"PrivateEndpointConnectionsOperations",
"PrivateLinkResourcesOperations",
"WorkspaceConnectionsOperations",
+ "RegistryCodeContainersOperations",
+ "RegistryCodeVersionsOperations",
+ "RegistryComponentContainersOperations",
+ "RegistryComponentVersionsOperations",
+ "RegistryDataContainersOperations",
+ "RegistryDataVersionsOperations",
+ "RegistryEnvironmentContainersOperations",
+ "RegistryEnvironmentVersionsOperations",
+ "RegistryModelContainersOperations",
+ "RegistryModelVersionsOperations",
"BatchEndpointsOperations",
"BatchDeploymentsOperations",
"CodeContainersOperations",
@@ -65,6 +86,7 @@
"OnlineEndpointsOperations",
"OnlineDeploymentsOperations",
"SchedulesOperations",
+ "RegistriesOperations",
"WorkspaceFeaturesOperations",
]
__all__.extend([p for p in _patch_all if p not in __all__])
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_batch_deployments_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_batch_deployments_operations.py
index 37950b084904..09a5fbbc9049 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_batch_deployments_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_batch_deployments_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -39,10 +38,6 @@
build_update_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -103,9 +98,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.BatchDeploymentTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -163,8 +156,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -195,9 +189,7 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -214,8 +206,9 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -272,9 +265,7 @@ async def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -298,7 +289,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -349,9 +342,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.BatchDeployment] = kwargs.pop("cls", None)
request = build_get_request(
@@ -368,8 +359,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -410,9 +402,7 @@ async def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.BatchDeployment]] = kwargs.pop("cls", None)
@@ -441,8 +431,9 @@ async def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -587,8 +578,8 @@ async def begin_update(
:type endpoint_name: str
:param deployment_name: The identifier for the Batch inference deployment. Required.
:type deployment_name: str
- :param body: Batch inference deployment definition object. Is either a model type or a IO type.
- Required.
+ :param body: Batch inference deployment definition object. Is either a
+ PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties type or a IO type. Required.
:type body:
~azure.mgmt.machinelearningservices.models.PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties
or IO
@@ -612,9 +603,7 @@ async def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchDeployment] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -681,9 +670,7 @@ async def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchDeployment] = kwargs.pop("cls", None)
@@ -712,8 +699,9 @@ async def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -859,8 +847,8 @@ async def begin_create_or_update(
:type endpoint_name: str
:param deployment_name: The identifier for the Batch inference deployment. Required.
:type deployment_name: str
- :param body: Batch inference deployment definition object. Is either a model type or a IO type.
- Required.
+ :param body: Batch inference deployment definition object. Is either a BatchDeployment type or
+ a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.BatchDeployment or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -882,9 +870,7 @@ async def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchDeployment] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -913,7 +899,10 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_batch_endpoints_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_batch_endpoints_operations.py
index 848fe6dc7e27..89a1a70c2287 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_batch_endpoints_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_batch_endpoints_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -40,10 +39,6 @@
build_update_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -98,9 +93,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.BatchEndpointTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -156,8 +149,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -188,9 +182,7 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -206,8 +198,9 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -262,9 +255,7 @@ async def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -287,7 +278,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -336,9 +329,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.BatchEndpoint] = kwargs.pop("cls", None)
request = build_get_request(
@@ -354,8 +345,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -395,9 +387,7 @@ async def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.BatchEndpoint]] = kwargs.pop("cls", None)
@@ -425,8 +415,9 @@ async def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -562,8 +553,8 @@ async def begin_update(
:type workspace_name: str
:param endpoint_name: Name for the Batch inference endpoint. Required.
:type endpoint_name: str
- :param body: Mutable batch inference endpoint definition object. Is either a model type or a IO
- type. Required.
+ :param body: Mutable batch inference endpoint definition object. Is either a
+ PartialMinimalTrackedResourceWithIdentity type or a IO type. Required.
:type body:
~azure.mgmt.machinelearningservices.models.PartialMinimalTrackedResourceWithIdentity or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -586,9 +577,7 @@ async def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchEndpoint] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -653,9 +642,7 @@ async def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchEndpoint] = kwargs.pop("cls", None)
@@ -683,8 +670,9 @@ async def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -821,8 +809,8 @@ async def begin_create_or_update(
:type workspace_name: str
:param endpoint_name: Name for the Batch inference endpoint. Required.
:type endpoint_name: str
- :param body: Batch inference endpoint definition object. Is either a model type or a IO type.
- Required.
+ :param body: Batch inference endpoint definition object. Is either a BatchEndpoint type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.BatchEndpoint or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -844,9 +832,7 @@ async def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchEndpoint] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -874,7 +860,10 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -923,9 +912,7 @@ async def list_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EndpointAuthKeys] = kwargs.pop("cls", None)
request = build_list_keys_request(
@@ -941,8 +928,9 @@ async def list_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_code_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_code_containers_operations.py
index c69213fa842c..387e735a87a2 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_code_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_code_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -87,9 +82,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.CodeContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -144,8 +137,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -193,9 +187,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -211,8 +203,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -260,9 +253,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -278,8 +269,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -386,7 +378,7 @@ async def create_or_update(
:type workspace_name: str
:param name: Container name. This is case-sensitive. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
+ :param body: Container entity to create or update. Is either a CodeContainer type or a IO type.
Required.
:type body: ~azure.mgmt.machinelearningservices.models.CodeContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -408,9 +400,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
@@ -438,8 +428,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_code_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_code_versions_operations.py
index 473dec5348b9..e0f2effe2186 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_code_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_code_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,16 +29,13 @@
from ... import models as _models
from ..._vendor import _convert_request
from ...operations._code_versions_operations import (
+ build_create_or_get_start_pending_upload_request,
build_create_or_update_request,
build_delete_request,
build_get_request,
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -72,6 +68,8 @@ def list(
order_by: Optional[str] = None,
top: Optional[int] = None,
skip: Optional[str] = None,
+ hash: Optional[str] = None,
+ hash_version: Optional[str] = None,
**kwargs: Any
) -> AsyncIterable["_models.CodeVersion"]:
"""List versions.
@@ -91,6 +89,11 @@ def list(
:type top: int
:param skip: Continuation token for pagination. Default value is None.
:type skip: str
+ :param hash: If specified, return CodeVersion assets with specified content hash value,
+ regardless of name. Default value is None.
+ :type hash: str
+ :param hash_version: Hash algorithm version when listing by hash. Default value is None.
+ :type hash_version: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CodeVersion or the result of cls(response)
:rtype:
@@ -100,9 +103,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.CodeVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -124,6 +125,8 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ hash=hash,
+ hash_version=hash_version,
api_version=api_version,
template_url=self.list.metadata["url"],
headers=_headers,
@@ -160,8 +163,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -211,9 +215,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -230,8 +232,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -281,9 +284,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
request = build_get_request(
@@ -300,8 +301,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -417,7 +419,8 @@ async def create_or_update(
:type name: str
:param version: Version identifier. This is case-sensitive. Required.
:type version: str
- :param body: Version entity to create or update. Is either a model type or a IO type. Required.
+ :param body: Version entity to create or update. Is either a CodeVersion type or a IO type.
+ Required.
:type body: ~azure.mgmt.machinelearningservices.models.CodeVersion or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -438,9 +441,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
@@ -469,8 +470,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -494,3 +496,172 @@ async def create_or_update(
create_or_update.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}"
}
+
+ @overload
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ workspace_name: str,
+ name: str,
+ version: str,
+ body: _models.PendingUploadRequestDto,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace. Required.
+ :type workspace_name: str
+ :param name: Container name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ workspace_name: str,
+ name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace. Required.
+ :type workspace_name: str
+ :param name: Container name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ workspace_name: str,
+ name: str,
+ version: str,
+ body: Union[_models.PendingUploadRequestDto, IO],
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace. Required.
+ :type workspace_name: str
+ :param name: Container name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Is either a PendingUploadRequestDto type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.PendingUploadResponseDto] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PendingUploadRequestDto")
+
+ request = build_create_or_get_start_pending_upload_request(
+ resource_group_name=resource_group_name,
+ workspace_name=workspace_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.create_or_get_start_pending_upload.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("PendingUploadResponseDto", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_start_pending_upload.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}/startPendingUpload"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_component_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_component_containers_operations.py
index 59f121afb4b1..f3a450ff346c 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_component_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_component_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -95,9 +90,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComponentContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -153,8 +146,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -202,9 +196,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -220,8 +212,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -269,9 +262,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -287,8 +278,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -395,8 +387,8 @@ async def create_or_update(
:type workspace_name: str
:param name: Container name. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
- Required.
+ :param body: Container entity to create or update. Is either a ComponentContainer type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.ComponentContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -417,9 +409,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
@@ -447,8 +437,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_component_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_component_versions_operations.py
index f217f6650def..530b0cb311c9 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_component_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_component_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -104,9 +99,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComponentVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -165,8 +158,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -216,9 +210,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -235,8 +227,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -286,9 +279,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
request = build_get_request(
@@ -305,8 +296,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -422,7 +414,8 @@ async def create_or_update(
:type name: str
:param version: Version identifier. Required.
:type version: str
- :param body: Version entity to create or update. Is either a model type or a IO type. Required.
+ :param body: Version entity to create or update. Is either a ComponentVersion type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.ComponentVersion or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -443,9 +436,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
@@ -474,8 +465,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_compute_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_compute_operations.py
index 382828847481..033d0d3330fd 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_compute_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_compute_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -44,10 +43,6 @@
build_update_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -93,9 +88,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.PaginatedComputeResourcesList] = kwargs.pop("cls", None)
error_map = {
@@ -150,8 +143,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -198,9 +192,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
request = build_get_request(
@@ -216,8 +208,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -257,9 +250,7 @@ async def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
@@ -287,8 +278,9 @@ async def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -422,8 +414,8 @@ async def begin_create_or_update(
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute. Required.
:type compute_name: str
- :param parameters: Payload with Machine Learning compute definition. Is either a model type or
- a IO type. Required.
+ :param parameters: Payload with Machine Learning compute definition. Is either a
+ ComputeResource type or a IO type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.ComputeResource or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -445,9 +437,7 @@ async def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -512,9 +502,7 @@ async def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
@@ -542,8 +530,9 @@ async def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -665,8 +654,8 @@ async def begin_update(
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute. Required.
:type compute_name: str
- :param parameters: Additional parameters for cluster update. Is either a model type or a IO
- type. Required.
+ :param parameters: Additional parameters for cluster update. Is either a
+ ClusterUpdateParameters type or a IO type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.ClusterUpdateParameters or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -688,9 +677,7 @@ async def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -755,9 +742,7 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -774,8 +759,9 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -837,9 +823,7 @@ async def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -904,9 +888,7 @@ def list_nodes(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.AmlComputeNodesInformation] = kwargs.pop("cls", None)
error_map = {
@@ -961,8 +943,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1008,9 +991,7 @@ async def list_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComputeSecrets] = kwargs.pop("cls", None)
request = build_list_keys_request(
@@ -1026,8 +1007,9 @@ async def list_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1062,9 +1044,7 @@ async def _start_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_start_request(
@@ -1080,8 +1060,9 @@ async def _start_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1126,9 +1107,7 @@ async def begin_start(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1183,9 +1162,7 @@ async def _stop_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_stop_request(
@@ -1201,8 +1178,9 @@ async def _stop_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1247,9 +1225,7 @@ async def begin_stop(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1304,9 +1280,7 @@ async def _restart_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_restart_request(
@@ -1322,8 +1296,9 @@ async def _restart_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1368,9 +1343,7 @@ async def begin_restart(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_data_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_data_containers_operations.py
index 4c5aca387b8f..e309a49a13ce 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_data_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_data_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -95,9 +90,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DataContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -153,8 +146,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -202,9 +196,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -220,8 +212,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -269,9 +262,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -287,8 +278,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -395,7 +387,7 @@ async def create_or_update(
:type workspace_name: str
:param name: Container name. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
+ :param body: Container entity to create or update. Is either a DataContainer type or a IO type.
Required.
:type body: ~azure.mgmt.machinelearningservices.models.DataContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -417,9 +409,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
@@ -447,8 +437,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_data_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_data_versions_operations.py
index a9f90dd943ed..d6274c502967 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_data_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_data_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -112,9 +107,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DataVersionBaseResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -174,8 +167,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -225,9 +219,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -244,8 +236,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -295,9 +288,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
request = build_get_request(
@@ -314,8 +305,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -431,7 +423,8 @@ async def create_or_update(
:type name: str
:param version: Version identifier. Required.
:type version: str
- :param body: Version entity to create or update. Is either a model type or a IO type. Required.
+ :param body: Version entity to create or update. Is either a DataVersionBase type or a IO type.
+ Required.
:type body: ~azure.mgmt.machinelearningservices.models.DataVersionBase or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -452,9 +445,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
@@ -483,8 +474,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_datastores_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_datastores_operations.py
index 293c073184e6..1cb11f9be015 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_datastores_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_datastores_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, List, Optional, TypeVar, Union, overload
import urllib.parse
@@ -37,10 +36,6 @@
build_list_secrets_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -110,9 +105,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DatastoreResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -173,8 +166,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -222,9 +216,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -240,8 +232,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -287,9 +280,7 @@ async def get(self, resource_group_name: str, workspace_name: str, name: str, **
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.Datastore] = kwargs.pop("cls", None)
request = build_get_request(
@@ -305,8 +296,9 @@ async def get(self, resource_group_name: str, workspace_name: str, name: str, **
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -420,7 +412,7 @@ async def create_or_update(
:type workspace_name: str
:param name: Datastore name. Required.
:type name: str
- :param body: Datastore entity to create or update. Is either a model type or a IO type.
+ :param body: Datastore entity to create or update. Is either a Datastore type or a IO type.
Required.
:type body: ~azure.mgmt.machinelearningservices.models.Datastore or IO
:param skip_validation: Flag to skip validation. Default value is False.
@@ -444,9 +436,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Datastore] = kwargs.pop("cls", None)
@@ -475,8 +465,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -532,9 +523,7 @@ async def list_secrets(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DatastoreSecrets] = kwargs.pop("cls", None)
request = build_list_secrets_request(
@@ -550,8 +539,9 @@ async def list_secrets(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_environment_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_environment_containers_operations.py
index 0115c7250a43..84a18f64fc6a 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_environment_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_environment_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -96,9 +91,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EnvironmentContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -154,8 +147,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -203,9 +197,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -221,8 +213,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -270,9 +263,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -288,8 +279,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -396,8 +388,8 @@ async def create_or_update(
:type workspace_name: str
:param name: Container name. This is case-sensitive. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
- Required.
+ :param body: Container entity to create or update. Is either a EnvironmentContainer type or a
+ IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.EnvironmentContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -418,9 +410,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
@@ -448,8 +438,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_environment_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_environment_versions_operations.py
index 8b4432552f55..f0836386b26b 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_environment_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_environment_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -104,9 +99,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EnvironmentVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -165,8 +158,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -216,9 +210,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -235,8 +227,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -286,9 +279,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
request = build_get_request(
@@ -305,8 +296,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -422,7 +414,8 @@ async def create_or_update(
:type name: str
:param version: Version of EnvironmentVersion. Required.
:type version: str
- :param body: Definition of EnvironmentVersion. Is either a model type or a IO type. Required.
+ :param body: Definition of EnvironmentVersion. Is either a EnvironmentVersion type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.EnvironmentVersion or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -443,9 +436,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
@@ -474,8 +465,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_jobs_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_jobs_operations.py
index e8e3110d7004..3cf7df6dca87 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_jobs_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_jobs_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -39,10 +38,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -104,9 +99,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.JobBaseResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -164,8 +157,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -196,9 +190,7 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -214,8 +206,9 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -270,9 +263,7 @@ async def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -295,7 +286,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -342,9 +335,7 @@ async def get(self, resource_group_name: str, workspace_name: str, id: str, **kw
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.JobBase] = kwargs.pop("cls", None)
request = build_get_request(
@@ -360,8 +351,9 @@ async def get(self, resource_group_name: str, workspace_name: str, id: str, **kw
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -463,7 +455,7 @@ async def create_or_update(
:type workspace_name: str
:param id: The name and identifier for the Job. This is case-sensitive. Required.
:type id: str
- :param body: Job definition object. Is either a model type or a IO type. Required.
+ :param body: Job definition object. Is either a JobBase type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.JobBase or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -484,9 +476,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.JobBase] = kwargs.pop("cls", None)
@@ -514,8 +504,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -554,9 +545,7 @@ async def _cancel_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_cancel_request(
@@ -572,8 +561,9 @@ async def _cancel_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -625,9 +615,7 @@ async def begin_cancel(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_model_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_model_containers_operations.py
index 0f18875a197a..a194c47e9375 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_model_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_model_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -98,9 +93,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ModelContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -157,8 +150,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -206,9 +200,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -224,8 +216,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -273,9 +266,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -291,8 +282,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -399,8 +391,8 @@ async def create_or_update(
:type workspace_name: str
:param name: Container name. This is case-sensitive. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
- Required.
+ :param body: Container entity to create or update. Is either a ModelContainer type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.ModelContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -421,9 +413,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
@@ -451,8 +441,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_model_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_model_versions_operations.py
index 68a4fd3be570..026d4ce11152 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_model_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_model_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -124,9 +119,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ModelVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -191,8 +184,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -242,9 +236,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -261,8 +253,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -312,9 +305,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
request = build_get_request(
@@ -331,8 +322,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -448,7 +440,8 @@ async def create_or_update(
:type name: str
:param version: Version identifier. This is case-sensitive. Required.
:type version: str
- :param body: Version entity to create or update. Is either a model type or a IO type. Required.
+ :param body: Version entity to create or update. Is either a ModelVersion type or a IO type.
+ Required.
:type body: ~azure.mgmt.machinelearningservices.models.ModelVersion or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -469,9 +462,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
@@ -500,8 +491,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_online_deployments_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_online_deployments_operations.py
index f78323104bda..dac6914354cc 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_online_deployments_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_online_deployments_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -41,10 +40,6 @@
build_update_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -105,9 +100,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.OnlineDeploymentTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -165,8 +158,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -197,9 +191,7 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -216,8 +208,9 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -274,9 +267,7 @@ async def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -300,7 +291,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -351,9 +344,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.OnlineDeployment] = kwargs.pop("cls", None)
request = build_get_request(
@@ -370,8 +361,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -412,9 +404,7 @@ async def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.OnlineDeployment]] = kwargs.pop("cls", None)
@@ -443,8 +433,9 @@ async def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -588,8 +579,8 @@ async def begin_update(
:type endpoint_name: str
:param deployment_name: Inference Endpoint Deployment name. Required.
:type deployment_name: str
- :param body: Online Endpoint entity to apply during operation. Is either a model type or a IO
- type. Required.
+ :param body: Online Endpoint entity to apply during operation. Is either a
+ PartialMinimalTrackedResourceWithSku type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.PartialMinimalTrackedResourceWithSku or
IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -612,9 +603,7 @@ async def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineDeployment] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -681,9 +670,7 @@ async def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineDeployment] = kwargs.pop("cls", None)
@@ -712,8 +699,9 @@ async def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -859,8 +847,8 @@ async def begin_create_or_update(
:type endpoint_name: str
:param deployment_name: Inference Endpoint Deployment name. Required.
:type deployment_name: str
- :param body: Inference Endpoint entity to apply during operation. Is either a model type or a
- IO type. Required.
+ :param body: Inference Endpoint entity to apply during operation. Is either a OnlineDeployment
+ type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.OnlineDeployment or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -882,9 +870,7 @@ async def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineDeployment] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -913,7 +899,10 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -1026,8 +1015,8 @@ async def get_logs(
:type endpoint_name: str
:param deployment_name: The name and identifier for the endpoint. Required.
:type deployment_name: str
- :param body: The request containing parameters for retrieving logs. Is either a model type or a
- IO type. Required.
+ :param body: The request containing parameters for retrieving logs. Is either a
+ DeploymentLogsRequest type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.DeploymentLogsRequest or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1048,9 +1037,7 @@ async def get_logs(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.DeploymentLogs] = kwargs.pop("cls", None)
@@ -1079,8 +1066,9 @@ async def get_logs(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1138,9 +1126,7 @@ def list_skus(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.SkuResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -1198,8 +1184,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_online_endpoints_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_online_endpoints_operations.py
index bb9f50e9e7b8..3d8cb4bace2a 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_online_endpoints_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_online_endpoints_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -42,10 +41,6 @@
build_update_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -121,9 +116,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.OnlineEndpointTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -184,8 +177,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -216,9 +210,7 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -234,8 +226,9 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -290,9 +283,7 @@ async def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -315,7 +306,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -364,9 +357,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.OnlineEndpoint] = kwargs.pop("cls", None)
request = build_get_request(
@@ -382,8 +373,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -423,9 +415,7 @@ async def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.OnlineEndpoint]] = kwargs.pop("cls", None)
@@ -453,8 +443,9 @@ async def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -590,8 +581,8 @@ async def begin_update(
:type workspace_name: str
:param endpoint_name: Online Endpoint name. Required.
:type endpoint_name: str
- :param body: Online Endpoint entity to apply during operation. Is either a model type or a IO
- type. Required.
+ :param body: Online Endpoint entity to apply during operation. Is either a
+ PartialMinimalTrackedResourceWithIdentity type or a IO type. Required.
:type body:
~azure.mgmt.machinelearningservices.models.PartialMinimalTrackedResourceWithIdentity or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -614,9 +605,7 @@ async def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineEndpoint] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -681,9 +670,7 @@ async def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineEndpoint] = kwargs.pop("cls", None)
@@ -711,8 +698,9 @@ async def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -849,8 +837,8 @@ async def begin_create_or_update(
:type workspace_name: str
:param endpoint_name: Online Endpoint name. Required.
:type endpoint_name: str
- :param body: Online Endpoint entity to apply during operation. Is either a model type or a IO
- type. Required.
+ :param body: Online Endpoint entity to apply during operation. Is either a OnlineEndpoint type
+ or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.OnlineEndpoint or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -872,9 +860,7 @@ async def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineEndpoint] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -902,7 +888,10 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -951,9 +940,7 @@ async def list_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EndpointAuthKeys] = kwargs.pop("cls", None)
request = build_list_keys_request(
@@ -969,8 +956,9 @@ async def list_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1010,9 +998,7 @@ async def _regenerate_keys_initial( # pylint: disable=inconsistent-return-state
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[None] = kwargs.pop("cls", None)
@@ -1040,8 +1026,9 @@ async def _regenerate_keys_initial( # pylint: disable=inconsistent-return-state
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1163,7 +1150,8 @@ async def begin_regenerate_keys(
:type workspace_name: str
:param endpoint_name: Online Endpoint name. Required.
:type endpoint_name: str
- :param body: RegenerateKeys request . Is either a model type or a IO type. Required.
+ :param body: RegenerateKeys request . Is either a RegenerateEndpointKeysRequest type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.RegenerateEndpointKeysRequest or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1183,9 +1171,7 @@ async def begin_regenerate_keys(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -1235,9 +1221,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
async def get_token(
self, resource_group_name: str, workspace_name: str, endpoint_name: str, **kwargs: Any
) -> _models.EndpointAuthToken:
- """Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.
+ """Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.
- Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.
+ Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
@@ -1262,9 +1248,7 @@ async def get_token(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EndpointAuthToken] = kwargs.pop("cls", None)
request = build_get_token_request(
@@ -1280,8 +1264,9 @@ async def get_token(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_operations.py
index ab8aec812cd0..3edc6c4bb6de 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar
import urllib.parse
@@ -30,10 +29,6 @@
from ..._vendor import _convert_request
from ...operations._operations import build_list_request
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -70,9 +65,7 @@ def list(self, **kwargs: Any) -> AsyncIterable["_models.AmlOperation"]:
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.AmlOperationListResult] = kwargs.pop("cls", None)
error_map = {
@@ -123,8 +116,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_private_endpoint_connections_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_private_endpoint_connections_operations.py
index ca1d84b13c3e..99ac1e9cb0d3 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_private_endpoint_connections_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_private_endpoint_connections_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -84,9 +79,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.PrivateEndpointConnectionListResult] = kwargs.pop("cls", None)
error_map = {
@@ -140,8 +133,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -188,9 +182,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.PrivateEndpointConnection] = kwargs.pop("cls", None)
request = build_get_request(
@@ -206,8 +198,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -311,8 +304,8 @@ async def create_or_update(
:param private_endpoint_connection_name: The name of the private endpoint connection associated
with the workspace. Required.
:type private_endpoint_connection_name: str
- :param properties: The private endpoint connection properties. Is either a model type or a IO
- type. Required.
+ :param properties: The private endpoint connection properties. Is either a
+ PrivateEndpointConnection type or a IO type. Required.
:type properties: ~azure.mgmt.machinelearningservices.models.PrivateEndpointConnection or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -333,9 +326,7 @@ async def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.PrivateEndpointConnection] = kwargs.pop("cls", None)
@@ -363,8 +354,9 @@ async def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -415,9 +407,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -433,8 +423,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_private_link_resources_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_private_link_resources_operations.py
index 8c30d300602a..3e0bfcb8b50c 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_private_link_resources_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_private_link_resources_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, Optional, TypeVar
from azure.core.exceptions import (
@@ -28,10 +27,6 @@
from ..._vendor import _convert_request
from ...operations._private_link_resources_operations import build_list_request
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -82,9 +77,7 @@ async def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.PrivateLinkResourceListResult] = kwargs.pop("cls", None)
request = build_list_request(
@@ -99,8 +92,9 @@ async def list(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_quotas_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_quotas_operations.py
index b101e920473f..2ecd3289b17e 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_quotas_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_quotas_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -31,10 +30,6 @@
from ..._vendor import _convert_request
from ...operations._quotas_operations import build_list_request, build_update_request
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -109,7 +104,8 @@ async def update(
:param location: The location for update quota is queried. Required.
:type location: str
- :param parameters: Quota update parameters. Is either a model type or a IO type. Required.
+ :param parameters: Quota update parameters. Is either a QuotaUpdateParameters type or a IO
+ type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.QuotaUpdateParameters or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -130,9 +126,7 @@ async def update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.UpdateWorkspaceQuotasResult] = kwargs.pop("cls", None)
@@ -158,8 +152,9 @@ async def update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -195,9 +190,7 @@ def list(self, location: str, **kwargs: Any) -> AsyncIterable["_models.ResourceQ
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListWorkspaceQuotas] = kwargs.pop("cls", None)
error_map = {
@@ -250,8 +243,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registries_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registries_operations.py
new file mode 100644
index 000000000000..9c1d1aa98366
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registries_operations.py
@@ -0,0 +1,1049 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registries_operations import (
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_by_subscription_request,
+ build_list_request,
+ build_remove_regions_request,
+ build_update_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistriesOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registries` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list_by_subscription(self, **kwargs: Any) -> AsyncIterable["_models.Registry"]:
+ """List registries by subscription.
+
+ List registries by subscription.
+
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either Registry or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.RegistryTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_by_subscription_request(
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.list_by_subscription.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("RegistryTrackedResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list_by_subscription.metadata = {
+ "url": "/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/registries"
+ }
+
+ @distributed_trace
+ def list(self, resource_group_name: str, **kwargs: Any) -> AsyncIterable["_models.Registry"]:
+ """List registries.
+
+ List registries.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either Registry or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.RegistryTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("RegistryTrackedResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(self, resource_group_name: str, registry_name: str, **kwargs: Any) -> AsyncLROPoller[None]:
+ """Delete registry.
+
+ Delete registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ @distributed_trace_async
+ async def get(self, resource_group_name: str, registry_name: str, **kwargs: Any) -> _models.Registry:
+ """Get registry.
+
+ Get registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: Registry or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.Registry
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ @overload
+ async def update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: _models.PartialRegistryPartialTrackedResource,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.Registry:
+ """Update tags.
+
+ Update tags.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PartialRegistryPartialTrackedResource
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: Registry or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.Registry
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.Registry:
+ """Update tags.
+
+ Update tags.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: Registry or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.Registry
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: Union[_models.PartialRegistryPartialTrackedResource, IO],
+ **kwargs: Any
+ ) -> _models.Registry:
+ """Update tags.
+
+ Update tags.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Is either a
+ PartialRegistryPartialTrackedResource type or a IO type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PartialRegistryPartialTrackedResource or
+ IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: Registry or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.Registry
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PartialRegistryPartialTrackedResource")
+
+ request = build_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.update.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ async def _create_or_update_initial(
+ self, resource_group_name: str, registry_name: str, body: Union[_models.Registry, IO], **kwargs: Any
+ ) -> _models.Registry:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "Registry")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ if response.status_code == 200:
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if response.status_code == 201:
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: _models.Registry,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.Registry]:
+ """Create or update registry.
+
+ Create or update registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.Registry
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either Registry or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.Registry]:
+ """Create or update registry.
+
+ Create or update registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either Registry or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self, resource_group_name: str, registry_name: str, body: Union[_models.Registry, IO], **kwargs: Any
+ ) -> AsyncLROPoller[_models.Registry]:
+ """Create or update registry.
+
+ Create or update registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Is either a Registry type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.Registry or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either Registry or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("Registry", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "azure-async-operation"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ async def _remove_regions_initial(
+ self, resource_group_name: str, registry_name: str, body: Union[_models.Registry, IO], **kwargs: Any
+ ) -> Optional[_models.Registry]:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[Optional[_models.Registry]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "Registry")
+
+ request = build_remove_regions_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._remove_regions_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = None
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers)
+
+ return deserialized
+
+ _remove_regions_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/removeRegions"
+ }
+
+ @overload
+ async def begin_remove_regions(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: _models.Registry,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.Registry]:
+ """Remove regions from registry.
+
+ Remove regions from registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.Registry
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either Registry or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_remove_regions(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.Registry]:
+ """Remove regions from registry.
+
+ Remove regions from registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either Registry or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_remove_regions(
+ self, resource_group_name: str, registry_name: str, body: Union[_models.Registry, IO], **kwargs: Any
+ ) -> AsyncLROPoller[_models.Registry]:
+ """Remove regions from registry.
+
+ Remove regions from registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Is either a Registry type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.Registry or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either Registry or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._remove_regions_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("Registry", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_remove_regions.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/removeRegions"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_code_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_code_containers_operations.py
new file mode 100644
index 000000000000..311d8212a389
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_code_containers_operations.py
@@ -0,0 +1,623 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_code_containers_operations import (
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryCodeContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_code_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self, resource_group_name: str, registry_name: str, skip: Optional[str] = None, **kwargs: Any
+ ) -> AsyncIterable["_models.CodeContainer"]:
+ """List containers.
+
+ List containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either CodeContainer or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.CodeContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.CodeContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("CodeContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, code_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, code_name: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete Code container.
+
+ Delete Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, code_name: str, **kwargs: Any
+ ) -> _models.CodeContainer:
+ """Get Code container.
+
+ Get Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: CodeContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.CodeContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("CodeContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ body: Union[_models.CodeContainer, IO],
+ **kwargs: Any
+ ) -> _models.CodeContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "CodeContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("CodeContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("CodeContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ body: _models.CodeContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.CodeContainer]:
+ """Create or update Code container.
+
+ Create or update Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.CodeContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either CodeContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.CodeContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.CodeContainer]:
+ """Create or update Code container.
+
+ Create or update Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either CodeContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.CodeContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ body: Union[_models.CodeContainer, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.CodeContainer]:
+ """Create or update Code container.
+
+ Create or update Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param body: Container entity to create or update. Is either a CodeContainer type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.CodeContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either CodeContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.CodeContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("CodeContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_code_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_code_versions_operations.py
new file mode 100644
index 000000000000..358d9b586cb4
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_code_versions_operations.py
@@ -0,0 +1,831 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_code_versions_operations import (
+ build_create_or_get_start_pending_upload_request,
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryCodeVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_code_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.CodeVersion"]:
+ """List versions.
+
+ List versions.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param order_by: Ordering of list. Default value is None.
+ :type order_by: str
+ :param top: Maximum number of records to return. Default value is None.
+ :type top: int
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either CodeVersion or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.CodeVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.CodeVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ subscription_id=self._config.subscription_id,
+ order_by=order_by,
+ top=top,
+ skip=skip,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("CodeVersionResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, code_name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, code_name: str, version: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, code_name: str, version: str, **kwargs: Any
+ ) -> _models.CodeVersion:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: CodeVersion or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.CodeVersion
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("CodeVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: Union[_models.CodeVersion, IO],
+ **kwargs: Any
+ ) -> _models.CodeVersion:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "CodeVersion")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("CodeVersion", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("CodeVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: _models.CodeVersion,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.CodeVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.CodeVersion
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either CodeVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.CodeVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.CodeVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either CodeVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.CodeVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: Union[_models.CodeVersion, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.CodeVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a CodeVersion type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.CodeVersion or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either CodeVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.CodeVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("CodeVersion", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ @overload
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: _models.PendingUploadRequestDto,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Pending upload name. This is case-sensitive. Required.
+ :type code_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Pending upload name. This is case-sensitive. Required.
+ :type code_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: Union[_models.PendingUploadRequestDto, IO],
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Pending upload name. This is case-sensitive. Required.
+ :type code_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Is either a PendingUploadRequestDto type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.PendingUploadResponseDto] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PendingUploadRequestDto")
+
+ request = build_create_or_get_start_pending_upload_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.create_or_get_start_pending_upload.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("PendingUploadResponseDto", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_start_pending_upload.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}/startPendingUpload"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_component_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_component_containers_operations.py
new file mode 100644
index 000000000000..b81621c705a4
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_component_containers_operations.py
@@ -0,0 +1,623 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_component_containers_operations import (
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryComponentContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_component_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self, resource_group_name: str, registry_name: str, skip: Optional[str] = None, **kwargs: Any
+ ) -> AsyncIterable["_models.ComponentContainer"]:
+ """List containers.
+
+ List containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either ComponentContainer or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.ComponentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ComponentContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("ComponentContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, component_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, component_name: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete container.
+
+ Delete container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, component_name: str, **kwargs: Any
+ ) -> _models.ComponentContainer:
+ """Get container.
+
+ Get container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: ComponentContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.ComponentContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("ComponentContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ body: Union[_models.ComponentContainer, IO],
+ **kwargs: Any
+ ) -> _models.ComponentContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "ComponentContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("ComponentContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("ComponentContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ body: _models.ComponentContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ComponentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ComponentContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ComponentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ComponentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ComponentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ComponentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ComponentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ body: Union[_models.ComponentContainer, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ComponentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param body: Container entity to create or update. Is either a ComponentContainer type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ComponentContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ComponentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ComponentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("ComponentContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_component_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_component_versions_operations.py
new file mode 100644
index 000000000000..b8e965d7432c
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_component_versions_operations.py
@@ -0,0 +1,658 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_component_versions_operations import (
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryComponentVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_component_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.ComponentVersion"]:
+ """List versions.
+
+ List versions.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param order_by: Ordering of list. Default value is None.
+ :type order_by: str
+ :param top: Maximum number of records to return. Default value is None.
+ :type top: int
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either ComponentVersion or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.ComponentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ComponentVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ subscription_id=self._config.subscription_id,
+ order_by=order_by,
+ top=top,
+ skip=skip,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("ComponentVersionResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, component_name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, component_name: str, version: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, component_name: str, version: str, **kwargs: Any
+ ) -> _models.ComponentVersion:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: ComponentVersion or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.ComponentVersion
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("ComponentVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ version: str,
+ body: Union[_models.ComponentVersion, IO],
+ **kwargs: Any
+ ) -> _models.ComponentVersion:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "ComponentVersion")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("ComponentVersion", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("ComponentVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ version: str,
+ body: _models.ComponentVersion,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ComponentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ComponentVersion
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ComponentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ComponentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ComponentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ComponentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ComponentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ version: str,
+ body: Union[_models.ComponentVersion, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ComponentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a ComponentVersion type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ComponentVersion or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ComponentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ComponentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("ComponentVersion", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_data_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_data_containers_operations.py
new file mode 100644
index 000000000000..c4461da6d425
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_data_containers_operations.py
@@ -0,0 +1,632 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_data_containers_operations import (
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryDataContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_data_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.DataContainer"]:
+ """List Data containers.
+
+ List Data containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either DataContainer or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.DataContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.DataContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("DataContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, name: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete container.
+
+ Delete container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, name: str, **kwargs: Any
+ ) -> _models.DataContainer:
+ """Get container.
+
+ Get container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: DataContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.DataContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("DataContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ body: Union[_models.DataContainer, IO],
+ **kwargs: Any
+ ) -> _models.DataContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "DataContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("DataContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("DataContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ body: _models.DataContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.DataContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.DataContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either DataContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.DataContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.DataContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either DataContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.DataContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ body: Union[_models.DataContainer, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.DataContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param body: Container entity to create or update. Is either a DataContainer type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.DataContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either DataContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.DataContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("DataContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_data_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_data_versions_operations.py
new file mode 100644
index 000000000000..2536b3c95de0
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_data_versions_operations.py
@@ -0,0 +1,845 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_data_versions_operations import (
+ build_create_or_get_start_pending_upload_request,
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryDataVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_data_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ tags: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.DataVersionBase"]:
+ """List data versions in the data container.
+
+ List data versions in the data container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Data container's name. Required.
+ :type name: str
+ :param order_by: Please choose OrderBy value from ['createdtime', 'modifiedtime']. Default
+ value is None.
+ :type order_by: str
+ :param top: Top count of results, top count cannot be greater than the page size.
+ If topCount > page size, results with be default page size count
+ will be returned. Default value is None.
+ :type top: int
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param tags: Comma-separated list of tag names (and optionally values). Example:
+ tag1,tag2=value2. Default value is None.
+ :type tags: str
+ :param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
+ ListViewType.All]View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either DataVersionBase or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.DataVersionBase]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.DataVersionBaseResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ subscription_id=self._config.subscription_id,
+ order_by=order_by,
+ top=top,
+ skip=skip,
+ tags=tags,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("DataVersionBaseResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, name: str, version: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, name: str, version: str, **kwargs: Any
+ ) -> _models.DataVersionBase:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: DataVersionBase or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.DataVersionBase
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("DataVersionBase", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: Union[_models.DataVersionBase, IO],
+ **kwargs: Any
+ ) -> _models.DataVersionBase:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "DataVersionBase")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("DataVersionBase", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("DataVersionBase", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: _models.DataVersionBase,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.DataVersionBase]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.DataVersionBase
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either DataVersionBase or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.DataVersionBase]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.DataVersionBase]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either DataVersionBase or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.DataVersionBase]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: Union[_models.DataVersionBase, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.DataVersionBase]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a DataVersionBase type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.DataVersionBase or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either DataVersionBase or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.DataVersionBase]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("DataVersionBase", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ @overload
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: _models.PendingUploadRequestDto,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a data asset to.
+
+ Generate a storage location and credential for the client to upload a data asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Data asset name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a data asset to.
+
+ Generate a storage location and credential for the client to upload a data asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Data asset name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: Union[_models.PendingUploadRequestDto, IO],
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a data asset to.
+
+ Generate a storage location and credential for the client to upload a data asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Data asset name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Is either a PendingUploadRequestDto type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.PendingUploadResponseDto] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PendingUploadRequestDto")
+
+ request = build_create_or_get_start_pending_upload_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.create_or_get_start_pending_upload.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("PendingUploadResponseDto", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_start_pending_upload.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}/startPendingUpload"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_environment_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_environment_containers_operations.py
new file mode 100644
index 000000000000..929c488adaee
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_environment_containers_operations.py
@@ -0,0 +1,633 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_environment_containers_operations import (
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryEnvironmentContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_environment_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.EnvironmentContainer"]:
+ """List environment containers.
+
+ List environment containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either EnvironmentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.EnvironmentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.EnvironmentContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("EnvironmentContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, environment_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, environment_name: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete container.
+
+ Delete container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, environment_name: str, **kwargs: Any
+ ) -> _models.EnvironmentContainer:
+ """Get container.
+
+ Get container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. This is case-sensitive. Required.
+ :type environment_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: EnvironmentContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.EnvironmentContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("EnvironmentContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ body: Union[_models.EnvironmentContainer, IO],
+ **kwargs: Any
+ ) -> _models.EnvironmentContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "EnvironmentContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("EnvironmentContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("EnvironmentContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ body: _models.EnvironmentContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.EnvironmentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.EnvironmentContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either EnvironmentContainer or the result
+ of cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.EnvironmentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either EnvironmentContainer or the result
+ of cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ body: Union[_models.EnvironmentContainer, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.EnvironmentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param body: Container entity to create or update. Is either a EnvironmentContainer type or a
+ IO type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.EnvironmentContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either EnvironmentContainer or the result
+ of cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("EnvironmentContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_environment_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_environment_versions_operations.py
new file mode 100644
index 000000000000..5bcdf001239e
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_environment_versions_operations.py
@@ -0,0 +1,663 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_environment_versions_operations import (
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryEnvironmentVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_environment_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.EnvironmentVersion"]:
+ """List versions.
+
+ List versions.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. This is case-sensitive. Required.
+ :type environment_name: str
+ :param order_by: Ordering of list. Default value is None.
+ :type order_by: str
+ :param top: Maximum number of records to return. Default value is None.
+ :type top: int
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either EnvironmentVersion or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.EnvironmentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.EnvironmentVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ subscription_id=self._config.subscription_id,
+ order_by=order_by,
+ top=top,
+ skip=skip,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("EnvironmentVersionResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, environment_name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, environment_name: str, version: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, environment_name: str, version: str, **kwargs: Any
+ ) -> _models.EnvironmentVersion:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. This is case-sensitive. Required.
+ :type environment_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: EnvironmentVersion or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.EnvironmentVersion
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("EnvironmentVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ body: Union[_models.EnvironmentVersion, IO],
+ **kwargs: Any
+ ) -> _models.EnvironmentVersion:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "EnvironmentVersion")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("EnvironmentVersion", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("EnvironmentVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ body: _models.EnvironmentVersion,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.EnvironmentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.EnvironmentVersion
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either EnvironmentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.EnvironmentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either EnvironmentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ body: Union[_models.EnvironmentVersion, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.EnvironmentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a EnvironmentVersion type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.EnvironmentVersion or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either EnvironmentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("EnvironmentVersion", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_model_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_model_containers_operations.py
new file mode 100644
index 000000000000..aed41328969f
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_model_containers_operations.py
@@ -0,0 +1,632 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_model_containers_operations import (
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryModelContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_model_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.ModelContainer"]:
+ """List model containers.
+
+ List model containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either ModelContainer or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.ModelContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ModelContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("ModelContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, model_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, model_name: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete container.
+
+ Delete container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, model_name: str, **kwargs: Any
+ ) -> _models.ModelContainer:
+ """Get container.
+
+ Get container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. This is case-sensitive. Required.
+ :type model_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: ModelContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.ModelContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("ModelContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ body: Union[_models.ModelContainer, IO],
+ **kwargs: Any
+ ) -> _models.ModelContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "ModelContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("ModelContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("ModelContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ body: _models.ModelContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ModelContainer]:
+ """Create or update model container.
+
+ Create or update model container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ModelContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ModelContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ModelContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ModelContainer]:
+ """Create or update model container.
+
+ Create or update model container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ModelContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ModelContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ body: Union[_models.ModelContainer, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ModelContainer]:
+ """Create or update model container.
+
+ Create or update model container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param body: Container entity to create or update. Is either a ModelContainer type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ModelContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ModelContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ModelContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("ModelContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_model_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_model_versions_operations.py
new file mode 100644
index 000000000000..d99e7163758d
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_registry_model_versions_operations.py
@@ -0,0 +1,854 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import AsyncHttpResponse
+from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
+
+from ... import models as _models
+from ..._vendor import _convert_request
+from ...operations._registry_model_versions_operations import (
+ build_create_or_get_start_pending_upload_request,
+ build_create_or_update_request,
+ build_delete_request,
+ build_get_request,
+ build_list_request,
+)
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class RegistryModelVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.aio.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_model_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ skip: Optional[str] = None,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ version: Optional[str] = None,
+ description: Optional[str] = None,
+ tags: Optional[str] = None,
+ properties: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.ModelVersion"]:
+ """List versions.
+
+ List versions.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. This is case-sensitive. Required.
+ :type model_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param order_by: Ordering of list. Default value is None.
+ :type order_by: str
+ :param top: Maximum number of records to return. Default value is None.
+ :type top: int
+ :param version: Version identifier. Default value is None.
+ :type version: str
+ :param description: Model description. Default value is None.
+ :type description: str
+ :param tags: Comma-separated list of tag names (and optionally values). Example:
+ tag1,tag2=value2. Default value is None.
+ :type tags: str
+ :param properties: Comma-separated list of property names (and optionally values). Example:
+ prop1,prop2=value2. Default value is None.
+ :type properties: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either ModelVersion or the result of cls(response)
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ModelVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ order_by=order_by,
+ top=top,
+ version=version,
+ description=description,
+ tags=tags,
+ properties=properties,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ async def extract_data(pipeline_response):
+ deserialized = self._deserialize("ModelVersionResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, AsyncList(list_of_elem)
+
+ async def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions"
+ }
+
+ async def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, model_name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def begin_delete(
+ self, resource_group_name: str, registry_name: str, model_name: str, version: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ @distributed_trace_async
+ async def get(
+ self, resource_group_name: str, registry_name: str, model_name: str, version: str, **kwargs: Any
+ ) -> _models.ModelVersion:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. This is case-sensitive. Required.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: ModelVersion or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.ModelVersion
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("ModelVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ async def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: Union[_models.ModelVersion, IO],
+ **kwargs: Any
+ ) -> _models.ModelVersion:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "ModelVersion")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("ModelVersion", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("ModelVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: _models.ModelVersion,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ModelVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ModelVersion
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ModelVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ModelVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ModelVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: Union[_models.ModelVersion, IO],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ModelVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a ModelVersion type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ModelVersion or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
+ this operation to not poll, or pass in your own initialized polling object for a personal
+ polling strategy.
+ :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of AsyncLROPoller that returns either ModelVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
+ polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = await self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("ModelVersion", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
+ elif polling is False:
+ polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return AsyncLROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ @overload
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: _models.PendingUploadRequestDto,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a model asset to.
+
+ Generate a storage location and credential for the client to upload a model asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Model name. This is case-sensitive. Required.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a model asset to.
+
+ Generate a storage location and credential for the client to upload a model asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Model name. This is case-sensitive. Required.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: Union[_models.PendingUploadRequestDto, IO],
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a model asset to.
+
+ Generate a storage location and credential for the client to upload a model asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Model name. This is case-sensitive. Required.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Is either a PendingUploadRequestDto type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.PendingUploadResponseDto] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PendingUploadRequestDto")
+
+ request = build_create_or_get_start_pending_upload_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.create_or_get_start_pending_upload.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("PendingUploadResponseDto", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_start_pending_upload.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}/startPendingUpload"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_schedules_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_schedules_operations.py
index 7e2d8fa6ae15..d0d5c6d20821 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_schedules_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_schedules_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -38,10 +37,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -97,9 +92,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ScheduleResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -155,8 +148,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -187,9 +181,7 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -205,8 +197,9 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -261,9 +254,7 @@ async def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -286,7 +277,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod, AsyncARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
@@ -333,9 +326,7 @@ async def get(self, resource_group_name: str, workspace_name: str, name: str, **
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.Schedule] = kwargs.pop("cls", None)
request = build_get_request(
@@ -351,8 +342,9 @@ async def get(self, resource_group_name: str, workspace_name: str, name: str, **
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -387,9 +379,7 @@ async def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Schedule] = kwargs.pop("cls", None)
@@ -417,8 +407,9 @@ async def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -548,7 +539,7 @@ async def begin_create_or_update(
:type workspace_name: str
:param name: Schedule name. Required.
:type name: str
- :param body: Schedule definition. Is either a model type or a IO type. Required.
+ :param body: Schedule definition. Is either a Schedule type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.Schedule or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -569,9 +560,7 @@ async def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Schedule] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -599,7 +588,10 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: AsyncPollingMethod = cast(AsyncPollingMethod, AsyncARMPolling(lro_delay, **kwargs))
+ polling_method: AsyncPollingMethod = cast(
+ AsyncPollingMethod,
+ AsyncARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs),
+ )
elif polling is False:
polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
else:
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_usages_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_usages_operations.py
index f7db5ff755cf..a8392c596462 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_usages_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_usages_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar
import urllib.parse
@@ -30,10 +29,6 @@
from ..._vendor import _convert_request
from ...operations._usages_operations import build_list_request
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -73,9 +68,7 @@ def list(self, location: str, **kwargs: Any) -> AsyncIterable["_models.Usage"]:
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListUsagesResult] = kwargs.pop("cls", None)
error_map = {
@@ -128,8 +121,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_virtual_machine_sizes_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_virtual_machine_sizes_operations.py
index e11949599426..dd19432ccc8c 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_virtual_machine_sizes_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_virtual_machine_sizes_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, Optional, TypeVar
from azure.core.exceptions import (
@@ -28,10 +27,6 @@
from ..._vendor import _convert_request
from ...operations._virtual_machine_sizes_operations import build_list_request
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -77,9 +72,7 @@ async def list(self, location: str, **kwargs: Any) -> _models.VirtualMachineSize
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.VirtualMachineSizeListResult] = kwargs.pop("cls", None)
request = build_list_request(
@@ -93,8 +86,9 @@ async def list(self, location: str, **kwargs: Any) -> _models.VirtualMachineSize
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspace_connections_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspace_connections_operations.py
index d849184954e4..35c65d84d4de 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspace_connections_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspace_connections_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, overload
import urllib.parse
@@ -36,10 +35,6 @@
build_list_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -145,7 +140,7 @@ async def create(
:param connection_name: Friendly name of the workspace connection. Required.
:type connection_name: str
:param parameters: The object for creating or updating a new workspace connection. Is either a
- model type or a IO type. Required.
+ WorkspaceConnectionPropertiesV2BasicResource type or a IO type. Required.
:type parameters:
~azure.mgmt.machinelearningservices.models.WorkspaceConnectionPropertiesV2BasicResource or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -167,9 +162,7 @@ async def create(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.WorkspaceConnectionPropertiesV2BasicResource] = kwargs.pop("cls", None)
@@ -197,8 +190,9 @@ async def create(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -248,9 +242,7 @@ async def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.WorkspaceConnectionPropertiesV2BasicResource] = kwargs.pop("cls", None)
request = build_get_request(
@@ -266,8 +258,9 @@ async def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -317,9 +310,7 @@ async def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -335,8 +326,9 @@ async def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -383,9 +375,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.WorkspaceConnectionPropertiesV2BasicResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -443,8 +433,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspace_features_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspace_features_operations.py
index a968302c5446..4de434394f7c 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspace_features_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspace_features_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar
import urllib.parse
@@ -30,10 +29,6 @@
from ..._vendor import _convert_request
from ...operations._workspace_features_operations import build_list_request
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -77,9 +72,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListAmlUserFeatureResult] = kwargs.pop("cls", None)
error_map = {
@@ -133,8 +126,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspaces_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspaces_operations.py
index 5c6cf54fea4d..e886189a8ad0 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspaces_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/aio/operations/_workspaces_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, AsyncIterable, Callable, Dict, IO, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -48,10 +47,6 @@
build_update_request,
)
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -100,9 +95,7 @@ async def get(self, resource_group_name: str, workspace_name: str, **kwargs: Any
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.Workspace] = kwargs.pop("cls", None)
request = build_get_request(
@@ -117,8 +110,9 @@ async def get(self, resource_group_name: str, workspace_name: str, **kwargs: Any
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -153,9 +147,7 @@ async def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.Workspace]] = kwargs.pop("cls", None)
@@ -182,8 +174,9 @@ async def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -294,7 +287,7 @@ async def begin_create_or_update(
:param workspace_name: Name of Azure Machine Learning workspace. Required.
:type workspace_name: str
:param parameters: The parameters for creating or updating a machine learning workspace. Is
- either a model type or a IO type. Required.
+ either a Workspace type or a IO type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.Workspace or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -316,9 +309,7 @@ async def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Workspace] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -377,9 +368,7 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -394,8 +383,9 @@ async def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -436,9 +426,7 @@ async def begin_delete(self, resource_group_name: str, workspace_name: str, **kw
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -496,9 +484,7 @@ async def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.Workspace]] = kwargs.pop("cls", None)
@@ -525,8 +511,9 @@ async def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -638,8 +625,8 @@ async def begin_update(
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace. Required.
:type workspace_name: str
- :param parameters: The parameters for updating a machine learning workspace. Is either a model
- type or a IO type. Required.
+ :param parameters: The parameters for updating a machine learning workspace. Is either a
+ WorkspaceUpdateParameters type or a IO type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.WorkspaceUpdateParameters or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -661,9 +648,7 @@ async def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Workspace] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -728,9 +713,7 @@ def list_by_resource_group(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.WorkspaceListResult] = kwargs.pop("cls", None)
error_map = {
@@ -784,8 +767,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -820,9 +804,7 @@ async def _diagnose_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.DiagnoseResponseResult]] = kwargs.pop("cls", None)
@@ -852,8 +834,9 @@ async def _diagnose_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -976,8 +959,8 @@ async def begin_diagnose(
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace. Required.
:type workspace_name: str
- :param parameters: The parameter of diagnosing workspace health. Is either a model type or a IO
- type. Default value is None.
+ :param parameters: The parameter of diagnosing workspace health. Is either a
+ DiagnoseWorkspaceParameters type or a IO type. Default value is None.
:type parameters: ~azure.mgmt.machinelearningservices.models.DiagnoseWorkspaceParameters or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -999,9 +982,7 @@ async def begin_diagnose(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.DiagnoseResponseResult] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
@@ -1076,9 +1057,7 @@ async def list_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListWorkspaceKeysResult] = kwargs.pop("cls", None)
request = build_list_keys_request(
@@ -1093,8 +1072,9 @@ async def list_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1129,9 +1109,7 @@ async def _resync_keys_initial( # pylint: disable=inconsistent-return-statement
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_resync_keys_request(
@@ -1146,8 +1124,9 @@ async def _resync_keys_initial( # pylint: disable=inconsistent-return-statement
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1191,9 +1170,7 @@ async def begin_resync_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1248,9 +1225,7 @@ def list_by_subscription(self, skip: Optional[str] = None, **kwargs: Any) -> Asy
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.WorkspaceListResult] = kwargs.pop("cls", None)
error_map = {
@@ -1303,8 +1278,9 @@ async def extract_data(pipeline_response):
async def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1348,9 +1324,7 @@ async def list_notebook_access_token(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.NotebookAccessTokenResult] = kwargs.pop("cls", None)
request = build_list_notebook_access_token_request(
@@ -1365,8 +1339,9 @@ async def list_notebook_access_token(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1401,9 +1376,7 @@ async def _prepare_notebook_initial(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[Optional[_models.NotebookResourceInfo]] = kwargs.pop("cls", None)
request = build_prepare_notebook_request(
@@ -1418,8 +1391,9 @@ async def _prepare_notebook_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1470,9 +1444,7 @@ async def begin_prepare_notebook(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.NotebookResourceInfo] = kwargs.pop("cls", None)
polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1543,9 +1515,7 @@ async def list_storage_account_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListStorageAccountKeysResult] = kwargs.pop("cls", None)
request = build_list_storage_account_keys_request(
@@ -1560,8 +1530,9 @@ async def list_storage_account_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1609,9 +1580,7 @@ async def list_notebook_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListNotebookKeysResult] = kwargs.pop("cls", None)
request = build_list_notebook_keys_request(
@@ -1626,8 +1595,9 @@ async def list_notebook_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1649,7 +1619,7 @@ async def list_notebook_keys(
}
@distributed_trace_async
- async def list_outbound_network_dependencies_endpoints(
+ async def list_outbound_network_dependencies_endpoints( # pylint: disable=name-too-long
self, resource_group_name: str, workspace_name: str, **kwargs: Any
) -> _models.ExternalFQDNResponse:
"""Called by Client (Portal, CLI, etc) to get a list of all external outbound dependencies (FQDNs)
@@ -1679,9 +1649,7 @@ async def list_outbound_network_dependencies_endpoints(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ExternalFQDNResponse] = kwargs.pop("cls", None)
request = build_list_outbound_network_dependencies_endpoints_request(
@@ -1696,8 +1664,9 @@ async def list_outbound_network_dependencies_endpoints(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/__init__.py
index 72bfcc9bc3c2..339c533836e3 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/__init__.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/__init__.py
@@ -11,9 +11,11 @@
from ._models_py3 import AKSSchemaProperties
from ._models_py3 import AccountKeyDatastoreCredentials
from ._models_py3 import AccountKeyDatastoreSecrets
+from ._models_py3 import AcrDetails
from ._models_py3 import AksComputeSecrets
from ._models_py3 import AksComputeSecretsProperties
from ._models_py3 import AksNetworkingConfiguration
+from ._models_py3 import AllNodes
from ._models_py3 import AmlCompute
from ._models_py3 import AmlComputeNodeInformation
from ._models_py3 import AmlComputeNodesInformation
@@ -24,6 +26,7 @@
from ._models_py3 import AmlOperationListResult
from ._models_py3 import AmlToken
from ._models_py3 import AmlUserFeature
+from ._models_py3 import ArmResourceId
from ._models_py3 import AssetBase
from ._models_py3 import AssetContainer
from ._models_py3 import AssetJobInput
@@ -53,6 +56,8 @@
from ._models_py3 import BatchEndpointTrackedResourceArmPaginatedResult
from ._models_py3 import BatchRetrySettings
from ._models_py3 import BayesianSamplingAlgorithm
+from ._models_py3 import BindOptions
+from ._models_py3 import BlobReferenceForConsumptionDto
from ._models_py3 import BuildContext
from ._models_py3 import CertificateDatastoreCredentials
from ._models_py3 import CertificateDatastoreSecrets
@@ -97,12 +102,14 @@
from ._models_py3 import ContainerResourceRequirements
from ._models_py3 import ContainerResourceSettings
from ._models_py3 import CosmosDbSettings
+from ._models_py3 import Cron
from ._models_py3 import CronTrigger
from ._models_py3 import CustomForecastHorizon
from ._models_py3 import CustomModelJobInput
from ._models_py3 import CustomModelJobOutput
from ._models_py3 import CustomNCrossValidations
from ._models_py3 import CustomSeasonality
+from ._models_py3 import CustomService
from ._models_py3 import CustomTargetLags
from ._models_py3 import CustomTargetRollingWindowSize
from ._models_py3 import DataContainer
@@ -136,9 +143,11 @@
from ._models_py3 import DiagnoseResult
from ._models_py3 import DiagnoseWorkspaceParameters
from ._models_py3 import DistributionConfiguration
+from ._models_py3 import Docker
from ._models_py3 import EarlyTerminationPolicy
from ._models_py3 import EncryptionKeyVaultProperties
from ._models_py3 import EncryptionProperty
+from ._models_py3 import Endpoint
from ._models_py3 import EndpointAuthKeys
from ._models_py3 import EndpointAuthToken
from ._models_py3 import EndpointDeploymentPropertiesBase
@@ -147,6 +156,7 @@
from ._models_py3 import EnvironmentContainer
from ._models_py3 import EnvironmentContainerProperties
from ._models_py3 import EnvironmentContainerResourceArmPaginatedResult
+from ._models_py3 import EnvironmentVariable
from ._models_py3 import EnvironmentVersion
from ._models_py3 import EnvironmentVersionProperties
from ._models_py3 import EnvironmentVersionResourceArmPaginatedResult
@@ -173,11 +183,14 @@
from ._models_py3 import IdAssetReference
from ._models_py3 import IdentityConfiguration
from ._models_py3 import IdentityForCmk
+from ._models_py3 import IdleShutdownSetting
+from ._models_py3 import Image
from ._models_py3 import ImageClassification
from ._models_py3 import ImageClassificationBase
from ._models_py3 import ImageClassificationMultilabel
from ._models_py3 import ImageInstanceSegmentation
from ._models_py3 import ImageLimitSettings
+from ._models_py3 import ImageMetadata
from ._models_py3 import ImageModelDistributionSettings
from ._models_py3 import ImageModelDistributionSettingsClassification
from ._models_py3 import ImageModelDistributionSettingsObjectDetection
@@ -233,6 +246,7 @@
from ._models_py3 import NlpVerticalFeaturizationSettings
from ._models_py3 import NlpVerticalLimitSettings
from ._models_py3 import NodeStateCounts
+from ._models_py3 import Nodes
from ._models_py3 import NoneAuthTypeWorkspaceConnectionProperties
from ._models_py3 import NoneDatastoreCredentials
from ._models_py3 import NotebookAccessTokenResult
@@ -256,13 +270,18 @@
from ._models_py3 import PartialMinimalTrackedResource
from ._models_py3 import PartialMinimalTrackedResourceWithIdentity
from ._models_py3 import PartialMinimalTrackedResourceWithSku
+from ._models_py3 import PartialRegistryPartialTrackedResource
from ._models_py3 import PartialSku
from ._models_py3 import Password
+from ._models_py3 import PendingUploadCredentialDto
+from ._models_py3 import PendingUploadRequestDto
+from ._models_py3 import PendingUploadResponseDto
from ._models_py3 import PersonalComputeInstanceSettings
from ._models_py3 import PipelineJob
from ._models_py3 import PrivateEndpoint
from ._models_py3 import PrivateEndpointConnection
from ._models_py3 import PrivateEndpointConnectionListResult
+from ._models_py3 import PrivateEndpointResource
from ._models_py3 import PrivateLinkResource
from ._models_py3 import PrivateLinkResourceListResult
from ._models_py3 import PrivateLinkServiceConnectionState
@@ -271,10 +290,17 @@
from ._models_py3 import QuotaBaseProperties
from ._models_py3 import QuotaUpdateParameters
from ._models_py3 import RandomSamplingAlgorithm
+from ._models_py3 import Recurrence
from ._models_py3 import RecurrenceSchedule
from ._models_py3 import RecurrenceTrigger
from ._models_py3 import RegenerateEndpointKeysRequest
+from ._models_py3 import Registry
from ._models_py3 import RegistryListCredentialsResult
+from ._models_py3 import RegistryPartialManagedServiceIdentity
+from ._models_py3 import RegistryPrivateEndpointConnection
+from ._models_py3 import RegistryPrivateLinkServiceConnectionState
+from ._models_py3 import RegistryRegionArmDetails
+from ._models_py3 import RegistryTrackedResourceArmPaginatedResult
from ._models_py3 import Regression
from ._models_py3 import RegressionTrainingSettings
from ._models_py3 import Resource
@@ -285,6 +311,7 @@
from ._models_py3 import ResourceQuota
from ._models_py3 import Route
from ._models_py3 import SASAuthTypeWorkspaceConnectionProperties
+from ._models_py3 import SASCredentialDto
from ._models_py3 import SamplingAlgorithm
from ._models_py3 import SasDatastoreCredentials
from ._models_py3 import SasDatastoreSecrets
@@ -310,10 +337,13 @@
from ._models_py3 import SkuSetting
from ._models_py3 import SslConfiguration
from ._models_py3 import StackEnsembleSettings
+from ._models_py3 import StorageAccountDetails
from ._models_py3 import SweepJob
from ._models_py3 import SweepJobLimits
from ._models_py3 import SynapseSpark
from ._models_py3 import SynapseSparkProperties
+from ._models_py3 import SystemCreatedAcrAccount
+from ._models_py3 import SystemCreatedStorageAccount
from ._models_py3 import SystemData
from ._models_py3 import SystemService
from ._models_py3 import TableVertical
@@ -326,6 +356,7 @@
from ._models_py3 import TextClassification
from ._models_py3 import TextClassificationMultilabel
from ._models_py3 import TextNer
+from ._models_py3 import TmpfsOptions
from ._models_py3 import TrackedResource
from ._models_py3 import TrainingSettings
from ._models_py3 import TrialComponent
@@ -345,6 +376,8 @@
from ._models_py3 import UsageName
from ._models_py3 import UserAccountCredentials
from ._models_py3 import UserAssignedIdentity
+from ._models_py3 import UserCreatedAcrAccount
+from ._models_py3 import UserCreatedStorageAccount
from ._models_py3 import UserIdentity
from ._models_py3 import UsernamePasswordAuthTypeWorkspaceConnectionProperties
from ._models_py3 import VirtualMachine
@@ -356,6 +389,8 @@
from ._models_py3 import VirtualMachineSize
from ._models_py3 import VirtualMachineSizeListResult
from ._models_py3 import VirtualMachineSshCredentials
+from ._models_py3 import VolumeDefinition
+from ._models_py3 import VolumeOptions
from ._models_py3 import Workspace
from ._models_py3 import WorkspaceConnectionManagedIdentity
from ._models_py3 import WorkspaceConnectionPersonalAccessToken
@@ -369,6 +404,7 @@
from ._machine_learning_services_mgmt_client_enums import AllocationState
from ._machine_learning_services_mgmt_client_enums import ApplicationSharingPolicy
+from ._machine_learning_services_mgmt_client_enums import AssetProvisioningState
from ._machine_learning_services_mgmt_client_enums import AutoRebuildSetting
from ._machine_learning_services_mgmt_client_enums import Autosave
from ._machine_learning_services_mgmt_client_enums import BatchLoggingLevel
@@ -400,7 +436,9 @@
from ._machine_learning_services_mgmt_client_enums import EndpointAuthMode
from ._machine_learning_services_mgmt_client_enums import EndpointComputeType
from ._machine_learning_services_mgmt_client_enums import EndpointProvisioningState
+from ._machine_learning_services_mgmt_client_enums import EndpointServiceConnectionStatus
from ._machine_learning_services_mgmt_client_enums import EnvironmentType
+from ._machine_learning_services_mgmt_client_enums import EnvironmentVariableType
from ._machine_learning_services_mgmt_client_enums import FeatureLags
from ._machine_learning_services_mgmt_client_enums import FeaturizationMode
from ._machine_learning_services_mgmt_client_enums import ForecastHorizonMode
@@ -408,6 +446,7 @@
from ._machine_learning_services_mgmt_client_enums import ForecastingPrimaryMetrics
from ._machine_learning_services_mgmt_client_enums import Goal
from ._machine_learning_services_mgmt_client_enums import IdentityConfigurationType
+from ._machine_learning_services_mgmt_client_enums import ImageType
from ._machine_learning_services_mgmt_client_enums import InputDeliveryMode
from ._machine_learning_services_mgmt_client_enums import InstanceSegmentationPrimaryMetrics
from ._machine_learning_services_mgmt_client_enums import JobInputType
@@ -427,6 +466,7 @@
from ._machine_learning_services_mgmt_client_enums import NCrossValidationsMode
from ._machine_learning_services_mgmt_client_enums import Network
from ._machine_learning_services_mgmt_client_enums import NodeState
+from ._machine_learning_services_mgmt_client_enums import NodesValueType
from ._machine_learning_services_mgmt_client_enums import ObjectDetectionPrimaryMetrics
from ._machine_learning_services_mgmt_client_enums import OperatingSystemType
from ._machine_learning_services_mgmt_client_enums import OperationName
@@ -435,8 +475,11 @@
from ._machine_learning_services_mgmt_client_enums import OrderString
from ._machine_learning_services_mgmt_client_enums import OsType
from ._machine_learning_services_mgmt_client_enums import OutputDeliveryMode
+from ._machine_learning_services_mgmt_client_enums import PendingUploadCredentialType
+from ._machine_learning_services_mgmt_client_enums import PendingUploadType
from ._machine_learning_services_mgmt_client_enums import PrivateEndpointConnectionProvisioningState
from ._machine_learning_services_mgmt_client_enums import PrivateEndpointServiceConnectionStatus
+from ._machine_learning_services_mgmt_client_enums import Protocol
from ._machine_learning_services_mgmt_client_enums import ProvisioningState
from ._machine_learning_services_mgmt_client_enums import ProvisioningStatus
from ._machine_learning_services_mgmt_client_enums import PublicNetworkAccess
@@ -482,6 +525,7 @@
from ._machine_learning_services_mgmt_client_enums import ValidationMetricType
from ._machine_learning_services_mgmt_client_enums import ValueFormat
from ._machine_learning_services_mgmt_client_enums import VmPriority
+from ._machine_learning_services_mgmt_client_enums import VolumeDefinitionType
from ._machine_learning_services_mgmt_client_enums import WeekDay
from ._patch import __all__ as _patch_all
from ._patch import * # pylint: disable=unused-wildcard-import
@@ -493,9 +537,11 @@
"AKSSchemaProperties",
"AccountKeyDatastoreCredentials",
"AccountKeyDatastoreSecrets",
+ "AcrDetails",
"AksComputeSecrets",
"AksComputeSecretsProperties",
"AksNetworkingConfiguration",
+ "AllNodes",
"AmlCompute",
"AmlComputeNodeInformation",
"AmlComputeNodesInformation",
@@ -506,6 +552,7 @@
"AmlOperationListResult",
"AmlToken",
"AmlUserFeature",
+ "ArmResourceId",
"AssetBase",
"AssetContainer",
"AssetJobInput",
@@ -535,6 +582,8 @@
"BatchEndpointTrackedResourceArmPaginatedResult",
"BatchRetrySettings",
"BayesianSamplingAlgorithm",
+ "BindOptions",
+ "BlobReferenceForConsumptionDto",
"BuildContext",
"CertificateDatastoreCredentials",
"CertificateDatastoreSecrets",
@@ -579,12 +628,14 @@
"ContainerResourceRequirements",
"ContainerResourceSettings",
"CosmosDbSettings",
+ "Cron",
"CronTrigger",
"CustomForecastHorizon",
"CustomModelJobInput",
"CustomModelJobOutput",
"CustomNCrossValidations",
"CustomSeasonality",
+ "CustomService",
"CustomTargetLags",
"CustomTargetRollingWindowSize",
"DataContainer",
@@ -618,9 +669,11 @@
"DiagnoseResult",
"DiagnoseWorkspaceParameters",
"DistributionConfiguration",
+ "Docker",
"EarlyTerminationPolicy",
"EncryptionKeyVaultProperties",
"EncryptionProperty",
+ "Endpoint",
"EndpointAuthKeys",
"EndpointAuthToken",
"EndpointDeploymentPropertiesBase",
@@ -629,6 +682,7 @@
"EnvironmentContainer",
"EnvironmentContainerProperties",
"EnvironmentContainerResourceArmPaginatedResult",
+ "EnvironmentVariable",
"EnvironmentVersion",
"EnvironmentVersionProperties",
"EnvironmentVersionResourceArmPaginatedResult",
@@ -655,11 +709,14 @@
"IdAssetReference",
"IdentityConfiguration",
"IdentityForCmk",
+ "IdleShutdownSetting",
+ "Image",
"ImageClassification",
"ImageClassificationBase",
"ImageClassificationMultilabel",
"ImageInstanceSegmentation",
"ImageLimitSettings",
+ "ImageMetadata",
"ImageModelDistributionSettings",
"ImageModelDistributionSettingsClassification",
"ImageModelDistributionSettingsObjectDetection",
@@ -715,6 +772,7 @@
"NlpVerticalFeaturizationSettings",
"NlpVerticalLimitSettings",
"NodeStateCounts",
+ "Nodes",
"NoneAuthTypeWorkspaceConnectionProperties",
"NoneDatastoreCredentials",
"NotebookAccessTokenResult",
@@ -738,13 +796,18 @@
"PartialMinimalTrackedResource",
"PartialMinimalTrackedResourceWithIdentity",
"PartialMinimalTrackedResourceWithSku",
+ "PartialRegistryPartialTrackedResource",
"PartialSku",
"Password",
+ "PendingUploadCredentialDto",
+ "PendingUploadRequestDto",
+ "PendingUploadResponseDto",
"PersonalComputeInstanceSettings",
"PipelineJob",
"PrivateEndpoint",
"PrivateEndpointConnection",
"PrivateEndpointConnectionListResult",
+ "PrivateEndpointResource",
"PrivateLinkResource",
"PrivateLinkResourceListResult",
"PrivateLinkServiceConnectionState",
@@ -753,10 +816,17 @@
"QuotaBaseProperties",
"QuotaUpdateParameters",
"RandomSamplingAlgorithm",
+ "Recurrence",
"RecurrenceSchedule",
"RecurrenceTrigger",
"RegenerateEndpointKeysRequest",
+ "Registry",
"RegistryListCredentialsResult",
+ "RegistryPartialManagedServiceIdentity",
+ "RegistryPrivateEndpointConnection",
+ "RegistryPrivateLinkServiceConnectionState",
+ "RegistryRegionArmDetails",
+ "RegistryTrackedResourceArmPaginatedResult",
"Regression",
"RegressionTrainingSettings",
"Resource",
@@ -767,6 +837,7 @@
"ResourceQuota",
"Route",
"SASAuthTypeWorkspaceConnectionProperties",
+ "SASCredentialDto",
"SamplingAlgorithm",
"SasDatastoreCredentials",
"SasDatastoreSecrets",
@@ -792,10 +863,13 @@
"SkuSetting",
"SslConfiguration",
"StackEnsembleSettings",
+ "StorageAccountDetails",
"SweepJob",
"SweepJobLimits",
"SynapseSpark",
"SynapseSparkProperties",
+ "SystemCreatedAcrAccount",
+ "SystemCreatedStorageAccount",
"SystemData",
"SystemService",
"TableVertical",
@@ -808,6 +882,7 @@
"TextClassification",
"TextClassificationMultilabel",
"TextNer",
+ "TmpfsOptions",
"TrackedResource",
"TrainingSettings",
"TrialComponent",
@@ -827,6 +902,8 @@
"UsageName",
"UserAccountCredentials",
"UserAssignedIdentity",
+ "UserCreatedAcrAccount",
+ "UserCreatedStorageAccount",
"UserIdentity",
"UsernamePasswordAuthTypeWorkspaceConnectionProperties",
"VirtualMachine",
@@ -838,6 +915,8 @@
"VirtualMachineSize",
"VirtualMachineSizeListResult",
"VirtualMachineSshCredentials",
+ "VolumeDefinition",
+ "VolumeOptions",
"Workspace",
"WorkspaceConnectionManagedIdentity",
"WorkspaceConnectionPersonalAccessToken",
@@ -850,6 +929,7 @@
"WorkspaceUpdateParameters",
"AllocationState",
"ApplicationSharingPolicy",
+ "AssetProvisioningState",
"AutoRebuildSetting",
"Autosave",
"BatchLoggingLevel",
@@ -881,7 +961,9 @@
"EndpointAuthMode",
"EndpointComputeType",
"EndpointProvisioningState",
+ "EndpointServiceConnectionStatus",
"EnvironmentType",
+ "EnvironmentVariableType",
"FeatureLags",
"FeaturizationMode",
"ForecastHorizonMode",
@@ -889,6 +971,7 @@
"ForecastingPrimaryMetrics",
"Goal",
"IdentityConfigurationType",
+ "ImageType",
"InputDeliveryMode",
"InstanceSegmentationPrimaryMetrics",
"JobInputType",
@@ -908,6 +991,7 @@
"NCrossValidationsMode",
"Network",
"NodeState",
+ "NodesValueType",
"ObjectDetectionPrimaryMetrics",
"OperatingSystemType",
"OperationName",
@@ -916,8 +1000,11 @@
"OrderString",
"OsType",
"OutputDeliveryMode",
+ "PendingUploadCredentialType",
+ "PendingUploadType",
"PrivateEndpointConnectionProvisioningState",
"PrivateEndpointServiceConnectionStatus",
+ "Protocol",
"ProvisioningState",
"ProvisioningStatus",
"PublicNetworkAccess",
@@ -963,6 +1050,7 @@
"ValidationMetricType",
"ValueFormat",
"VmPriority",
+ "VolumeDefinitionType",
"WeekDay",
]
__all__.extend([p for p in _patch_all if p not in __all__])
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/_machine_learning_services_mgmt_client_enums.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/_machine_learning_services_mgmt_client_enums.py
index 640b9b12a650..a32b5b391440 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/_machine_learning_services_mgmt_client_enums.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/_machine_learning_services_mgmt_client_enums.py
@@ -32,6 +32,17 @@ class ApplicationSharingPolicy(str, Enum, metaclass=CaseInsensitiveEnumMeta):
SHARED = "Shared"
+class AssetProvisioningState(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Provisioning state of registry asset."""
+
+ SUCCEEDED = "Succeeded"
+ FAILED = "Failed"
+ CANCELED = "Canceled"
+ CREATING = "Creating"
+ UPDATING = "Updating"
+ DELETING = "Deleting"
+
+
class AutoRebuildSetting(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""AutoRebuild setting for the derived image."""
@@ -74,30 +85,30 @@ class BillingCurrency(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class BlockedTransformers(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum for all classification models supported by AutoML."""
- #: Target encoding for text data.
TEXT_TARGET_ENCODER = "TextTargetEncoder"
- #: Ohe hot encoding creates a binary feature transformation.
+ """Target encoding for text data."""
ONE_HOT_ENCODER = "OneHotEncoder"
- #: Target encoding for categorical data.
+ """Ohe hot encoding creates a binary feature transformation."""
CAT_TARGET_ENCODER = "CatTargetEncoder"
- #: Tf-Idf stands for, term-frequency times inverse document-frequency. This is a common term
- #: weighting scheme for identifying information from documents.
+ """Target encoding for categorical data."""
TF_IDF = "TfIdf"
- #: Weight of Evidence encoding is a technique used to encode categorical variables. It uses the
- #: natural log of the P(1)/P(0) to create weights.
+ """Tf-Idf stands for, term-frequency times inverse document-frequency. This is a common term
+ #: weighting scheme for identifying information from documents."""
WO_E_TARGET_ENCODER = "WoETargetEncoder"
- #: Label encoder converts labels/categorical variables in a numerical form.
+ """Weight of Evidence encoding is a technique used to encode categorical variables. It uses the
+ #: natural log of the P(1)/P(0) to create weights."""
LABEL_ENCODER = "LabelEncoder"
- #: Word embedding helps represents words or phrases as a vector, or a series of numbers.
+ """Label encoder converts labels/categorical variables in a numerical form."""
WORD_EMBEDDING = "WordEmbedding"
- #: Naive Bayes is a classified that is used for classification of discrete features that are
- #: categorically distributed.
+ """Word embedding helps represents words or phrases as a vector, or a series of numbers."""
NAIVE_BAYES = "NaiveBayes"
- #: Count Vectorizer converts a collection of text documents to a matrix of token counts.
+ """Naive Bayes is a classified that is used for classification of discrete features that are
+ #: categorically distributed."""
COUNT_VECTORIZER = "CountVectorizer"
- #: Hashing One Hot Encoder can turn categorical variables into a limited number of new features.
- #: This is often used for high-cardinality categorical features.
+ """Count Vectorizer converts a collection of text documents to a matrix of token counts."""
HASH_ONE_HOT_ENCODER = "HashOneHotEncoder"
+ """Hashing One Hot Encoder can turn categorical variables into a limited number of new features.
+ #: This is often used for high-cardinality categorical features."""
class Caching(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -111,107 +122,107 @@ class Caching(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class ClassificationModels(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum for all classification models supported by AutoML."""
- #: Logistic regression is a fundamental classification technique.
+ LOGISTIC_REGRESSION = "LogisticRegression"
+ """Logistic regression is a fundamental classification technique.
#: It belongs to the group of linear classifiers and is somewhat similar to polynomial and linear
#: regression.
#: Logistic regression is fast and relatively uncomplicated, and it's convenient for you to
#: interpret the results.
#: Although it's essentially a method for binary classification, it can also be applied to
- #: multiclass problems.
- LOGISTIC_REGRESSION = "LogisticRegression"
- #: SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning
+ #: multiclass problems."""
+ SGD = "SGD"
+ """SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning
#: applications
#: to find the model parameters that correspond to the best fit between predicted and actual
- #: outputs.
- SGD = "SGD"
- #: The multinomial Naive Bayes classifier is suitable for classification with discrete features
+ #: outputs."""
+ MULTINOMIAL_NAIVE_BAYES = "MultinomialNaiveBayes"
+ """The multinomial Naive Bayes classifier is suitable for classification with discrete features
#: (e.g., word counts for text classification).
#: The multinomial distribution normally requires integer feature counts. However, in practice,
- #: fractional counts such as tf-idf may also work.
- MULTINOMIAL_NAIVE_BAYES = "MultinomialNaiveBayes"
- #: Naive Bayes classifier for multivariate Bernoulli models.
+ #: fractional counts such as tf-idf may also work."""
BERNOULLI_NAIVE_BAYES = "BernoulliNaiveBayes"
- #: A support vector machine (SVM) is a supervised machine learning model that uses classification
+ """Naive Bayes classifier for multivariate Bernoulli models."""
+ SVM = "SVM"
+ """A support vector machine (SVM) is a supervised machine learning model that uses classification
#: algorithms for two-group classification problems.
#: After giving an SVM model sets of labeled training data for each category, they're able to
- #: categorize new text.
- SVM = "SVM"
- #: A support vector machine (SVM) is a supervised machine learning model that uses classification
+ #: categorize new text."""
+ LINEAR_SVM = "LinearSVM"
+ """A support vector machine (SVM) is a supervised machine learning model that uses classification
#: algorithms for two-group classification problems.
#: After giving an SVM model sets of labeled training data for each category, they're able to
#: categorize new text.
#: Linear SVM performs best when input data is linear, i.e., data can be easily classified by
- #: drawing the straight line between classified values on a plotted graph.
- LINEAR_SVM = "LinearSVM"
- #: K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new
+ #: drawing the straight line between classified values on a plotted graph."""
+ KNN = "KNN"
+ """K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new
#: datapoints
#: which further means that the new data point will be assigned a value based on how closely it
- #: matches the points in the training set.
- KNN = "KNN"
- #: Decision Trees are a non-parametric supervised learning method used for both classification and
+ #: matches the points in the training set."""
+ DECISION_TREE = "DecisionTree"
+ """Decision Trees are a non-parametric supervised learning method used for both classification and
#: regression tasks.
#: The goal is to create a model that predicts the value of a target variable by learning simple
- #: decision rules inferred from the data features.
- DECISION_TREE = "DecisionTree"
- #: Random forest is a supervised learning algorithm.
+ #: decision rules inferred from the data features."""
+ RANDOM_FOREST = "RandomForest"
+ """Random forest is a supervised learning algorithm.
#: The "forest"\ it builds, is an ensemble of decision trees, usually trained with the “bagging”\
#: method.
#: The general idea of the bagging method is that a combination of learning models increases the
- #: overall result.
- RANDOM_FOREST = "RandomForest"
- #: Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many
- #: decision trees. It is related to the widely used random forest algorithm.
+ #: overall result."""
EXTREME_RANDOM_TREES = "ExtremeRandomTrees"
- #: LightGBM is a gradient boosting framework that uses tree based learning algorithms.
+ """Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many
+ #: decision trees. It is related to the widely used random forest algorithm."""
LIGHT_GBM = "LightGBM"
- #: The technique of transiting week learners into a strong learner is called Boosting. The
- #: gradient boosting algorithm process works on this theory of execution.
+ """LightGBM is a gradient boosting framework that uses tree based learning algorithms."""
GRADIENT_BOOSTING = "GradientBoosting"
- #: XGBoost: Extreme Gradient Boosting Algorithm. This algorithm is used for structured data where
- #: target column values can be divided into distinct class values.
+ """The technique of transiting week learners into a strong learner is called Boosting. The
+ #: gradient boosting algorithm process works on this theory of execution."""
XG_BOOST_CLASSIFIER = "XGBoostClassifier"
+ """XGBoost: Extreme Gradient Boosting Algorithm. This algorithm is used for structured data where
+ #: target column values can be divided into distinct class values."""
class ClassificationMultilabelPrimaryMetrics(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Primary metrics for classification multilabel tasks."""
- #: AUC is the Area under the curve.
- #: This metric represents arithmetic mean of the score for each class,
- #: weighted by the number of true instances in each class.
AUC_WEIGHTED = "AUCWeighted"
- #: Accuracy is the ratio of predictions that exactly match the true class labels.
+ """AUC is the Area under the curve.
+ #: This metric represents arithmetic mean of the score for each class,
+ #: weighted by the number of true instances in each class."""
ACCURACY = "Accuracy"
- #: Normalized macro recall is recall macro-averaged and normalized, so that random
- #: performance has a score of 0, and perfect performance has a score of 1.
+ """Accuracy is the ratio of predictions that exactly match the true class labels."""
NORM_MACRO_RECALL = "NormMacroRecall"
- #: The arithmetic mean of the average precision score for each class, weighted by
- #: the number of true instances in each class.
+ """Normalized macro recall is recall macro-averaged and normalized, so that random
+ #: performance has a score of 0, and perfect performance has a score of 1."""
AVERAGE_PRECISION_SCORE_WEIGHTED = "AveragePrecisionScoreWeighted"
- #: The arithmetic mean of precision for each class, weighted by number of true instances in each
- #: class.
+ """The arithmetic mean of the average precision score for each class, weighted by
+ #: the number of true instances in each class."""
PRECISION_SCORE_WEIGHTED = "PrecisionScoreWeighted"
- #: Intersection Over Union. Intersection of predictions divided by union of predictions.
+ """The arithmetic mean of precision for each class, weighted by number of true instances in each
+ #: class."""
IOU = "IOU"
+ """Intersection Over Union. Intersection of predictions divided by union of predictions."""
class ClassificationPrimaryMetrics(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Primary metrics for classification tasks."""
- #: AUC is the Area under the curve.
- #: This metric represents arithmetic mean of the score for each class,
- #: weighted by the number of true instances in each class.
AUC_WEIGHTED = "AUCWeighted"
- #: Accuracy is the ratio of predictions that exactly match the true class labels.
+ """AUC is the Area under the curve.
+ #: This metric represents arithmetic mean of the score for each class,
+ #: weighted by the number of true instances in each class."""
ACCURACY = "Accuracy"
- #: Normalized macro recall is recall macro-averaged and normalized, so that random
- #: performance has a score of 0, and perfect performance has a score of 1.
+ """Accuracy is the ratio of predictions that exactly match the true class labels."""
NORM_MACRO_RECALL = "NormMacroRecall"
- #: The arithmetic mean of the average precision score for each class, weighted by
- #: the number of true instances in each class.
+ """Normalized macro recall is recall macro-averaged and normalized, so that random
+ #: performance has a score of 0, and perfect performance has a score of 1."""
AVERAGE_PRECISION_SCORE_WEIGHTED = "AveragePrecisionScoreWeighted"
- #: The arithmetic mean of precision for each class, weighted by number of true instances in each
- #: class.
+ """The arithmetic mean of the average precision score for each class, weighted by
+ #: the number of true instances in each class."""
PRECISION_SCORE_WEIGHTED = "PrecisionScoreWeighted"
+ """The arithmetic mean of precision for each class, weighted by number of true instances in each
+ #: class."""
class ClusterPurpose(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -410,6 +421,15 @@ class EndpointProvisioningState(str, Enum, metaclass=CaseInsensitiveEnumMeta):
CANCELED = "Canceled"
+class EndpointServiceConnectionStatus(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Connection status of the service consumer with the service provider."""
+
+ APPROVED = "Approved"
+ PENDING = "Pending"
+ REJECTED = "Rejected"
+ DISCONNECTED = "Disconnected"
+
+
class EnvironmentType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Environment type is either user created or curated by Azure ML service."""
@@ -417,128 +437,134 @@ class EnvironmentType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
USER_CREATED = "UserCreated"
+class EnvironmentVariableType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of the Environment Variable. Possible values are: local - For local variable."""
+
+ LOCAL = "local"
+
+
class FeatureLags(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Flag for generating lags for the numeric features."""
- #: No feature lags generated.
NONE = "None"
- #: System auto-generates feature lags.
+ """No feature lags generated."""
AUTO = "Auto"
+ """System auto-generates feature lags."""
class FeaturizationMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Featurization mode - determines data featurization mode."""
- #: Auto mode, system performs featurization without any custom featurization inputs.
AUTO = "Auto"
- #: Custom featurization.
+ """Auto mode, system performs featurization without any custom featurization inputs."""
CUSTOM = "Custom"
- #: Featurization off. 'Forecasting' task cannot use this value.
+ """Custom featurization."""
OFF = "Off"
+ """Featurization off. 'Forecasting' task cannot use this value."""
class ForecastHorizonMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum to determine forecast horizon selection mode."""
- #: Forecast horizon to be determined automatically.
AUTO = "Auto"
- #: Use the custom forecast horizon.
+ """Forecast horizon to be determined automatically."""
CUSTOM = "Custom"
+ """Use the custom forecast horizon."""
class ForecastingModels(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum for all forecasting models supported by AutoML."""
- #: Auto-Autoregressive Integrated Moving Average (ARIMA) model uses time-series data and
+ AUTO_ARIMA = "AutoArima"
+ """Auto-Autoregressive Integrated Moving Average (ARIMA) model uses time-series data and
#: statistical analysis to interpret the data and make future predictions.
#: This model aims to explain data by using time series data on its past values and uses linear
- #: regression to make predictions.
- AUTO_ARIMA = "AutoArima"
- #: Prophet is a procedure for forecasting time series data based on an additive model where
+ #: regression to make predictions."""
+ PROPHET = "Prophet"
+ """Prophet is a procedure for forecasting time series data based on an additive model where
#: non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.
#: It works best with time series that have strong seasonal effects and several seasons of
#: historical data. Prophet is robust to missing data and shifts in the trend, and typically
- #: handles outliers well.
- PROPHET = "Prophet"
- #: The Naive forecasting model makes predictions by carrying forward the latest target value for
- #: each time-series in the training data.
+ #: handles outliers well."""
NAIVE = "Naive"
- #: The Seasonal Naive forecasting model makes predictions by carrying forward the latest season of
- #: target values for each time-series in the training data.
+ """The Naive forecasting model makes predictions by carrying forward the latest target value for
+ #: each time-series in the training data."""
SEASONAL_NAIVE = "SeasonalNaive"
- #: The Average forecasting model makes predictions by carrying forward the average of the target
- #: values for each time-series in the training data.
+ """The Seasonal Naive forecasting model makes predictions by carrying forward the latest season of
+ #: target values for each time-series in the training data."""
AVERAGE = "Average"
- #: The Seasonal Average forecasting model makes predictions by carrying forward the average value
- #: of the latest season of data for each time-series in the training data.
+ """The Average forecasting model makes predictions by carrying forward the average of the target
+ #: values for each time-series in the training data."""
SEASONAL_AVERAGE = "SeasonalAverage"
- #: Exponential smoothing is a time series forecasting method for univariate data that can be
- #: extended to support data with a systematic trend or seasonal component.
+ """The Seasonal Average forecasting model makes predictions by carrying forward the average value
+ #: of the latest season of data for each time-series in the training data."""
EXPONENTIAL_SMOOTHING = "ExponentialSmoothing"
- #: An Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) model can be
+ """Exponential smoothing is a time series forecasting method for univariate data that can be
+ #: extended to support data with a systematic trend or seasonal component."""
+ ARIMAX = "Arimax"
+ """An Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) model can be
#: viewed as a multiple regression model with one or more autoregressive (AR) terms and/or one or
#: more moving average (MA) terms.
#: This method is suitable for forecasting when data is stationary/non stationary, and
- #: multivariate with any type of data pattern, i.e., level/trend /seasonality/cyclicity.
- ARIMAX = "Arimax"
- #: TCNForecaster: Temporal Convolutional Networks Forecaster. //TODO: Ask forecasting team for
- #: brief intro.
+ #: multivariate with any type of data pattern, i.e., level/trend /seasonality/cyclicity."""
TCN_FORECASTER = "TCNForecaster"
- #: Elastic net is a popular type of regularized linear regression that combines two popular
- #: penalties, specifically the L1 and L2 penalty functions.
+ """TCNForecaster: Temporal Convolutional Networks Forecaster. //TODO: Ask forecasting team for
+ #: brief intro."""
ELASTIC_NET = "ElasticNet"
- #: The technique of transiting week learners into a strong learner is called Boosting. The
- #: gradient boosting algorithm process works on this theory of execution.
+ """Elastic net is a popular type of regularized linear regression that combines two popular
+ #: penalties, specifically the L1 and L2 penalty functions."""
GRADIENT_BOOSTING = "GradientBoosting"
- #: Decision Trees are a non-parametric supervised learning method used for both classification and
+ """The technique of transiting week learners into a strong learner is called Boosting. The
+ #: gradient boosting algorithm process works on this theory of execution."""
+ DECISION_TREE = "DecisionTree"
+ """Decision Trees are a non-parametric supervised learning method used for both classification and
#: regression tasks.
#: The goal is to create a model that predicts the value of a target variable by learning simple
- #: decision rules inferred from the data features.
- DECISION_TREE = "DecisionTree"
- #: K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new
+ #: decision rules inferred from the data features."""
+ KNN = "KNN"
+ """K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new
#: datapoints
#: which further means that the new data point will be assigned a value based on how closely it
- #: matches the points in the training set.
- KNN = "KNN"
- #: Lasso model fit with Least Angle Regression a.k.a. Lars. It is a Linear Model trained with an
- #: L1 prior as regularizer.
+ #: matches the points in the training set."""
LASSO_LARS = "LassoLars"
- #: SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning
+ """Lasso model fit with Least Angle Regression a.k.a. Lars. It is a Linear Model trained with an
+ #: L1 prior as regularizer."""
+ SGD = "SGD"
+ """SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning
#: applications
#: to find the model parameters that correspond to the best fit between predicted and actual
#: outputs.
- #: It's an inexact but powerful technique.
- SGD = "SGD"
- #: Random forest is a supervised learning algorithm.
+ #: It's an inexact but powerful technique."""
+ RANDOM_FOREST = "RandomForest"
+ """Random forest is a supervised learning algorithm.
#: The "forest" it builds, is an ensemble of decision trees, usually trained with the “bagging”
#: method.
#: The general idea of the bagging method is that a combination of learning models increases the
- #: overall result.
- RANDOM_FOREST = "RandomForest"
- #: Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many
- #: decision trees. It is related to the widely used random forest algorithm.
+ #: overall result."""
EXTREME_RANDOM_TREES = "ExtremeRandomTrees"
- #: LightGBM is a gradient boosting framework that uses tree based learning algorithms.
+ """Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many
+ #: decision trees. It is related to the widely used random forest algorithm."""
LIGHT_GBM = "LightGBM"
- #: XGBoostRegressor: Extreme Gradient Boosting Regressor is a supervised machine learning model
- #: using ensemble of base learners.
+ """LightGBM is a gradient boosting framework that uses tree based learning algorithms."""
XG_BOOST_REGRESSOR = "XGBoostRegressor"
+ """XGBoostRegressor: Extreme Gradient Boosting Regressor is a supervised machine learning model
+ #: using ensemble of base learners."""
class ForecastingPrimaryMetrics(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Primary metrics for Forecasting task."""
- #: The Spearman's rank coefficient of correlation is a non-parametric measure of rank correlation.
SPEARMAN_CORRELATION = "SpearmanCorrelation"
- #: The Normalized Root Mean Squared Error (NRMSE) the RMSE facilitates the comparison between
- #: models with different scales.
+ """The Spearman's rank coefficient of correlation is a non-parametric measure of rank correlation."""
NORMALIZED_ROOT_MEAN_SQUARED_ERROR = "NormalizedRootMeanSquaredError"
- #: The R2 score is one of the performance evaluation measures for forecasting-based machine
- #: learning models.
+ """The Normalized Root Mean Squared Error (NRMSE) the RMSE facilitates the comparison between
+ #: models with different scales."""
R2_SCORE = "R2Score"
- #: The Normalized Mean Absolute Error (NMAE) is a validation metric to compare the Mean Absolute
- #: Error (MAE) of (time) series with different scales.
+ """The R2 score is one of the performance evaluation measures for forecasting-based machine
+ #: learning models."""
NORMALIZED_MEAN_ABSOLUTE_ERROR = "NormalizedMeanAbsoluteError"
+ """The Normalized Mean Absolute Error (NMAE) is a validation metric to compare the Mean Absolute
+ #: Error (MAE) of (time) series with different scales."""
class Goal(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -556,6 +582,15 @@ class IdentityConfigurationType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
USER_IDENTITY = "UserIdentity"
+class ImageType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of the image. Possible values are: docker - For docker images. azureml - For AzureML
+ images.
+ """
+
+ DOCKER = "docker"
+ AZUREML = "azureml"
+
+
class InputDeliveryMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum to determine the input data delivery mode."""
@@ -570,9 +605,9 @@ class InputDeliveryMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class InstanceSegmentationPrimaryMetrics(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Primary metrics for InstanceSegmentation tasks."""
- #: Mean Average Precision (MAP) is the average of AP (Average Precision).
- #: AP is calculated for each class and averaged to get the MAP.
MEAN_AVERAGE_PRECISION = "MeanAveragePrecision"
+ """Mean Average Precision (MAP) is the average of AP (Average Precision).
+ #: AP is calculated for each class and averaged to get the MAP."""
class JobInputType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -608,39 +643,39 @@ class JobOutputType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class JobStatus(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""The status of a job."""
- #: Run hasn't started yet.
NOT_STARTED = "NotStarted"
- #: Run has started. The user has a run ID.
+ """Run hasn't started yet."""
STARTING = "Starting"
- #: (Not used currently) It will be used if ES is creating the compute target.
+ """Run has started. The user has a run ID."""
PROVISIONING = "Provisioning"
- #: The run environment is being prepared.
+ """(Not used currently) It will be used if ES is creating the compute target."""
PREPARING = "Preparing"
- #: The job is queued in the compute target. For example, in BatchAI the job is in queued state,
- #: while waiting for all required nodes to be ready.
+ """The run environment is being prepared."""
QUEUED = "Queued"
- #: The job started to run in the compute target.
+ """The job is queued in the compute target. For example, in BatchAI the job is in queued state,
+ #: while waiting for all required nodes to be ready."""
RUNNING = "Running"
- #: Job is completed in the target. It is in output collection state now.
+ """The job started to run in the compute target."""
FINALIZING = "Finalizing"
- #: Cancellation has been requested for the job.
+ """Job is completed in the target. It is in output collection state now."""
CANCEL_REQUESTED = "CancelRequested"
- #: Job completed successfully. This reflects that both the job itself and output collection states
- #: completed successfully
+ """Cancellation has been requested for the job."""
COMPLETED = "Completed"
- #: Job failed.
+ """Job completed successfully. This reflects that both the job itself and output collection states
+ #: completed successfully"""
FAILED = "Failed"
- #: Following cancellation request, the job is now successfully canceled.
+ """Job failed."""
CANCELED = "Canceled"
- #: When heartbeat is enabled, if the run isn't updating any information to RunHistory then the run
+ """Following cancellation request, the job is now successfully canceled."""
+ NOT_RESPONDING = "NotResponding"
+ """When heartbeat is enabled, if the run isn't updating any information to RunHistory then the run
#: goes to NotResponding state.
#: NotResponding is the only state that is exempt from strict transition orders. A run can go from
- #: NotResponding to any of the previous states.
- NOT_RESPONDING = "NotResponding"
- #: The job is paused by users. Some adjustment to labeling jobs can be made only in paused state.
+ #: NotResponding to any of the previous states."""
PAUSED = "Paused"
- #: Default job status if not mapped to all other statuses
+ """The job is paused by users. Some adjustment to labeling jobs can be made only in paused state."""
UNKNOWN = "Unknown"
+ """Default job status if not mapped to all other statuses"""
class JobType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -662,12 +697,12 @@ class KeyType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class LearningRateScheduler(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Learning rate scheduler enum."""
- #: No learning rate scheduler selected.
NONE = "None"
- #: Cosine Annealing With Warmup.
+ """No learning rate scheduler selected."""
WARMUP_COSINE = "WarmupCosine"
- #: Step learning rate scheduler.
+ """Cosine Annealing With Warmup."""
STEP = "Step"
+ """Step learning rate scheduler."""
class ListViewType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -688,18 +723,18 @@ class LoadBalancerType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class LogVerbosity(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum for setting log verbosity."""
- #: No logs emitted.
NOT_SET = "NotSet"
- #: Debug and above log statements logged.
+ """No logs emitted."""
DEBUG = "Debug"
- #: Info and above log statements logged.
+ """Debug and above log statements logged."""
INFO = "Info"
- #: Warning and above log statements logged.
+ """Info and above log statements logged."""
WARNING = "Warning"
- #: Error and above log statements logged.
+ """Warning and above log statements logged."""
ERROR = "Error"
- #: Only critical statements logged.
+ """Error and above log statements logged."""
CRITICAL = "Critical"
+ """Only critical statements logged."""
class ManagedServiceIdentityType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -716,16 +751,16 @@ class ManagedServiceIdentityType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class ModelSize(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Image model size."""
- #: No value selected.
NONE = "None"
- #: Small size.
+ """No value selected."""
SMALL = "Small"
- #: Medium size.
+ """Small size."""
MEDIUM = "Medium"
- #: Large size.
+ """Medium size."""
LARGE = "Large"
- #: Extra large size.
+ """Large size."""
EXTRA_LARGE = "ExtraLarge"
+ """Extra large size."""
class MountAction(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -749,11 +784,11 @@ class MountState(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class NCrossValidationsMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Determines how N-Cross validations value is determined."""
- #: Determine N-Cross validations value automatically. Supported only for 'Forecasting' AutoML
- #: task.
AUTO = "Auto"
- #: Use custom N-Cross validations value.
+ """Determine N-Cross validations value automatically. Supported only for 'Forecasting' AutoML
+ #: task."""
CUSTOM = "Custom"
+ """Use custom N-Cross validations value."""
class Network(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -776,12 +811,18 @@ class NodeState(str, Enum, metaclass=CaseInsensitiveEnumMeta):
PREEMPTED = "preempted"
+class NodesValueType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """The enumerated types for the nodes value."""
+
+ ALL = "All"
+
+
class ObjectDetectionPrimaryMetrics(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Primary metrics for Image ObjectDetection task."""
- #: Mean Average Precision (MAP) is the average of AP (Average Precision).
- #: AP is calculated for each class and averaged to get the MAP.
MEAN_AVERAGE_PRECISION = "MeanAveragePrecision"
+ """Mean Average Precision (MAP) is the average of AP (Average Precision).
+ #: AP is calculated for each class and averaged to get the MAP."""
class OperatingSystemType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -846,6 +887,19 @@ class OutputDeliveryMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
UPLOAD = "Upload"
+class PendingUploadCredentialType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Enum to determine the PendingUpload credentials type."""
+
+ SAS = "SAS"
+
+
+class PendingUploadType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of storage to use for the pending upload location."""
+
+ NONE = "None"
+ TEMPORARY_BLOB_REFERENCE = "TemporaryBlobReference"
+
+
class PrivateEndpointConnectionProvisioningState(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""The current provisioning state."""
@@ -865,6 +919,14 @@ class PrivateEndpointServiceConnectionStatus(str, Enum, metaclass=CaseInsensitiv
TIMEOUT = "Timeout"
+class Protocol(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Protocol over which communication will happen over this endpoint."""
+
+ TCP = "tcp"
+ UDP = "udp"
+ HTTP = "http"
+
+
class ProvisioningState(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""The current deployment state of workspace resource. The provisioningState is to indicate states
for resource provisioning.
@@ -917,16 +979,16 @@ class RandomSamplingAlgorithmRule(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class RecurrenceFrequency(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum to describe the frequency of a recurrence schedule."""
- #: Minute frequency
MINUTE = "Minute"
- #: Hour frequency
+ """Minute frequency"""
HOUR = "Hour"
- #: Day frequency
+ """Hour frequency"""
DAY = "Day"
- #: Week frequency
+ """Day frequency"""
WEEK = "Week"
- #: Month frequency
+ """Week frequency"""
MONTH = "Month"
+ """Month frequency"""
class ReferenceType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -940,61 +1002,61 @@ class ReferenceType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class RegressionModels(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum for all Regression models supported by AutoML."""
- #: Elastic net is a popular type of regularized linear regression that combines two popular
- #: penalties, specifically the L1 and L2 penalty functions.
ELASTIC_NET = "ElasticNet"
- #: The technique of transiting week learners into a strong learner is called Boosting. The
- #: gradient boosting algorithm process works on this theory of execution.
+ """Elastic net is a popular type of regularized linear regression that combines two popular
+ #: penalties, specifically the L1 and L2 penalty functions."""
GRADIENT_BOOSTING = "GradientBoosting"
- #: Decision Trees are a non-parametric supervised learning method used for both classification and
+ """The technique of transiting week learners into a strong learner is called Boosting. The
+ #: gradient boosting algorithm process works on this theory of execution."""
+ DECISION_TREE = "DecisionTree"
+ """Decision Trees are a non-parametric supervised learning method used for both classification and
#: regression tasks.
#: The goal is to create a model that predicts the value of a target variable by learning simple
- #: decision rules inferred from the data features.
- DECISION_TREE = "DecisionTree"
- #: K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new
+ #: decision rules inferred from the data features."""
+ KNN = "KNN"
+ """K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new
#: datapoints
#: which further means that the new data point will be assigned a value based on how closely it
- #: matches the points in the training set.
- KNN = "KNN"
- #: Lasso model fit with Least Angle Regression a.k.a. Lars. It is a Linear Model trained with an
- #: L1 prior as regularizer.
+ #: matches the points in the training set."""
LASSO_LARS = "LassoLars"
- #: SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning
+ """Lasso model fit with Least Angle Regression a.k.a. Lars. It is a Linear Model trained with an
+ #: L1 prior as regularizer."""
+ SGD = "SGD"
+ """SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning
#: applications
#: to find the model parameters that correspond to the best fit between predicted and actual
#: outputs.
- #: It's an inexact but powerful technique.
- SGD = "SGD"
- #: Random forest is a supervised learning algorithm.
+ #: It's an inexact but powerful technique."""
+ RANDOM_FOREST = "RandomForest"
+ """Random forest is a supervised learning algorithm.
#: The "forest"\ it builds, is an ensemble of decision trees, usually trained with the “bagging”\
#: method.
#: The general idea of the bagging method is that a combination of learning models increases the
- #: overall result.
- RANDOM_FOREST = "RandomForest"
- #: Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many
- #: decision trees. It is related to the widely used random forest algorithm.
+ #: overall result."""
EXTREME_RANDOM_TREES = "ExtremeRandomTrees"
- #: LightGBM is a gradient boosting framework that uses tree based learning algorithms.
+ """Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many
+ #: decision trees. It is related to the widely used random forest algorithm."""
LIGHT_GBM = "LightGBM"
- #: XGBoostRegressor: Extreme Gradient Boosting Regressor is a supervised machine learning model
- #: using ensemble of base learners.
+ """LightGBM is a gradient boosting framework that uses tree based learning algorithms."""
XG_BOOST_REGRESSOR = "XGBoostRegressor"
+ """XGBoostRegressor: Extreme Gradient Boosting Regressor is a supervised machine learning model
+ #: using ensemble of base learners."""
class RegressionPrimaryMetrics(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Primary metrics for Regression task."""
- #: The Spearman's rank coefficient of correlation is a nonparametric measure of rank correlation.
SPEARMAN_CORRELATION = "SpearmanCorrelation"
- #: The Normalized Root Mean Squared Error (NRMSE) the RMSE facilitates the comparison between
- #: models with different scales.
+ """The Spearman's rank coefficient of correlation is a nonparametric measure of rank correlation."""
NORMALIZED_ROOT_MEAN_SQUARED_ERROR = "NormalizedRootMeanSquaredError"
- #: The R2 score is one of the performance evaluation measures for forecasting-based machine
- #: learning models.
+ """The Normalized Root Mean Squared Error (NRMSE) the RMSE facilitates the comparison between
+ #: models with different scales."""
R2_SCORE = "R2Score"
- #: The Normalized Mean Absolute Error (NMAE) is a validation metric to compare the Mean Absolute
- #: Error (MAE) of (time) series with different scales.
+ """The R2 score is one of the performance evaluation measures for forecasting-based machine
+ #: learning models."""
NORMALIZED_MEAN_ABSOLUTE_ERROR = "NormalizedMeanAbsoluteError"
+ """The Normalized Mean Absolute Error (NMAE) is a validation metric to compare the Mean Absolute
+ #: Error (MAE) of (time) series with different scales."""
class RemoteLoginPortPublicAccess(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -1070,10 +1132,10 @@ class ScheduleStatus(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class SeasonalityMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Forecasting seasonality mode."""
- #: Seasonality to be determined automatically.
AUTO = "Auto"
- #: Use the custom seasonality value.
+ """Seasonality to be determined automatically."""
CUSTOM = "Custom"
+ """Use the custom seasonality value."""
class SecretsType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -1088,37 +1150,37 @@ class SecretsType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class ServiceDataAccessAuthIdentity(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""ServiceDataAccessAuthIdentity."""
- #: Do not use any identity for service data access.
NONE = "None"
- #: Use the system assigned managed identity of the Workspace to authenticate service data access.
+ """Do not use any identity for service data access."""
WORKSPACE_SYSTEM_ASSIGNED_IDENTITY = "WorkspaceSystemAssignedIdentity"
- #: Use the user assigned managed identity of the Workspace to authenticate service data access.
+ """Use the system assigned managed identity of the Workspace to authenticate service data access."""
WORKSPACE_USER_ASSIGNED_IDENTITY = "WorkspaceUserAssignedIdentity"
+ """Use the user assigned managed identity of the Workspace to authenticate service data access."""
class ShortSeriesHandlingConfiguration(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""The parameter defining how if AutoML should handle short time series."""
- #: Represents no/null value.
NONE = "None"
- #: Short series will be padded if there are no long series, otherwise short series will be
- #: dropped.
+ """Represents no/null value."""
AUTO = "Auto"
- #: All the short series will be padded.
+ """Short series will be padded if there are no long series, otherwise short series will be
+ #: dropped."""
PAD = "Pad"
- #: All the short series will be dropped.
+ """All the short series will be padded."""
DROP = "Drop"
+ """All the short series will be dropped."""
class SkuScaleType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Node scaling setting for the compute sku."""
- #: Automatically scales node count.
AUTOMATIC = "Automatic"
- #: Node count scaled upon user request.
+ """Automatically scales node count."""
MANUAL = "Manual"
- #: Fixed set of nodes.
+ """Node count scaled upon user request."""
NONE = "None"
+ """Fixed set of nodes."""
class SkuTier(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -1168,15 +1230,15 @@ class StackMetaLearnerType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""
NONE = "None"
- #: Default meta-learners are LogisticRegression for classification tasks.
LOGISTIC_REGRESSION = "LogisticRegression"
- #: Default meta-learners are LogisticRegression for classification task when CV is on.
+ """Default meta-learners are LogisticRegression for classification tasks."""
LOGISTIC_REGRESSION_CV = "LogisticRegressionCV"
+ """Default meta-learners are LogisticRegression for classification task when CV is on."""
LIGHT_GBM_CLASSIFIER = "LightGBMClassifier"
- #: Default meta-learners are LogisticRegression for regression task.
ELASTIC_NET = "ElasticNet"
- #: Default meta-learners are LogisticRegression for regression task when CV is on.
+ """Default meta-learners are LogisticRegression for regression task."""
ELASTIC_NET_CV = "ElasticNetCV"
+ """Default meta-learners are LogisticRegression for regression task when CV is on."""
LIGHT_GBM_REGRESSOR = "LightGBMRegressor"
LINEAR_REGRESSION = "LinearRegression"
@@ -1197,15 +1259,15 @@ class Status(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class StochasticOptimizer(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Stochastic optimizer for image models."""
- #: No optimizer selected.
NONE = "None"
- #: Stochastic Gradient Descent optimizer.
+ """No optimizer selected."""
SGD = "Sgd"
- #: Adam is algorithm the optimizes stochastic objective functions based on adaptive estimates of
- #: moments
+ """Stochastic Gradient Descent optimizer."""
ADAM = "Adam"
- #: AdamW is a variant of the optimizer Adam that has an improved implementation of weight decay.
+ """Adam is algorithm the optimizes stochastic objective functions based on adaptive estimates of
+ #: moments"""
ADAMW = "Adamw"
+ """AdamW is a variant of the optimizer Adam that has an improved implementation of weight decay."""
class StorageAccountType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -1218,8 +1280,8 @@ class StorageAccountType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class TargetAggregationFunction(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Target aggregate function."""
- #: Represent no value set.
NONE = "None"
+ """Represent no value set."""
SUM = "Sum"
MAX = "Max"
MIN = "Min"
@@ -1229,62 +1291,62 @@ class TargetAggregationFunction(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class TargetLagsMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Target lags selection modes."""
- #: Target lags to be determined automatically.
AUTO = "Auto"
- #: Use the custom target lags.
+ """Target lags to be determined automatically."""
CUSTOM = "Custom"
+ """Use the custom target lags."""
class TargetRollingWindowSizeMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Target rolling windows size mode."""
- #: Determine rolling windows size automatically.
AUTO = "Auto"
- #: Use the specified rolling window size.
+ """Determine rolling windows size automatically."""
CUSTOM = "Custom"
+ """Use the specified rolling window size."""
class TaskType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""AutoMLJob Task type."""
- #: Classification in machine learning and statistics is a supervised learning approach in which
- #: the computer program learns from the data given to it and make new observations or
- #: classifications.
CLASSIFICATION = "Classification"
- #: Regression means to predict the value using the input data. Regression models are used to
- #: predict a continuous value.
+ """Classification in machine learning and statistics is a supervised learning approach in which
+ #: the computer program learns from the data given to it and make new observations or
+ #: classifications."""
REGRESSION = "Regression"
- #: Forecasting is a special kind of regression task that deals with time-series data and creates
- #: forecasting model
- #: that can be used to predict the near future values based on the inputs.
+ """Regression means to predict the value using the input data. Regression models are used to
+ #: predict a continuous value."""
FORECASTING = "Forecasting"
- #: Image Classification. Multi-class image classification is used when an image is classified with
+ """Forecasting is a special kind of regression task that deals with time-series data and creates
+ #: forecasting model
+ #: that can be used to predict the near future values based on the inputs."""
+ IMAGE_CLASSIFICATION = "ImageClassification"
+ """Image Classification. Multi-class image classification is used when an image is classified with
#: only a single label
#: from a set of classes - e.g. each image is classified as either an image of a 'cat' or a 'dog'
- #: or a 'duck'.
- IMAGE_CLASSIFICATION = "ImageClassification"
- #: Image Classification Multilabel. Multi-label image classification is used when an image could
- #: have one or more labels
- #: from a set of labels - e.g. an image could be labeled with both 'cat' and 'dog'.
+ #: or a 'duck'."""
IMAGE_CLASSIFICATION_MULTILABEL = "ImageClassificationMultilabel"
- #: Image Object Detection. Object detection is used to identify objects in an image and locate
- #: each object with a
- #: bounding box e.g. locate all dogs and cats in an image and draw a bounding box around each.
+ """Image Classification Multilabel. Multi-label image classification is used when an image could
+ #: have one or more labels
+ #: from a set of labels - e.g. an image could be labeled with both 'cat' and 'dog'."""
IMAGE_OBJECT_DETECTION = "ImageObjectDetection"
- #: Image Instance Segmentation. Instance segmentation is used to identify objects in an image at
- #: the pixel level,
- #: drawing a polygon around each object in the image.
+ """Image Object Detection. Object detection is used to identify objects in an image and locate
+ #: each object with a
+ #: bounding box e.g. locate all dogs and cats in an image and draw a bounding box around each."""
IMAGE_INSTANCE_SEGMENTATION = "ImageInstanceSegmentation"
- #: Text classification (also known as text tagging or text categorization) is the process of
- #: sorting texts into categories.
- #: Categories are mutually exclusive.
+ """Image Instance Segmentation. Instance segmentation is used to identify objects in an image at
+ #: the pixel level,
+ #: drawing a polygon around each object in the image."""
TEXT_CLASSIFICATION = "TextClassification"
- #: Multilabel classification task assigns each sample to a group (zero or more) of target labels.
+ """Text classification (also known as text tagging or text categorization) is the process of
+ #: sorting texts into categories.
+ #: Categories are mutually exclusive."""
TEXT_CLASSIFICATION_MULTILABEL = "TextClassificationMultilabel"
- #: Text Named Entity Recognition a.k.a. TextNER.
- #: Named Entity Recognition (NER) is the ability to take free-form text and identify the
- #: occurrences of entities such as people, locations, organizations, and more.
+ """Multilabel classification task assigns each sample to a group (zero or more) of target labels."""
TEXT_NER = "TextNER"
+ """Text Named Entity Recognition a.k.a. TextNER.
+ #: Named Entity Recognition (NER) is the ability to take free-form text and identify the
+ #: occurrences of entities such as people, locations, organizations, and more."""
class TriggerType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -1316,8 +1378,8 @@ class UsageUnit(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class UseStl(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Configure STL Decomposition of the time-series target column."""
- #: No stl decomposition.
NONE = "None"
+ """No stl decomposition."""
SEASON = "Season"
SEASON_TREND = "SeasonTrend"
@@ -1325,14 +1387,14 @@ class UseStl(str, Enum, metaclass=CaseInsensitiveEnumMeta):
class ValidationMetricType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Metric computation method to use for validation metrics in image tasks."""
- #: No metric.
NONE = "None"
- #: Coco metric.
+ """No metric."""
COCO = "Coco"
- #: Voc metric.
+ """Coco metric."""
VOC = "Voc"
- #: CocoVoc metric.
+ """Voc metric."""
COCO_VOC = "CocoVoc"
+ """CocoVoc metric."""
class ValueFormat(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -1363,20 +1425,29 @@ class VMTier(str, Enum, metaclass=CaseInsensitiveEnumMeta):
SPOT = "Spot"
+class VolumeDefinitionType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of Volume Definition. Possible Values: bind,volume,tmpfs,npipe."""
+
+ BIND = "bind"
+ VOLUME = "volume"
+ TMPFS = "tmpfs"
+ NPIPE = "npipe"
+
+
class WeekDay(str, Enum, metaclass=CaseInsensitiveEnumMeta):
"""Enum of weekday."""
- #: Monday weekday
MONDAY = "Monday"
- #: Tuesday weekday
+ """Monday weekday"""
TUESDAY = "Tuesday"
- #: Wednesday weekday
+ """Tuesday weekday"""
WEDNESDAY = "Wednesday"
- #: Thursday weekday
+ """Wednesday weekday"""
THURSDAY = "Thursday"
- #: Friday weekday
+ """Thursday weekday"""
FRIDAY = "Friday"
- #: Saturday weekday
+ """Friday weekday"""
SATURDAY = "Saturday"
- #: Sunday weekday
+ """Saturday weekday"""
SUNDAY = "Sunday"
+ """Sunday weekday"""
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/_models_py3.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/_models_py3.py
index a0c8196e7297..736189ee6853 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/_models_py3.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/_models_py3.py
@@ -56,7 +56,7 @@ class DatastoreCredentials(_serialization.Model):
}
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.credentials_type: Optional[str] = None
@@ -84,7 +84,7 @@ class AccountKeyDatastoreCredentials(DatastoreCredentials):
"secrets": {"key": "secrets", "type": "AccountKeyDatastoreSecrets"},
}
- def __init__(self, *, secrets: "_models.AccountKeyDatastoreSecrets", **kwargs):
+ def __init__(self, *, secrets: "_models.AccountKeyDatastoreSecrets", **kwargs: Any) -> None:
"""
:keyword secrets: [Required] Storage account secrets. Required.
:paramtype secrets: ~azure.mgmt.machinelearningservices.models.AccountKeyDatastoreSecrets
@@ -125,7 +125,7 @@ class DatastoreSecrets(_serialization.Model):
}
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.secrets_type: Optional[str] = None
@@ -152,7 +152,7 @@ class AccountKeyDatastoreSecrets(DatastoreSecrets):
"key": {"key": "key", "type": "str"},
}
- def __init__(self, *, key: Optional[str] = None, **kwargs):
+ def __init__(self, *, key: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword key: Storage account key.
:paramtype key: str
@@ -162,6 +162,46 @@ def __init__(self, *, key: Optional[str] = None, **kwargs):
self.key = key
+class AcrDetails(_serialization.Model):
+ """Details of ACR account to be used for the Registry.
+
+ :ivar system_created_acr_account: Details of system created ACR account to be used for the
+ Registry.
+ :vartype system_created_acr_account:
+ ~azure.mgmt.machinelearningservices.models.SystemCreatedAcrAccount
+ :ivar user_created_acr_account: Details of user created ACR account to be used for the
+ Registry.
+ :vartype user_created_acr_account:
+ ~azure.mgmt.machinelearningservices.models.UserCreatedAcrAccount
+ """
+
+ _attribute_map = {
+ "system_created_acr_account": {"key": "systemCreatedAcrAccount", "type": "SystemCreatedAcrAccount"},
+ "user_created_acr_account": {"key": "userCreatedAcrAccount", "type": "UserCreatedAcrAccount"},
+ }
+
+ def __init__(
+ self,
+ *,
+ system_created_acr_account: Optional["_models.SystemCreatedAcrAccount"] = None,
+ user_created_acr_account: Optional["_models.UserCreatedAcrAccount"] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword system_created_acr_account: Details of system created ACR account to be used for the
+ Registry.
+ :paramtype system_created_acr_account:
+ ~azure.mgmt.machinelearningservices.models.SystemCreatedAcrAccount
+ :keyword user_created_acr_account: Details of user created ACR account to be used for the
+ Registry.
+ :paramtype user_created_acr_account:
+ ~azure.mgmt.machinelearningservices.models.UserCreatedAcrAccount
+ """
+ super().__init__(**kwargs)
+ self.system_created_acr_account = system_created_acr_account
+ self.user_created_acr_account = user_created_acr_account
+
+
class AKSSchema(_serialization.Model):
"""AKSSchema.
@@ -173,7 +213,7 @@ class AKSSchema(_serialization.Model):
"properties": {"key": "properties", "type": "AKSSchemaProperties"},
}
- def __init__(self, *, properties: Optional["_models.AKSSchemaProperties"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.AKSSchemaProperties"] = None, **kwargs: Any) -> None:
"""
:keyword properties: AKS properties.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.AKSSchemaProperties
@@ -266,8 +306,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword compute_location: Location for the underlying compute.
:paramtype compute_location: str
@@ -361,8 +401,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties: AKS properties.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.AKSSchemaProperties
@@ -422,8 +462,8 @@ def __init__(
user_kube_config: Optional[str] = None,
admin_kube_config: Optional[str] = None,
image_pull_secret_name: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword user_kube_config: Content of kubeconfig file that can be used to connect to the
Kubernetes cluster.
@@ -470,7 +510,7 @@ class ComputeSecrets(_serialization.Model):
}
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.compute_type: Optional[str] = None
@@ -512,8 +552,8 @@ def __init__(
user_kube_config: Optional[str] = None,
admin_kube_config: Optional[str] = None,
image_pull_secret_name: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword user_kube_config: Content of kubeconfig file that can be used to connect to the
Kubernetes cluster.
@@ -574,8 +614,8 @@ def __init__(
service_cidr: Optional[str] = None,
dns_service_ip: Optional[str] = None,
docker_bridge_cidr: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword subnet_id: Virtual network subnet resource ID the compute nodes belong to.
:paramtype subnet_id: str
@@ -652,8 +692,8 @@ def __init__(
aks_networking_configuration: Optional["_models.AksNetworkingConfiguration"] = None,
load_balancer_type: Union[str, "_models.LoadBalancerType"] = "PublicIp",
load_balancer_subnet: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword cluster_fqdn: Cluster full qualified domain name.
:paramtype cluster_fqdn: str
@@ -688,6 +728,57 @@ def __init__(
self.load_balancer_subnet = load_balancer_subnet
+class Nodes(_serialization.Model):
+ """Abstract Nodes definition.
+
+ You probably want to use the sub-classes and not this class directly. Known sub-classes are:
+ AllNodes
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar nodes_value_type: [Required] Type of the Nodes value. Required. "All"
+ :vartype nodes_value_type: str or ~azure.mgmt.machinelearningservices.models.NodesValueType
+ """
+
+ _validation = {
+ "nodes_value_type": {"required": True},
+ }
+
+ _attribute_map = {
+ "nodes_value_type": {"key": "nodesValueType", "type": "str"},
+ }
+
+ _subtype_map = {"nodes_value_type": {"All": "AllNodes"}}
+
+ def __init__(self, **kwargs: Any) -> None:
+ """ """
+ super().__init__(**kwargs)
+ self.nodes_value_type: Optional[str] = None
+
+
+class AllNodes(Nodes):
+ """All nodes means the service will be running on all of the nodes of the job.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar nodes_value_type: [Required] Type of the Nodes value. Required. "All"
+ :vartype nodes_value_type: str or ~azure.mgmt.machinelearningservices.models.NodesValueType
+ """
+
+ _validation = {
+ "nodes_value_type": {"required": True},
+ }
+
+ _attribute_map = {
+ "nodes_value_type": {"key": "nodesValueType", "type": "str"},
+ }
+
+ def __init__(self, **kwargs: Any) -> None:
+ """ """
+ super().__init__(**kwargs)
+ self.nodes_value_type: str = "All"
+
+
class AmlComputeSchema(_serialization.Model):
"""Properties(top level) of AmlCompute.
@@ -699,7 +790,7 @@ class AmlComputeSchema(_serialization.Model):
"properties": {"key": "properties", "type": "AmlComputeProperties"},
}
- def __init__(self, *, properties: Optional["_models.AmlComputeProperties"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.AmlComputeProperties"] = None, **kwargs: Any) -> None:
"""
:keyword properties: Properties of AmlCompute.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.AmlComputeProperties
@@ -777,8 +868,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties: Properties of AmlCompute.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.AmlComputeProperties
@@ -852,7 +943,7 @@ class AmlComputeNodeInformation(_serialization.Model):
"run_id": {"key": "runId", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.node_id = None
@@ -884,7 +975,7 @@ class AmlComputeNodesInformation(_serialization.Model):
"next_link": {"key": "nextLink", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.nodes = None
@@ -996,8 +1087,8 @@ def __init__(
remote_login_port_public_access: Union[str, "_models.RemoteLoginPortPublicAccess"] = "NotSpecified",
enable_node_public_ip: bool = True,
property_bag: Optional[JSON] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword os_type: Compute OS Type. Known values are: "Linux" and "Windows".
:paramtype os_type: str or ~azure.mgmt.machinelearningservices.models.OsType
@@ -1079,8 +1170,8 @@ def __init__(
name: Optional[str] = None,
display: Optional["_models.AmlOperationDisplay"] = None,
is_data_action: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword name: Operation name: {provider}/{resource}/{operation}.
:paramtype name: str
@@ -1122,8 +1213,8 @@ def __init__(
resource: Optional[str] = None,
operation: Optional[str] = None,
description: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword provider: The resource provider name: Microsoft.MachineLearningExperimentation.
:paramtype provider: str
@@ -1152,7 +1243,7 @@ class AmlOperationListResult(_serialization.Model):
"value": {"key": "value", "type": "[AmlOperation]"},
}
- def __init__(self, *, value: Optional[List["_models.AmlOperation"]] = None, **kwargs):
+ def __init__(self, *, value: Optional[List["_models.AmlOperation"]] = None, **kwargs: Any) -> None:
"""
:keyword value: List of AML workspace operations supported by the AML workspace resource
provider.
@@ -1188,7 +1279,7 @@ class IdentityConfiguration(_serialization.Model):
"identity_type": {"AMLToken": "AmlToken", "Managed": "ManagedIdentity", "UserIdentity": "UserIdentity"}
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.identity_type: Optional[str] = None
@@ -1213,7 +1304,7 @@ class AmlToken(IdentityConfiguration):
"identity_type": {"key": "identityType", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.identity_type: str = "AMLToken"
@@ -1242,8 +1333,8 @@ def __init__(
id: Optional[str] = None, # pylint: disable=redefined-builtin
display_name: Optional[str] = None,
description: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword id: Specifies the feature ID.
:paramtype id: str
@@ -1258,6 +1349,32 @@ def __init__(
self.description = description
+class ArmResourceId(_serialization.Model):
+ """ARM ResourceId of a resource.
+
+ :ivar resource_id: Arm ResourceId is in the format
+ "/subscriptions/{SubscriptionId}/resourceGroups/{ResourceGroupName}/providers/Microsoft.Storage/storageAccounts/{StorageAccountName}"
+ or
+ "/subscriptions/{SubscriptionId}/resourceGroups/{ResourceGroupName}/providers/Microsoft.ContainerRegistry/registries/{AcrName}".
+ :vartype resource_id: str
+ """
+
+ _attribute_map = {
+ "resource_id": {"key": "resourceId", "type": "str"},
+ }
+
+ def __init__(self, *, resource_id: Optional[str] = None, **kwargs: Any) -> None:
+ """
+ :keyword resource_id: Arm ResourceId is in the format
+ "/subscriptions/{SubscriptionId}/resourceGroups/{ResourceGroupName}/providers/Microsoft.Storage/storageAccounts/{StorageAccountName}"
+ or
+ "/subscriptions/{SubscriptionId}/resourceGroups/{ResourceGroupName}/providers/Microsoft.ContainerRegistry/registries/{AcrName}".
+ :paramtype resource_id: str
+ """
+ super().__init__(**kwargs)
+ self.resource_id = resource_id
+
+
class ResourceBase(_serialization.Model):
"""ResourceBase.
@@ -1281,8 +1398,8 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -1328,8 +1445,8 @@ def __init__(
tags: Optional[Dict[str, str]] = None,
is_anonymous: bool = False,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -1387,8 +1504,8 @@ def __init__(
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -1418,7 +1535,7 @@ class AssetJobInput(_serialization.Model):
"""
_validation = {
- "uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -1426,7 +1543,9 @@ class AssetJobInput(_serialization.Model):
"uri": {"key": "uri", "type": "str"},
}
- def __init__(self, *, uri: str, mode: Optional[Union[str, "_models.InputDeliveryMode"]] = None, **kwargs):
+ def __init__(
+ self, *, uri: str, mode: Optional[Union[str, "_models.InputDeliveryMode"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword mode: Input Asset Delivery Mode. Known values are: "ReadOnlyMount", "ReadWriteMount",
"Download", "Direct", "EvalMount", and "EvalDownload".
@@ -1454,8 +1573,12 @@ class AssetJobOutput(_serialization.Model):
}
def __init__(
- self, *, mode: Optional[Union[str, "_models.OutputDeliveryMode"]] = None, uri: Optional[str] = None, **kwargs
- ):
+ self,
+ *,
+ mode: Optional[Union[str, "_models.OutputDeliveryMode"]] = None,
+ uri: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword mode: Output Asset Delivery Mode. Known values are: "ReadWriteMount" and "Upload".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -1496,7 +1619,7 @@ class AssetReferenceBase(_serialization.Model):
}
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.reference_type: Optional[str] = None
@@ -1523,7 +1646,7 @@ class AssignedUser(_serialization.Model):
"tenant_id": {"key": "tenantId", "type": "str"},
}
- def __init__(self, *, object_id: str, tenant_id: str, **kwargs):
+ def __init__(self, *, object_id: str, tenant_id: str, **kwargs: Any) -> None:
"""
:keyword object_id: User’s AAD Object Id. Required.
:paramtype object_id: str
@@ -1558,7 +1681,7 @@ class ForecastHorizon(_serialization.Model):
_subtype_map = {"mode": {"Auto": "AutoForecastHorizon", "Custom": "CustomForecastHorizon"}}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: Optional[str] = None
@@ -1582,7 +1705,7 @@ class AutoForecastHorizon(ForecastHorizon):
"mode": {"key": "mode", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: str = "Auto"
@@ -1668,8 +1791,8 @@ def __init__(
identity: Optional["_models.IdentityConfiguration"] = None,
is_archived: bool = False,
services: Optional[Dict[str, "_models.JobService"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -1713,54 +1836,54 @@ class AutoMLJob(JobBaseProperties): # pylint: disable=too-many-instance-attribu
Use this class for executing AutoML tasks like Classification/Regression etc.
See TaskType enum for all the tasks supported.
- Variables are only populated by the server, and will be ignored when sending a request.
-
- All required parameters must be populated in order to send to Azure.
-
- :ivar description: The asset description text.
- :vartype description: str
- :ivar properties: The asset property dictionary.
- :vartype properties: dict[str, str]
- :ivar tags: Tag dictionary. Tags can be added, removed, and updated.
- :vartype tags: dict[str, str]
- :ivar component_id: ARM resource ID of the component resource.
- :vartype component_id: str
- :ivar compute_id: ARM resource ID of the compute resource.
- :vartype compute_id: str
- :ivar display_name: Display name of job.
- :vartype display_name: str
- :ivar experiment_name: The name of the experiment the job belongs to. If not set, the job is
- placed in the "Default" experiment.
- :vartype experiment_name: str
- :ivar identity: Identity configuration. If set, this should be one of AmlToken,
- ManagedIdentity, UserIdentity or null.
- Defaults to AmlToken if null.
- :vartype identity: ~azure.mgmt.machinelearningservices.models.IdentityConfiguration
- :ivar is_archived: Is the asset archived?.
- :vartype is_archived: bool
- :ivar job_type: [Required] Specifies the type of job. Required. Known values are: "AutoML",
- "Command", "Sweep", and "Pipeline".
- :vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
- :ivar services: List of JobEndpoints.
- For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
- :vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
- :ivar status: Status of the job. Known values are: "NotStarted", "Starting", "Provisioning",
- "Preparing", "Queued", "Running", "Finalizing", "CancelRequested", "Completed", "Failed",
- "Canceled", "NotResponding", "Paused", and "Unknown".
- :vartype status: str or ~azure.mgmt.machinelearningservices.models.JobStatus
- :ivar environment_id: The ARM resource ID of the Environment specification for the job.
- This is optional value to provide, if not provided, AutoML will default this to Production
- AutoML curated environment version when running the job.
- :vartype environment_id: str
- :ivar environment_variables: Environment variables included in the job.
- :vartype environment_variables: dict[str, str]
- :ivar outputs: Mapping of output data bindings used in the job.
- :vartype outputs: dict[str, ~azure.mgmt.machinelearningservices.models.JobOutput]
- :ivar resources: Compute Resource configuration for the job.
- :vartype resources: ~azure.mgmt.machinelearningservices.models.JobResourceConfiguration
- :ivar task_details: [Required] This represents scenario which can be one of Tables/NLP/Image.
- Required.
- :vartype task_details: ~azure.mgmt.machinelearningservices.models.AutoMLVertical
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar description: The asset description text.
+ :vartype description: str
+ :ivar properties: The asset property dictionary.
+ :vartype properties: dict[str, str]
+ :ivar tags: Tag dictionary. Tags can be added, removed, and updated.
+ :vartype tags: dict[str, str]
+ :ivar component_id: ARM resource ID of the component resource.
+ :vartype component_id: str
+ :ivar compute_id: ARM resource ID of the compute resource.
+ :vartype compute_id: str
+ :ivar display_name: Display name of job.
+ :vartype display_name: str
+ :ivar experiment_name: The name of the experiment the job belongs to. If not set, the job is
+ placed in the "Default" experiment.
+ :vartype experiment_name: str
+ :ivar identity: Identity configuration. If set, this should be one of AmlToken,
+ ManagedIdentity, UserIdentity or null.
+ Defaults to AmlToken if null.
+ :vartype identity: ~azure.mgmt.machinelearningservices.models.IdentityConfiguration
+ :ivar is_archived: Is the asset archived?.
+ :vartype is_archived: bool
+ :ivar job_type: [Required] Specifies the type of job. Required. Known values are: "AutoML",
+ "Command", "Sweep", and "Pipeline".
+ :vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
+ :ivar services: List of JobEndpoints.
+ For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
+ :vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
+ :ivar status: Status of the job. Known values are: "NotStarted", "Starting", "Provisioning",
+ "Preparing", "Queued", "Running", "Finalizing", "CancelRequested", "Completed", "Failed",
+ "Canceled", "NotResponding", "Paused", and "Unknown".
+ :vartype status: str or ~azure.mgmt.machinelearningservices.models.JobStatus
+ :ivar environment_id: The ARM resource ID of the Environment specification for the job.
+ This is optional value to provide, if not provided, AutoML will default this to Production
+ AutoML curated environment version when running the job.
+ :vartype environment_id: str
+ :ivar environment_variables: Environment variables included in the job.
+ :vartype environment_variables: dict[str, str]
+ :ivar outputs: Mapping of output data bindings used in the job.
+ :vartype outputs: dict[str, ~azure.mgmt.machinelearningservices.models.JobOutput]
+ :ivar resources: Compute Resource configuration for the job.
+ :vartype resources: ~azure.mgmt.machinelearningservices.models.JobResourceConfiguration
+ :ivar task_details: [Required] This represents scenario which can be one of Tables/NLP/Image.
+ Required.
+ :vartype task_details: ~azure.mgmt.machinelearningservices.models.AutoMLVertical
"""
_validation = {
@@ -1807,8 +1930,8 @@ def __init__(
environment_variables: Optional[Dict[str, str]] = None,
outputs: Optional[Dict[str, "_models.JobOutput"]] = None,
resources: Optional["_models.JobResourceConfiguration"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -1873,26 +1996,26 @@ class AutoMLVertical(_serialization.Model):
"""AutoML vertical class.
Base class for AutoML verticals - TableVertical/ImageVertical/NLPVertical.
- You probably want to use the sub-classes and not this class directly. Known sub-classes are:
- Classification, Forecasting, ImageClassification, ImageClassificationMultilabel,
- ImageInstanceSegmentation, ImageObjectDetection, Regression, TextClassification,
- TextClassificationMultilabel, TextNer
+ You probably want to use the sub-classes and not this class directly. Known sub-classes are:
+ Classification, Forecasting, ImageClassification, ImageClassificationMultilabel,
+ ImageInstanceSegmentation, ImageObjectDetection, Regression, TextClassification,
+ TextClassificationMultilabel, TextNer
- All required parameters must be populated in order to send to Azure.
+ All required parameters must be populated in order to send to Azure.
- :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
- "Warning", "Error", and "Critical".
- :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
- :ivar target_column_name: Target column name: This is prediction values column.
- Also known as label column name in context of classification tasks.
- :vartype target_column_name: str
- :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
- "Classification", "Regression", "Forecasting", "ImageClassification",
- "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
- "TextClassification", "TextClassificationMultilabel", and "TextNER".
- :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
- :ivar training_data: [Required] Training data input. Required.
- :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
+ "Warning", "Error", and "Critical".
+ :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
+ :ivar target_column_name: Target column name: This is prediction values column.
+ Also known as label column name in context of classification tasks.
+ :vartype target_column_name: str
+ :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
+ "Classification", "Regression", "Forecasting", "ImageClassification",
+ "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
+ "TextClassification", "TextClassificationMultilabel", and "TextNER".
+ :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
+ :ivar training_data: [Required] Training data input. Required.
+ :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
"""
_validation = {
@@ -1928,8 +2051,8 @@ def __init__(
training_data: "_models.MLTableJobInput",
log_verbosity: Optional[Union[str, "_models.LogVerbosity"]] = None,
target_column_name: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -1970,7 +2093,7 @@ class NCrossValidations(_serialization.Model):
_subtype_map = {"mode": {"Auto": "AutoNCrossValidations", "Custom": "CustomNCrossValidations"}}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: Optional[str] = None
@@ -1994,7 +2117,7 @@ class AutoNCrossValidations(NCrossValidations):
"mode": {"key": "mode", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: str = "Auto"
@@ -2014,7 +2137,9 @@ class AutoPauseProperties(_serialization.Model):
"enabled": {"key": "enabled", "type": "bool"},
}
- def __init__(self, *, delay_in_minutes: Optional[int] = None, enabled: Optional[bool] = None, **kwargs):
+ def __init__(
+ self, *, delay_in_minutes: Optional[int] = None, enabled: Optional[bool] = None, **kwargs: Any
+ ) -> None:
"""
:keyword delay_in_minutes:
:paramtype delay_in_minutes: int
@@ -2049,8 +2174,8 @@ def __init__(
min_node_count: Optional[int] = None,
enabled: Optional[bool] = None,
max_node_count: Optional[int] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword min_node_count:
:paramtype min_node_count: int
@@ -2087,7 +2212,7 @@ class Seasonality(_serialization.Model):
_subtype_map = {"mode": {"Auto": "AutoSeasonality", "Custom": "CustomSeasonality"}}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: Optional[str] = None
@@ -2110,7 +2235,7 @@ class AutoSeasonality(Seasonality):
"mode": {"key": "mode", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: str = "Auto"
@@ -2139,7 +2264,7 @@ class TargetLags(_serialization.Model):
_subtype_map = {"mode": {"Auto": "AutoTargetLags", "Custom": "CustomTargetLags"}}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: Optional[str] = None
@@ -2163,7 +2288,7 @@ class AutoTargetLags(TargetLags):
"mode": {"key": "mode", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: str = "Auto"
@@ -2192,7 +2317,7 @@ class TargetRollingWindowSize(_serialization.Model):
_subtype_map = {"mode": {"Auto": "AutoTargetRollingWindowSize", "Custom": "CustomTargetRollingWindowSize"}}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: Optional[str] = None
@@ -2216,7 +2341,7 @@ class AutoTargetRollingWindowSize(TargetRollingWindowSize):
"mode": {"key": "mode", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.mode: str = "Auto"
@@ -2279,8 +2404,8 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -2365,8 +2490,8 @@ def __init__(
endpoint: Optional[str] = None,
protocol: Optional[str] = None,
service_data_access_auth_identity: Optional[Union[str, "_models.ServiceDataAccessAuthIdentity"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -2433,7 +2558,7 @@ class AzureDataLakeGen1Datastore(DatastoreProperties):
"credentials": {"required": True},
"datastore_type": {"required": True},
"is_default": {"readonly": True},
- "store_name": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "store_name": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -2456,8 +2581,8 @@ def __init__(
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
service_data_access_auth_identity: Optional[Union[str, "_models.ServiceDataAccessAuthIdentity"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -2521,8 +2646,8 @@ class AzureDataLakeGen2Datastore(DatastoreProperties): # pylint: disable=too-ma
"credentials": {"required": True},
"datastore_type": {"required": True},
"is_default": {"readonly": True},
- "account_name": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
- "filesystem": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "account_name": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
+ "filesystem": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -2551,8 +2676,8 @@ def __init__(
endpoint: Optional[str] = None,
protocol: Optional[str] = None,
service_data_access_auth_identity: Optional[Union[str, "_models.ServiceDataAccessAuthIdentity"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -2626,8 +2751,8 @@ class AzureFileDatastore(DatastoreProperties): # pylint: disable=too-many-insta
"credentials": {"required": True},
"datastore_type": {"required": True},
"is_default": {"readonly": True},
- "account_name": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
- "file_share_name": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "account_name": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
+ "file_share_name": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -2656,8 +2781,8 @@ def __init__(
endpoint: Optional[str] = None,
protocol: Optional[str] = None,
service_data_access_auth_identity: Optional[Union[str, "_models.ServiceDataAccessAuthIdentity"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -2727,7 +2852,7 @@ class EarlyTerminationPolicy(_serialization.Model):
}
}
- def __init__(self, *, delay_evaluation: int = 0, evaluation_interval: int = 0, **kwargs):
+ def __init__(self, *, delay_evaluation: int = 0, evaluation_interval: int = 0, **kwargs: Any) -> None:
"""
:keyword delay_evaluation: Number of intervals by which to delay the first evaluation.
:paramtype delay_evaluation: int
@@ -2741,7 +2866,8 @@ def __init__(self, *, delay_evaluation: int = 0, evaluation_interval: int = 0, *
class BanditPolicy(EarlyTerminationPolicy):
- """Defines an early termination policy based on slack criteria, and a frequency and delay interval for evaluation.
+ """Defines an early termination policy based on slack criteria, and a frequency and delay interval
+ for evaluation.
All required parameters must be populated in order to send to Azure.
@@ -2778,8 +2904,8 @@ def __init__(
evaluation_interval: int = 0,
slack_amount: float = 0,
slack_factor: float = 0,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword delay_evaluation: Number of intervals by which to delay the first evaluation.
:paramtype delay_evaluation: int
@@ -2828,7 +2954,7 @@ class Resource(_serialization.Model):
"system_data": {"key": "systemData", "type": "SystemData"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.id = None
@@ -2838,7 +2964,8 @@ def __init__(self, **kwargs):
class TrackedResource(Resource):
- """The resource model definition for an Azure Resource Manager tracked top level resource which has 'tags' and a 'location'.
+ """The resource model definition for an Azure Resource Manager tracked top level resource which
+ has 'tags' and a 'location'.
Variables are only populated by the server, and will be ignored when sending a request.
@@ -2878,7 +3005,7 @@ class TrackedResource(Resource):
"location": {"key": "location", "type": "str"},
}
- def __init__(self, *, location: str, tags: Optional[Dict[str, str]] = None, **kwargs):
+ def __init__(self, *, location: str, tags: Optional[Dict[str, str]] = None, **kwargs: Any) -> None:
"""
:keyword tags: Resource tags.
:paramtype tags: dict[str, str]
@@ -2954,8 +3081,8 @@ def __init__(
identity: Optional["_models.ManagedServiceIdentity"] = None,
kind: Optional[str] = None,
sku: Optional["_models.Sku"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword tags: Resource tags.
:paramtype tags: dict[str, str]
@@ -3010,8 +3137,8 @@ def __init__(
environment_id: Optional[str] = None,
environment_variables: Optional[Dict[str, str]] = None,
properties: Optional[Dict[str, str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword code_configuration: Code configuration for the endpoint deployment.
:paramtype code_configuration: ~azure.mgmt.machinelearningservices.models.CodeConfiguration
@@ -3127,8 +3254,8 @@ def __init__(
output_file_name: str = "predictions.csv",
resources: Optional["_models.DeploymentResourceConfiguration"] = None,
retry_settings: Optional["_models.BatchRetrySettings"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword code_configuration: Code configuration for the endpoint deployment.
:paramtype code_configuration: ~azure.mgmt.machinelearningservices.models.CodeConfiguration
@@ -3211,8 +3338,8 @@ class BatchDeploymentTrackedResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.BatchDeployment"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.BatchDeployment"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of BatchDeployment objects. If null, there are no
additional pages.
@@ -3289,8 +3416,8 @@ def __init__(
identity: Optional["_models.ManagedServiceIdentity"] = None,
kind: Optional[str] = None,
sku: Optional["_models.Sku"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword tags: Resource tags.
:paramtype tags: dict[str, str]
@@ -3325,7 +3452,7 @@ class BatchEndpointDefaults(_serialization.Model):
"deployment_name": {"key": "deploymentName", "type": "str"},
}
- def __init__(self, *, deployment_name: Optional[str] = None, **kwargs):
+ def __init__(self, *, deployment_name: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword deployment_name: Name of the deployment that will be default for the endpoint.
This deployment will end up getting 100% traffic when the endpoint scoring URL is invoked.
@@ -3382,8 +3509,8 @@ def __init__(
description: Optional[str] = None,
keys: Optional["_models.EndpointAuthKeys"] = None,
properties: Optional[Dict[str, str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword auth_mode: [Required] Use 'Key' for key based authentication and 'AMLToken' for Azure
Machine Learning token-based authentication. 'Key' doesn't expire but 'AMLToken' does.
@@ -3464,8 +3591,8 @@ def __init__(
keys: Optional["_models.EndpointAuthKeys"] = None,
properties: Optional[Dict[str, str]] = None,
defaults: Optional["_models.BatchEndpointDefaults"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword auth_mode: [Required] Use 'Key' for key based authentication and 'AMLToken' for Azure
Machine Learning token-based authentication. 'Key' doesn't expire but 'AMLToken' does.
@@ -3503,8 +3630,8 @@ class BatchEndpointTrackedResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.BatchEndpoint"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.BatchEndpoint"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of BatchEndpoint objects. If null, there are no
additional pages.
@@ -3531,7 +3658,7 @@ class BatchRetrySettings(_serialization.Model):
"timeout": {"key": "timeout", "type": "duration"},
}
- def __init__(self, *, max_retries: int = 3, timeout: datetime.timedelta = "PT30S", **kwargs):
+ def __init__(self, *, max_retries: int = 3, timeout: datetime.timedelta = "PT30S", **kwargs: Any) -> None:
"""
:keyword max_retries: Maximum retry count for a mini-batch.
:paramtype max_retries: int
@@ -3547,16 +3674,16 @@ class SamplingAlgorithm(_serialization.Model):
"""The Sampling Algorithm used to generate hyperparameter values, along with properties to
configure the algorithm.
- You probably want to use the sub-classes and not this class directly. Known sub-classes are:
- BayesianSamplingAlgorithm, GridSamplingAlgorithm, RandomSamplingAlgorithm
+ You probably want to use the sub-classes and not this class directly. Known sub-classes are:
+ BayesianSamplingAlgorithm, GridSamplingAlgorithm, RandomSamplingAlgorithm
- All required parameters must be populated in order to send to Azure.
+ All required parameters must be populated in order to send to Azure.
- :ivar sampling_algorithm_type: [Required] The algorithm used for generating hyperparameter
- values, along with configuration properties. Required. Known values are: "Grid", "Random", and
- "Bayesian".
- :vartype sampling_algorithm_type: str or
- ~azure.mgmt.machinelearningservices.models.SamplingAlgorithmType
+ :ivar sampling_algorithm_type: [Required] The algorithm used for generating hyperparameter
+ values, along with configuration properties. Required. Known values are: "Grid", "Random", and
+ "Bayesian".
+ :vartype sampling_algorithm_type: str or
+ ~azure.mgmt.machinelearningservices.models.SamplingAlgorithmType
"""
_validation = {
@@ -3575,7 +3702,7 @@ class SamplingAlgorithm(_serialization.Model):
}
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.sampling_algorithm_type: Optional[str] = None
@@ -3601,12 +3728,92 @@ class BayesianSamplingAlgorithm(SamplingAlgorithm):
"sampling_algorithm_type": {"key": "samplingAlgorithmType", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.sampling_algorithm_type: str = "Bayesian"
+class BindOptions(_serialization.Model):
+ """Describes the bind options for the container.
+
+ :ivar propagation: Type of Bind Option.
+ :vartype propagation: str
+ :ivar create_host_path: Indicate whether to create host path.
+ :vartype create_host_path: bool
+ :ivar selinux: Mention the selinux options.
+ :vartype selinux: str
+ """
+
+ _attribute_map = {
+ "propagation": {"key": "propagation", "type": "str"},
+ "create_host_path": {"key": "createHostPath", "type": "bool"},
+ "selinux": {"key": "selinux", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ propagation: Optional[str] = None,
+ create_host_path: Optional[bool] = None,
+ selinux: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword propagation: Type of Bind Option.
+ :paramtype propagation: str
+ :keyword create_host_path: Indicate whether to create host path.
+ :paramtype create_host_path: bool
+ :keyword selinux: Mention the selinux options.
+ :paramtype selinux: str
+ """
+ super().__init__(**kwargs)
+ self.propagation = propagation
+ self.create_host_path = create_host_path
+ self.selinux = selinux
+
+
+class BlobReferenceForConsumptionDto(_serialization.Model):
+ """BlobReferenceForConsumptionDto.
+
+ :ivar blob_uri: Blob URI path for client to upload data.
+ Example: https://blob.windows.core.net/Container/Path.
+ :vartype blob_uri: str
+ :ivar credential: Credential info to access storage account.
+ :vartype credential: ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialDto
+ :ivar storage_account_arm_id: Arm ID of the storage account to use.
+ :vartype storage_account_arm_id: str
+ """
+
+ _attribute_map = {
+ "blob_uri": {"key": "blobUri", "type": "str"},
+ "credential": {"key": "credential", "type": "PendingUploadCredentialDto"},
+ "storage_account_arm_id": {"key": "storageAccountArmId", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ blob_uri: Optional[str] = None,
+ credential: Optional["_models.PendingUploadCredentialDto"] = None,
+ storage_account_arm_id: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword blob_uri: Blob URI path for client to upload data.
+ Example: https://blob.windows.core.net/Container/Path.
+ :paramtype blob_uri: str
+ :keyword credential: Credential info to access storage account.
+ :paramtype credential: ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialDto
+ :keyword storage_account_arm_id: Arm ID of the storage account to use.
+ :paramtype storage_account_arm_id: str
+ """
+ super().__init__(**kwargs)
+ self.blob_uri = blob_uri
+ self.credential = credential
+ self.storage_account_arm_id = storage_account_arm_id
+
+
class BuildContext(_serialization.Model):
"""Configuration settings for Docker build context.
@@ -3632,7 +3839,7 @@ class BuildContext(_serialization.Model):
"""
_validation = {
- "context_uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "context_uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -3640,7 +3847,7 @@ class BuildContext(_serialization.Model):
"dockerfile_path": {"key": "dockerfilePath", "type": "str"},
}
- def __init__(self, *, context_uri: str, dockerfile_path: str = "Dockerfile", **kwargs):
+ def __init__(self, *, context_uri: str, dockerfile_path: str = "Dockerfile", **kwargs: Any) -> None:
"""
:keyword context_uri: [Required] URI of the Docker build context used to build the image.
Supports blob URIs on environment creation and may return blob or Git URIs.
@@ -3692,7 +3899,7 @@ class CertificateDatastoreCredentials(DatastoreCredentials):
"client_id": {"required": True},
"secrets": {"required": True},
"tenant_id": {"required": True},
- "thumbprint": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "thumbprint": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -3714,8 +3921,8 @@ def __init__(
thumbprint: str,
authority_url: Optional[str] = None,
resource_url: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword authority_url: Authority URL used for authentication.
:paramtype authority_url: str
@@ -3763,7 +3970,7 @@ class CertificateDatastoreSecrets(DatastoreSecrets):
"certificate": {"key": "certificate", "type": "str"},
}
- def __init__(self, *, certificate: Optional[str] = None, **kwargs):
+ def __init__(self, *, certificate: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword certificate: Service principal certificate.
:paramtype certificate: str
@@ -3774,7 +3981,8 @@ def __init__(self, *, certificate: Optional[str] = None, **kwargs):
class TableVertical(_serialization.Model):
- """Abstract class for AutoML tasks that use table dataset as input - such as Classification/Regression/Forecasting.
+ """Abstract class for AutoML tasks that use table dataset as input - such as
+ Classification/Regression/Forecasting.
:ivar cv_split_column_names: Columns to use for CVSplit data.
:vartype cv_split_column_names: list[str]
@@ -3829,8 +4037,8 @@ def __init__(
validation_data: Optional["_models.MLTableJobInput"] = None,
validation_data_size: Optional[float] = None,
weight_column_name: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword cv_split_column_names: Columns to use for CVSplit data.
:paramtype cv_split_column_names: list[str]
@@ -3972,8 +4180,8 @@ def __init__(
positive_label: Optional[str] = None,
primary_metric: Optional[Union[str, "_models.ClassificationPrimaryMetrics"]] = None,
training_settings: Optional["_models.ClassificationTrainingSettings"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -4097,8 +4305,8 @@ def __init__(
enable_vote_ensemble: bool = True,
ensemble_model_download_timeout: datetime.timedelta = "PT5M",
stack_ensemble_settings: Optional["_models.StackEnsembleSettings"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword enable_dnn_training: Enable recommendation of DNN models.
:paramtype enable_dnn_training: bool
@@ -4180,8 +4388,8 @@ def __init__(
stack_ensemble_settings: Optional["_models.StackEnsembleSettings"] = None,
allowed_training_algorithms: Optional[List[Union[str, "_models.ClassificationModels"]]] = None,
blocked_training_algorithms: Optional[List[Union[str, "_models.ClassificationModels"]]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword enable_dnn_training: Enable recommendation of DNN models.
:paramtype enable_dnn_training: bool
@@ -4232,7 +4440,7 @@ class ClusterUpdateParameters(_serialization.Model):
"properties": {"key": "properties.properties", "type": "ScaleSettingsInformation"},
}
- def __init__(self, *, properties: Optional["_models.ScaleSettingsInformation"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.ScaleSettingsInformation"] = None, **kwargs: Any) -> None:
"""
:keyword properties: Properties of ClusterUpdate.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.ScaleSettingsInformation
@@ -4261,7 +4469,7 @@ class CodeConfiguration(_serialization.Model):
"scoring_script": {"key": "scoringScript", "type": "str"},
}
- def __init__(self, *, scoring_script: str, code_id: Optional[str] = None, **kwargs):
+ def __init__(self, *, scoring_script: str, code_id: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword code_id: ARM resource ID of the code asset.
:paramtype code_id: str
@@ -4311,7 +4519,7 @@ class CodeContainer(Resource):
"properties": {"key": "properties", "type": "CodeContainerProperties"},
}
- def __init__(self, *, properties: "_models.CodeContainerProperties", **kwargs):
+ def __init__(self, *, properties: "_models.CodeContainerProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.CodeContainerProperties
@@ -4337,11 +4545,16 @@ class CodeContainerProperties(AssetContainer):
:vartype latest_version: str
:ivar next_version: The next auto incremental version.
:vartype next_version: str
+ :ivar provisioning_state: Provisioning state for the code container. Known values are:
+ "Succeeded", "Failed", "Canceled", "Creating", "Updating", and "Deleting".
+ :vartype provisioning_state: str or
+ ~azure.mgmt.machinelearningservices.models.AssetProvisioningState
"""
_validation = {
"latest_version": {"readonly": True},
"next_version": {"readonly": True},
+ "provisioning_state": {"readonly": True},
}
_attribute_map = {
@@ -4351,6 +4564,7 @@ class CodeContainerProperties(AssetContainer):
"is_archived": {"key": "isArchived", "type": "bool"},
"latest_version": {"key": "latestVersion", "type": "str"},
"next_version": {"key": "nextVersion", "type": "str"},
+ "provisioning_state": {"key": "provisioningState", "type": "str"},
}
def __init__(
@@ -4360,8 +4574,8 @@ def __init__(
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -4373,6 +4587,7 @@ def __init__(
:paramtype is_archived: bool
"""
super().__init__(description=description, properties=properties, tags=tags, is_archived=is_archived, **kwargs)
+ self.provisioning_state = None
class CodeContainerResourceArmPaginatedResult(_serialization.Model):
@@ -4391,8 +4606,8 @@ class CodeContainerResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.CodeContainer"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.CodeContainer"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of CodeContainer objects. If null, there are no
additional pages.
@@ -4443,7 +4658,7 @@ class CodeVersion(Resource):
"properties": {"key": "properties", "type": "CodeVersionProperties"},
}
- def __init__(self, *, properties: "_models.CodeVersionProperties", **kwargs):
+ def __init__(self, *, properties: "_models.CodeVersionProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.CodeVersionProperties
@@ -4455,6 +4670,8 @@ def __init__(self, *, properties: "_models.CodeVersionProperties", **kwargs):
class CodeVersionProperties(AssetBase):
"""Code asset version details.
+ Variables are only populated by the server, and will be ignored when sending a request.
+
:ivar description: The asset description text.
:vartype description: str
:ivar properties: The asset property dictionary.
@@ -4467,8 +4684,16 @@ class CodeVersionProperties(AssetBase):
:vartype is_archived: bool
:ivar code_uri: Uri where code is located.
:vartype code_uri: str
+ :ivar provisioning_state: Provisioning state for the code version. Known values are:
+ "Succeeded", "Failed", "Canceled", "Creating", "Updating", and "Deleting".
+ :vartype provisioning_state: str or
+ ~azure.mgmt.machinelearningservices.models.AssetProvisioningState
"""
+ _validation = {
+ "provisioning_state": {"readonly": True},
+ }
+
_attribute_map = {
"description": {"key": "description", "type": "str"},
"properties": {"key": "properties", "type": "{str}"},
@@ -4476,6 +4701,7 @@ class CodeVersionProperties(AssetBase):
"is_anonymous": {"key": "isAnonymous", "type": "bool"},
"is_archived": {"key": "isArchived", "type": "bool"},
"code_uri": {"key": "codeUri", "type": "str"},
+ "provisioning_state": {"key": "provisioningState", "type": "str"},
}
def __init__(
@@ -4487,8 +4713,8 @@ def __init__(
is_anonymous: bool = False,
is_archived: bool = False,
code_uri: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -4512,6 +4738,7 @@ def __init__(
**kwargs
)
self.code_uri = code_uri
+ self.provisioning_state = None
class CodeVersionResourceArmPaginatedResult(_serialization.Model):
@@ -4530,8 +4757,8 @@ class CodeVersionResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.CodeVersion"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.CodeVersion"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of CodeVersion objects. If null, there are no
additional pages.
@@ -4559,7 +4786,7 @@ class ColumnTransformer(_serialization.Model):
"parameters": {"key": "parameters", "type": "object"},
}
- def __init__(self, *, fields: Optional[List[str]] = None, parameters: Optional[JSON] = None, **kwargs):
+ def __init__(self, *, fields: Optional[List[str]] = None, parameters: Optional[JSON] = None, **kwargs: Any) -> None:
"""
:keyword fields: Fields to apply transformer logic on.
:paramtype fields: list[str]
@@ -4639,7 +4866,7 @@ class CommandJob(JobBaseProperties): # pylint: disable=too-many-instance-attrib
"job_type": {"required": True},
"status": {"readonly": True},
"command": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
- "environment_id": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "environment_id": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
"parameters": {"readonly": True},
}
@@ -4690,8 +4917,8 @@ def __init__(
limits: Optional["_models.CommandJobLimits"] = None,
outputs: Optional[Dict[str, "_models.JobOutput"]] = None,
resources: Optional["_models.JobResourceConfiguration"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -4792,7 +5019,7 @@ class JobLimits(_serialization.Model):
_subtype_map = {"job_limits_type": {"Command": "CommandJobLimits", "Sweep": "SweepJobLimits"}}
- def __init__(self, *, timeout: Optional[datetime.timedelta] = None, **kwargs):
+ def __init__(self, *, timeout: Optional[datetime.timedelta] = None, **kwargs: Any) -> None:
"""
:keyword timeout: The max run duration in ISO 8601 format, after which the job will be
cancelled. Only supports duration with precision as low as Seconds.
@@ -4825,7 +5052,7 @@ class CommandJobLimits(JobLimits):
"timeout": {"key": "timeout", "type": "duration"},
}
- def __init__(self, *, timeout: Optional[datetime.timedelta] = None, **kwargs):
+ def __init__(self, *, timeout: Optional[datetime.timedelta] = None, **kwargs: Any) -> None:
"""
:keyword timeout: The max run duration in ISO 8601 format, after which the job will be
cancelled. Only supports duration with precision as low as Seconds.
@@ -4873,7 +5100,7 @@ class ComponentContainer(Resource):
"properties": {"key": "properties", "type": "ComponentContainerProperties"},
}
- def __init__(self, *, properties: "_models.ComponentContainerProperties", **kwargs):
+ def __init__(self, *, properties: "_models.ComponentContainerProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.ComponentContainerProperties
@@ -4888,27 +5115,34 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
- Variables are only populated by the server, and will be ignored when sending a request.
+ Variables are only populated by the server, and will be ignored when sending a request.
- :ivar description: The asset description text.
- :vartype description: str
- :ivar properties: The asset property dictionary.
- :vartype properties: dict[str, str]
- :ivar tags: Tag dictionary. Tags can be added, removed, and updated.
- :vartype tags: dict[str, str]
- :ivar is_archived: Is the asset archived?.
- :vartype is_archived: bool
- :ivar latest_version: The latest version inside this container.
- :vartype latest_version: str
- :ivar next_version: The next auto incremental version.
- :vartype next_version: str
+ :ivar description: The asset description text.
+ :vartype description: str
+ :ivar properties: The asset property dictionary.
+ :vartype properties: dict[str, str]
+ :ivar tags: Tag dictionary. Tags can be added, removed, and updated.
+ :vartype tags: dict[str, str]
+ :ivar is_archived: Is the asset archived?.
+ :vartype is_archived: bool
+ :ivar latest_version: The latest version inside this container.
+ :vartype latest_version: str
+ :ivar next_version: The next auto incremental version.
+ :vartype next_version: str
+ :ivar provisioning_state: Provisioning state for the component container. Known values are:
+ "Succeeded", "Failed", "Canceled", "Creating", "Updating", and "Deleting".
+ :vartype provisioning_state: str or
+ ~azure.mgmt.machinelearningservices.models.AssetProvisioningState
"""
_validation = {
"latest_version": {"readonly": True},
"next_version": {"readonly": True},
+ "provisioning_state": {"readonly": True},
}
_attribute_map = {
@@ -4918,6 +5152,7 @@ class ComponentContainerProperties(AssetContainer):
"is_archived": {"key": "isArchived", "type": "bool"},
"latest_version": {"key": "latestVersion", "type": "str"},
"next_version": {"key": "nextVersion", "type": "str"},
+ "provisioning_state": {"key": "provisioningState", "type": "str"},
}
def __init__(
@@ -4927,8 +5162,8 @@ def __init__(
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -4940,6 +5175,7 @@ def __init__(
:paramtype is_archived: bool
"""
super().__init__(description=description, properties=properties, tags=tags, is_archived=is_archived, **kwargs)
+ self.provisioning_state = None
class ComponentContainerResourceArmPaginatedResult(_serialization.Model):
@@ -4958,8 +5194,12 @@ class ComponentContainerResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.ComponentContainer"]] = None, **kwargs
- ):
+ self,
+ *,
+ next_link: Optional[str] = None,
+ value: Optional[List["_models.ComponentContainer"]] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of ComponentContainer objects. If null, there are
no additional pages.
@@ -5010,7 +5250,7 @@ class ComponentVersion(Resource):
"properties": {"key": "properties", "type": "ComponentVersionProperties"},
}
- def __init__(self, *, properties: "_models.ComponentVersionProperties", **kwargs):
+ def __init__(self, *, properties: "_models.ComponentVersionProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.ComponentVersionProperties
@@ -5022,6 +5262,8 @@ def __init__(self, *, properties: "_models.ComponentVersionProperties", **kwargs
class ComponentVersionProperties(AssetBase):
"""Definition of a component version: defines resources that span component types.
+ Variables are only populated by the server, and will be ignored when sending a request.
+
:ivar description: The asset description text.
:vartype description: str
:ivar properties: The asset property dictionary.
@@ -5041,8 +5283,16 @@ class ComponentVersionProperties(AssetBase):
href="https://docs.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-command"
/>.
:vartype component_spec: JSON
+ :ivar provisioning_state: Provisioning state for the component version. Known values are:
+ "Succeeded", "Failed", "Canceled", "Creating", "Updating", and "Deleting".
+ :vartype provisioning_state: str or
+ ~azure.mgmt.machinelearningservices.models.AssetProvisioningState
"""
+ _validation = {
+ "provisioning_state": {"readonly": True},
+ }
+
_attribute_map = {
"description": {"key": "description", "type": "str"},
"properties": {"key": "properties", "type": "{str}"},
@@ -5050,6 +5300,7 @@ class ComponentVersionProperties(AssetBase):
"is_anonymous": {"key": "isAnonymous", "type": "bool"},
"is_archived": {"key": "isArchived", "type": "bool"},
"component_spec": {"key": "componentSpec", "type": "object"},
+ "provisioning_state": {"key": "provisioningState", "type": "str"},
}
def __init__(
@@ -5061,8 +5312,8 @@ def __init__(
is_anonymous: bool = False,
is_archived: bool = False,
component_spec: Optional[JSON] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -5093,6 +5344,7 @@ def __init__(
**kwargs
)
self.component_spec = component_spec
+ self.provisioning_state = None
class ComponentVersionResourceArmPaginatedResult(_serialization.Model):
@@ -5111,8 +5363,12 @@ class ComponentVersionResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.ComponentVersion"]] = None, **kwargs
- ):
+ self,
+ *,
+ next_link: Optional[str] = None,
+ value: Optional[List["_models.ComponentVersion"]] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of ComponentVersion objects. If null, there are
no additional pages.
@@ -5136,7 +5392,7 @@ class ComputeInstanceSchema(_serialization.Model):
"properties": {"key": "properties", "type": "ComputeInstanceProperties"},
}
- def __init__(self, *, properties: Optional["_models.ComputeInstanceProperties"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.ComputeInstanceProperties"] = None, **kwargs: Any) -> None:
"""
:keyword properties: Properties of ComputeInstance.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.ComputeInstanceProperties
@@ -5214,8 +5470,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties: Properties of ComputeInstance.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.ComputeInstanceProperties
@@ -5264,7 +5520,9 @@ class ComputeInstanceApplication(_serialization.Model):
"endpoint_uri": {"key": "endpointUri", "type": "str"},
}
- def __init__(self, *, display_name: Optional[str] = None, endpoint_uri: Optional[str] = None, **kwargs):
+ def __init__(
+ self, *, display_name: Optional[str] = None, endpoint_uri: Optional[str] = None, **kwargs: Any
+ ) -> None:
"""
:keyword display_name: Name of the ComputeInstance application.
:paramtype display_name: str
@@ -5298,7 +5556,7 @@ class ComputeInstanceConnectivityEndpoints(_serialization.Model):
"private_ip_address": {"key": "privateIpAddress", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.public_ip_address = None
@@ -5345,8 +5603,8 @@ def __init__(
gpu: Optional[str] = None,
network: Optional[Union[str, "_models.Network"]] = None,
environment: Optional["_models.ComputeInstanceEnvironmentInfo"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword name: Name of the ComputeInstance container.
:paramtype name: str
@@ -5394,7 +5652,7 @@ class ComputeInstanceCreatedBy(_serialization.Model):
"user_id": {"key": "userId", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.user_name = None
@@ -5433,8 +5691,8 @@ def __init__(
disk_size_gb: Optional[int] = None,
lun: Optional[int] = None,
storage_account_type: Union[str, "_models.StorageAccountType"] = "Standard_LRS",
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword caching: Caching type of Data Disk. Known values are: "None", "ReadOnly", and
"ReadWrite".
@@ -5504,8 +5762,8 @@ def __init__(
mount_state: Optional[Union[str, "_models.MountState"]] = None,
mounted_on: Optional[datetime.datetime] = None,
error: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword source: Source of the ComputeInstance data mount.
:paramtype source: str
@@ -5553,7 +5811,7 @@ class ComputeInstanceEnvironmentInfo(_serialization.Model):
"version": {"key": "version", "type": "str"},
}
- def __init__(self, *, name: Optional[str] = None, version: Optional[str] = None, **kwargs):
+ def __init__(self, *, name: Optional[str] = None, version: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword name: name of environment.
:paramtype name: str
@@ -5596,8 +5854,8 @@ def __init__(
operation_time: Optional[datetime.datetime] = None,
operation_status: Optional[Union[str, "_models.OperationStatus"]] = None,
operation_trigger: Optional[Union[str, "_models.OperationTrigger"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword operation_name: Name of the last operation. Known values are: "Create", "Start",
"Stop", "Restart", "Reimage", and "Delete".
@@ -5637,6 +5895,11 @@ class ComputeInstanceProperties(_serialization.Model): # pylint: disable=too-ma
~azure.mgmt.machinelearningservices.models.ApplicationSharingPolicy
:ivar ssh_settings: Specifies policy and settings for SSH access.
:vartype ssh_settings: ~azure.mgmt.machinelearningservices.models.ComputeInstanceSshSettings
+ :ivar custom_services: List of Custom Services added to the compute.
+ :vartype custom_services: list[~azure.mgmt.machinelearningservices.models.CustomService]
+ :ivar os_image_metadata: Returns metadata about the operating system image for this compute
+ instance.
+ :vartype os_image_metadata: ~azure.mgmt.machinelearningservices.models.ImageMetadata
:ivar connectivity_endpoints: Describes all connectivity endpoints available for this
ComputeInstance.
:vartype connectivity_endpoints:
@@ -5684,13 +5947,13 @@ class ComputeInstanceProperties(_serialization.Model): # pylint: disable=too-ma
"""
_validation = {
+ "os_image_metadata": {"readonly": True},
"connectivity_endpoints": {"readonly": True},
"applications": {"readonly": True},
"created_by": {"readonly": True},
"errors": {"readonly": True},
"state": {"readonly": True},
"last_operation": {"readonly": True},
- "schedules": {"readonly": True},
"containers": {"readonly": True},
"data_disks": {"readonly": True},
"data_mounts": {"readonly": True},
@@ -5702,6 +5965,8 @@ class ComputeInstanceProperties(_serialization.Model): # pylint: disable=too-ma
"subnet": {"key": "subnet", "type": "ResourceId"},
"application_sharing_policy": {"key": "applicationSharingPolicy", "type": "str"},
"ssh_settings": {"key": "sshSettings", "type": "ComputeInstanceSshSettings"},
+ "custom_services": {"key": "customServices", "type": "[CustomService]"},
+ "os_image_metadata": {"key": "osImageMetadata", "type": "ImageMetadata"},
"connectivity_endpoints": {"key": "connectivityEndpoints", "type": "ComputeInstanceConnectivityEndpoints"},
"applications": {"key": "applications", "type": "[ComputeInstanceApplication]"},
"created_by": {"key": "createdBy", "type": "ComputeInstanceCreatedBy"},
@@ -5729,12 +5994,14 @@ def __init__(
subnet: Optional["_models.ResourceId"] = None,
application_sharing_policy: Union[str, "_models.ApplicationSharingPolicy"] = "Shared",
ssh_settings: Optional["_models.ComputeInstanceSshSettings"] = None,
+ custom_services: Optional[List["_models.CustomService"]] = None,
compute_instance_authorization_type: Union[str, "_models.ComputeInstanceAuthorizationType"] = "personal",
personal_compute_instance_settings: Optional["_models.PersonalComputeInstanceSettings"] = None,
setup_scripts: Optional["_models.SetupScripts"] = None,
+ schedules: Optional["_models.ComputeSchedules"] = None,
enable_node_public_ip: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword vm_size: Virtual Machine Size.
:paramtype vm_size: str
@@ -5748,6 +6015,8 @@ def __init__(
~azure.mgmt.machinelearningservices.models.ApplicationSharingPolicy
:keyword ssh_settings: Specifies policy and settings for SSH access.
:paramtype ssh_settings: ~azure.mgmt.machinelearningservices.models.ComputeInstanceSshSettings
+ :keyword custom_services: List of Custom Services added to the compute.
+ :paramtype custom_services: list[~azure.mgmt.machinelearningservices.models.CustomService]
:keyword compute_instance_authorization_type: The Compute Instance Authorization type.
Available values are personal (default). "personal"
:paramtype compute_instance_authorization_type: str or
@@ -5757,6 +6026,8 @@ def __init__(
~azure.mgmt.machinelearningservices.models.PersonalComputeInstanceSettings
:keyword setup_scripts: Details of customized scripts to execute for setting up the cluster.
:paramtype setup_scripts: ~azure.mgmt.machinelearningservices.models.SetupScripts
+ :keyword schedules: The list of schedules to be applied on the computes.
+ :paramtype schedules: ~azure.mgmt.machinelearningservices.models.ComputeSchedules
:keyword enable_node_public_ip: Enable or disable node public IP address provisioning. Possible
values are: Possible values are: true - Indicates that the compute nodes will have public IPs
provisioned. false - Indicates that the compute nodes will have a private endpoint and no
@@ -5768,6 +6039,8 @@ def __init__(
self.subnet = subnet
self.application_sharing_policy = application_sharing_policy
self.ssh_settings = ssh_settings
+ self.custom_services = custom_services
+ self.os_image_metadata = None
self.connectivity_endpoints = None
self.applications = None
self.created_by = None
@@ -5777,7 +6050,7 @@ def __init__(
self.personal_compute_instance_settings = personal_compute_instance_settings
self.setup_scripts = setup_scripts
self.last_operation = None
- self.schedules = None
+ self.schedules = schedules
self.enable_node_public_ip = enable_node_public_ip
self.containers = None
self.data_disks = None
@@ -5821,8 +6094,8 @@ def __init__(
*,
ssh_public_access: Union[str, "_models.SshPublicAccess"] = "Disabled",
admin_public_key: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword ssh_public_access: State of the public SSH port. Possible values are: Disabled -
Indicates that the public ssh port is closed on this instance. Enabled - Indicates that the
@@ -5851,7 +6124,7 @@ class ComputeInstanceVersion(_serialization.Model):
"runtime": {"key": "runtime", "type": "str"},
}
- def __init__(self, *, runtime: Optional[str] = None, **kwargs):
+ def __init__(self, *, runtime: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword runtime: Runtime of compute instance.
:paramtype runtime: str
@@ -5871,7 +6144,7 @@ class ComputeResourceSchema(_serialization.Model):
"properties": {"key": "properties", "type": "Compute"},
}
- def __init__(self, *, properties: Optional["_models.Compute"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.Compute"] = None, **kwargs: Any) -> None:
"""
:keyword properties: Compute properties.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.Compute
@@ -5935,8 +6208,8 @@ def __init__(
location: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
sku: Optional["_models.Sku"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties: Compute properties.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.Compute
@@ -5973,7 +6246,9 @@ class ComputeSchedules(_serialization.Model):
"compute_start_stop": {"key": "computeStartStop", "type": "[ComputeStartStopSchedule]"},
}
- def __init__(self, *, compute_start_stop: Optional[List["_models.ComputeStartStopSchedule"]] = None, **kwargs):
+ def __init__(
+ self, *, compute_start_stop: Optional[List["_models.ComputeStartStopSchedule"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword compute_start_stop: The list of compute start stop schedules to be applied.
:paramtype compute_start_stop:
@@ -6002,9 +6277,9 @@ class ComputeStartStopSchedule(_serialization.Model):
"Cron".
:vartype trigger_type: str or ~azure.mgmt.machinelearningservices.models.TriggerType
:ivar recurrence: Required if triggerType is Recurrence.
- :vartype recurrence: ~azure.mgmt.machinelearningservices.models.RecurrenceTrigger
+ :vartype recurrence: ~azure.mgmt.machinelearningservices.models.Recurrence
:ivar cron: Required if triggerType is Cron.
- :vartype cron: ~azure.mgmt.machinelearningservices.models.CronTrigger
+ :vartype cron: ~azure.mgmt.machinelearningservices.models.Cron
:ivar schedule: [Deprecated] Not used any more.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ScheduleBase
"""
@@ -6020,8 +6295,8 @@ class ComputeStartStopSchedule(_serialization.Model):
"status": {"key": "status", "type": "str"},
"action": {"key": "action", "type": "str"},
"trigger_type": {"key": "triggerType", "type": "str"},
- "recurrence": {"key": "recurrence", "type": "RecurrenceTrigger"},
- "cron": {"key": "cron", "type": "CronTrigger"},
+ "recurrence": {"key": "recurrence", "type": "Recurrence"},
+ "cron": {"key": "cron", "type": "Cron"},
"schedule": {"key": "schedule", "type": "ScheduleBase"},
}
@@ -6031,11 +6306,11 @@ def __init__(
status: Optional[Union[str, "_models.ScheduleStatus"]] = None,
action: Optional[Union[str, "_models.ComputePowerAction"]] = None,
trigger_type: Optional[Union[str, "_models.TriggerType"]] = None,
- recurrence: Optional["_models.RecurrenceTrigger"] = None,
- cron: Optional["_models.CronTrigger"] = None,
+ recurrence: Optional["_models.Recurrence"] = None,
+ cron: Optional["_models.Cron"] = None,
schedule: Optional["_models.ScheduleBase"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword status: Is the schedule enabled or disabled?. Known values are: "Enabled" and
"Disabled".
@@ -6046,9 +6321,9 @@ def __init__(
"Cron".
:paramtype trigger_type: str or ~azure.mgmt.machinelearningservices.models.TriggerType
:keyword recurrence: Required if triggerType is Recurrence.
- :paramtype recurrence: ~azure.mgmt.machinelearningservices.models.RecurrenceTrigger
+ :paramtype recurrence: ~azure.mgmt.machinelearningservices.models.Recurrence
:keyword cron: Required if triggerType is Cron.
- :paramtype cron: ~azure.mgmt.machinelearningservices.models.CronTrigger
+ :paramtype cron: ~azure.mgmt.machinelearningservices.models.Cron
:keyword schedule: [Deprecated] Not used any more.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ScheduleBase
"""
@@ -6084,8 +6359,8 @@ def __init__(
*,
container_resource_limits: Optional["_models.ContainerResourceSettings"] = None,
container_resource_requests: Optional["_models.ContainerResourceSettings"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword container_resource_limits: Container resource limit info:.
:paramtype container_resource_limits:
@@ -6119,7 +6394,9 @@ class ContainerResourceSettings(_serialization.Model):
"memory": {"key": "memory", "type": "str"},
}
- def __init__(self, *, cpu: Optional[str] = None, gpu: Optional[str] = None, memory: Optional[str] = None, **kwargs):
+ def __init__(
+ self, *, cpu: Optional[str] = None, gpu: Optional[str] = None, memory: Optional[str] = None, **kwargs: Any
+ ) -> None:
"""
:keyword cpu: Number of vCPUs request/limit for container. More info:
https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/.
@@ -6148,7 +6425,7 @@ class CosmosDbSettings(_serialization.Model):
"collections_throughput": {"key": "collectionsThroughput", "type": "int"},
}
- def __init__(self, *, collections_throughput: Optional[int] = None, **kwargs):
+ def __init__(self, *, collections_throughput: Optional[int] = None, **kwargs: Any) -> None:
"""
:keyword collections_throughput: The throughput of the collections in cosmosdb database.
:paramtype collections_throughput: int
@@ -6157,6 +6434,51 @@ def __init__(self, *, collections_throughput: Optional[int] = None, **kwargs):
self.collections_throughput = collections_throughput
+class Cron(_serialization.Model):
+ """The workflow trigger cron for ComputeStartStop schedule type.
+
+ :ivar start_time: The start time in yyyy-MM-ddTHH:mm:ss format.
+ :vartype start_time: str
+ :ivar time_zone: Specifies time zone in which the schedule runs.
+ TimeZone should follow Windows time zone format. Refer:
+ https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ :vartype time_zone: str
+ :ivar expression: [Required] Specifies cron expression of schedule.
+ The expression should follow NCronTab format.
+ :vartype expression: str
+ """
+
+ _attribute_map = {
+ "start_time": {"key": "startTime", "type": "str"},
+ "time_zone": {"key": "timeZone", "type": "str"},
+ "expression": {"key": "expression", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ start_time: Optional[str] = None,
+ time_zone: str = "UTC",
+ expression: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword start_time: The start time in yyyy-MM-ddTHH:mm:ss format.
+ :paramtype start_time: str
+ :keyword time_zone: Specifies time zone in which the schedule runs.
+ TimeZone should follow Windows time zone format. Refer:
+ https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ :paramtype time_zone: str
+ :keyword expression: [Required] Specifies cron expression of schedule.
+ The expression should follow NCronTab format.
+ :paramtype expression: str
+ """
+ super().__init__(**kwargs)
+ self.start_time = start_time
+ self.time_zone = time_zone
+ self.expression = expression
+
+
class TriggerBase(_serialization.Model):
"""TriggerBase.
@@ -6195,8 +6517,8 @@ class TriggerBase(_serialization.Model):
_subtype_map = {"trigger_type": {"Cron": "CronTrigger", "Recurrence": "RecurrenceTrigger"}}
def __init__(
- self, *, end_time: Optional[str] = None, start_time: Optional[str] = None, time_zone: str = "UTC", **kwargs
- ):
+ self, *, end_time: Optional[str] = None, start_time: Optional[str] = None, time_zone: str = "UTC", **kwargs: Any
+ ) -> None:
"""
:keyword end_time: Specifies end time of schedule in ISO 8601, but without a UTC offset. Refer
https://en.wikipedia.org/wiki/ISO_8601.
@@ -6244,7 +6566,7 @@ class CronTrigger(TriggerBase):
_validation = {
"trigger_type": {"required": True},
- "expression": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "expression": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -6262,8 +6584,8 @@ def __init__(
end_time: Optional[str] = None,
start_time: Optional[str] = None,
time_zone: str = "UTC",
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword end_time: Specifies end time of schedule in ISO 8601, but without a UTC offset. Refer
https://en.wikipedia.org/wiki/ISO_8601.
@@ -6308,7 +6630,7 @@ class CustomForecastHorizon(ForecastHorizon):
"value": {"key": "value", "type": "int"},
}
- def __init__(self, *, value: int, **kwargs):
+ def __init__(self, *, value: int, **kwargs: Any) -> None:
"""
:keyword value: [Required] Forecast horizon value. Required.
:paramtype value: int
@@ -6356,7 +6678,7 @@ class JobInput(_serialization.Model):
}
}
- def __init__(self, *, description: Optional[str] = None, **kwargs):
+ def __init__(self, *, description: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword description: Description for the input.
:paramtype description: str
@@ -6386,7 +6708,7 @@ class CustomModelJobInput(AssetJobInput, JobInput):
_validation = {
"job_input_type": {"required": True},
- "uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -6402,8 +6724,8 @@ def __init__(
uri: str,
description: Optional[str] = None,
mode: Optional[Union[str, "_models.InputDeliveryMode"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the input.
:paramtype description: str
@@ -6456,7 +6778,7 @@ class JobOutput(_serialization.Model):
}
}
- def __init__(self, *, description: Optional[str] = None, **kwargs):
+ def __init__(self, *, description: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword description: Description for the output.
:paramtype description: str
@@ -6499,8 +6821,8 @@ def __init__(
description: Optional[str] = None,
mode: Optional[Union[str, "_models.OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the output.
:paramtype description: str
@@ -6538,7 +6860,7 @@ class CustomNCrossValidations(NCrossValidations):
"value": {"key": "value", "type": "int"},
}
- def __init__(self, *, value: int, **kwargs):
+ def __init__(self, *, value: int, **kwargs: Any) -> None:
"""
:keyword value: [Required] N-Cross validations value. Required.
:paramtype value: int
@@ -6569,7 +6891,7 @@ class CustomSeasonality(Seasonality):
"value": {"key": "value", "type": "int"},
}
- def __init__(self, *, value: int, **kwargs):
+ def __init__(self, *, value: int, **kwargs: Any) -> None:
"""
:keyword value: [Required] Seasonality value. Required.
:paramtype value: int
@@ -6579,10 +6901,81 @@ def __init__(self, *, value: int, **kwargs):
self.value = value
-class CustomTargetLags(TargetLags):
- """CustomTargetLags.
+class CustomService(_serialization.Model):
+ """Specifies the custom service configuration.
- All required parameters must be populated in order to send to Azure.
+ :ivar additional_properties: Unmatched properties from the message are deserialized to this
+ collection.
+ :vartype additional_properties: dict[str, any]
+ :ivar name: Name of the Custom Service.
+ :vartype name: str
+ :ivar image: Describes the Image Specifications.
+ :vartype image: ~azure.mgmt.machinelearningservices.models.Image
+ :ivar environment_variables: Environment Variable for the container.
+ :vartype environment_variables: dict[str,
+ ~azure.mgmt.machinelearningservices.models.EnvironmentVariable]
+ :ivar docker: Describes the docker settings for the image.
+ :vartype docker: ~azure.mgmt.machinelearningservices.models.Docker
+ :ivar endpoints: Configuring the endpoints for the container.
+ :vartype endpoints: list[~azure.mgmt.machinelearningservices.models.Endpoint]
+ :ivar volumes: Configuring the volumes for the container.
+ :vartype volumes: list[~azure.mgmt.machinelearningservices.models.VolumeDefinition]
+ """
+
+ _attribute_map = {
+ "additional_properties": {"key": "", "type": "{object}"},
+ "name": {"key": "name", "type": "str"},
+ "image": {"key": "image", "type": "Image"},
+ "environment_variables": {"key": "environmentVariables", "type": "{EnvironmentVariable}"},
+ "docker": {"key": "docker", "type": "Docker"},
+ "endpoints": {"key": "endpoints", "type": "[Endpoint]"},
+ "volumes": {"key": "volumes", "type": "[VolumeDefinition]"},
+ }
+
+ def __init__(
+ self,
+ *,
+ additional_properties: Optional[Dict[str, Any]] = None,
+ name: Optional[str] = None,
+ image: Optional["_models.Image"] = None,
+ environment_variables: Optional[Dict[str, "_models.EnvironmentVariable"]] = None,
+ docker: Optional["_models.Docker"] = None,
+ endpoints: Optional[List["_models.Endpoint"]] = None,
+ volumes: Optional[List["_models.VolumeDefinition"]] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword additional_properties: Unmatched properties from the message are deserialized to this
+ collection.
+ :paramtype additional_properties: dict[str, any]
+ :keyword name: Name of the Custom Service.
+ :paramtype name: str
+ :keyword image: Describes the Image Specifications.
+ :paramtype image: ~azure.mgmt.machinelearningservices.models.Image
+ :keyword environment_variables: Environment Variable for the container.
+ :paramtype environment_variables: dict[str,
+ ~azure.mgmt.machinelearningservices.models.EnvironmentVariable]
+ :keyword docker: Describes the docker settings for the image.
+ :paramtype docker: ~azure.mgmt.machinelearningservices.models.Docker
+ :keyword endpoints: Configuring the endpoints for the container.
+ :paramtype endpoints: list[~azure.mgmt.machinelearningservices.models.Endpoint]
+ :keyword volumes: Configuring the volumes for the container.
+ :paramtype volumes: list[~azure.mgmt.machinelearningservices.models.VolumeDefinition]
+ """
+ super().__init__(**kwargs)
+ self.additional_properties = additional_properties
+ self.name = name
+ self.image = image
+ self.environment_variables = environment_variables
+ self.docker = docker
+ self.endpoints = endpoints
+ self.volumes = volumes
+
+
+class CustomTargetLags(TargetLags):
+ """CustomTargetLags.
+
+ All required parameters must be populated in order to send to Azure.
:ivar mode: [Required] Set target lags mode - Auto/Custom. Required. Known values are: "Auto"
and "Custom".
@@ -6601,7 +6994,7 @@ class CustomTargetLags(TargetLags):
"values": {"key": "values", "type": "[int]"},
}
- def __init__(self, *, values: List[int], **kwargs):
+ def __init__(self, *, values: List[int], **kwargs: Any) -> None:
"""
:keyword values: [Required] Set target lags values. Required.
:paramtype values: list[int]
@@ -6633,7 +7026,7 @@ class CustomTargetRollingWindowSize(TargetRollingWindowSize):
"value": {"key": "value", "type": "int"},
}
- def __init__(self, *, value: int, **kwargs):
+ def __init__(self, *, value: int, **kwargs: Any) -> None:
"""
:keyword value: [Required] TargetRollingWindowSize value. Required.
:paramtype value: int
@@ -6654,7 +7047,7 @@ class DatabricksSchema(_serialization.Model):
"properties": {"key": "properties", "type": "DatabricksProperties"},
}
- def __init__(self, *, properties: Optional["_models.DatabricksProperties"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.DatabricksProperties"] = None, **kwargs: Any) -> None:
"""
:keyword properties: Properties of Databricks.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.DatabricksProperties
@@ -6732,8 +7125,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties: Properties of Databricks.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.DatabricksProperties
@@ -6779,7 +7172,7 @@ class DatabricksComputeSecretsProperties(_serialization.Model):
"databricks_access_token": {"key": "databricksAccessToken", "type": "str"},
}
- def __init__(self, *, databricks_access_token: Optional[str] = None, **kwargs):
+ def __init__(self, *, databricks_access_token: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword databricks_access_token: access token for databricks account.
:paramtype databricks_access_token: str
@@ -6810,7 +7203,7 @@ class DatabricksComputeSecrets(ComputeSecrets, DatabricksComputeSecretsPropertie
"compute_type": {"key": "computeType", "type": "str"},
}
- def __init__(self, *, databricks_access_token: Optional[str] = None, **kwargs):
+ def __init__(self, *, databricks_access_token: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword databricks_access_token: access token for databricks account.
:paramtype databricks_access_token: str
@@ -6834,7 +7227,9 @@ class DatabricksProperties(_serialization.Model):
"workspace_url": {"key": "workspaceUrl", "type": "str"},
}
- def __init__(self, *, databricks_access_token: Optional[str] = None, workspace_url: Optional[str] = None, **kwargs):
+ def __init__(
+ self, *, databricks_access_token: Optional[str] = None, workspace_url: Optional[str] = None, **kwargs: Any
+ ) -> None:
"""
:keyword databricks_access_token: Databricks access token.
:paramtype databricks_access_token: str
@@ -6884,7 +7279,7 @@ class DataContainer(Resource):
"properties": {"key": "properties", "type": "DataContainerProperties"},
}
- def __init__(self, *, properties: "_models.DataContainerProperties", **kwargs):
+ def __init__(self, *, properties: "_models.DataContainerProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.DataContainerProperties
@@ -6941,8 +7336,8 @@ def __init__(
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -6976,8 +7371,8 @@ class DataContainerResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.DataContainer"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.DataContainer"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of DataContainer objects. If null, there are no
additional pages.
@@ -7055,8 +7450,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword compute_location: Location for the underlying compute.
:paramtype compute_location: str
@@ -7090,7 +7485,9 @@ class DataLakeAnalyticsSchema(_serialization.Model):
"properties": {"key": "properties", "type": "DataLakeAnalyticsSchemaProperties"},
}
- def __init__(self, *, properties: Optional["_models.DataLakeAnalyticsSchemaProperties"] = None, **kwargs):
+ def __init__(
+ self, *, properties: Optional["_models.DataLakeAnalyticsSchemaProperties"] = None, **kwargs: Any
+ ) -> None:
"""
:keyword properties:
:paramtype properties:
@@ -7170,8 +7567,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties:
:paramtype properties:
@@ -7218,7 +7615,7 @@ class DataLakeAnalyticsSchemaProperties(_serialization.Model):
"data_lake_store_account_name": {"key": "dataLakeStoreAccountName", "type": "str"},
}
- def __init__(self, *, data_lake_store_account_name: Optional[str] = None, **kwargs):
+ def __init__(self, *, data_lake_store_account_name: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword data_lake_store_account_name: DataLake Store Account Name.
:paramtype data_lake_store_account_name: str
@@ -7251,7 +7648,7 @@ class DataPathAssetReference(AssetReferenceBase):
"path": {"key": "path", "type": "str"},
}
- def __init__(self, *, datastore_id: Optional[str] = None, path: Optional[str] = None, **kwargs):
+ def __init__(self, *, datastore_id: Optional[str] = None, path: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword datastore_id: ARM resource ID of the datastore where the asset is located.
:paramtype datastore_id: str
@@ -7302,7 +7699,7 @@ class Datastore(Resource):
"properties": {"key": "properties", "type": "DatastoreProperties"},
}
- def __init__(self, *, properties: "_models.DatastoreProperties", **kwargs):
+ def __init__(self, *, properties: "_models.DatastoreProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.DatastoreProperties
@@ -7326,7 +7723,9 @@ class DatastoreResourceArmPaginatedResult(_serialization.Model):
"value": {"key": "value", "type": "[Datastore]"},
}
- def __init__(self, *, next_link: Optional[str] = None, value: Optional[List["_models.Datastore"]] = None, **kwargs):
+ def __init__(
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.Datastore"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of Datastore objects. If null, there are no
additional pages.
@@ -7377,7 +7776,7 @@ class DataVersionBase(Resource):
"properties": {"key": "properties", "type": "DataVersionBaseProperties"},
}
- def __init__(self, *, properties: "_models.DataVersionBaseProperties", **kwargs):
+ def __init__(self, *, properties: "_models.DataVersionBaseProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.DataVersionBaseProperties
@@ -7407,15 +7806,14 @@ class DataVersionBaseProperties(AssetBase):
:ivar data_type: [Required] Specifies the type of data. Required. Known values are: "uri_file",
"uri_folder", and "mltable".
:vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
- :ivar data_uri: [Required] Uri of the data. Usage/meaning depends on
- Microsoft.MachineLearning.ManagementFrontEnd.Contracts.V20221001.Assets.DataVersionBase.DataType.
- Required.
+ :ivar data_uri: [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330. Required.
:vartype data_uri: str
"""
_validation = {
"data_type": {"required": True},
- "data_uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "data_uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -7441,8 +7839,8 @@ def __init__(
tags: Optional[Dict[str, str]] = None,
is_anonymous: bool = False,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -7454,9 +7852,8 @@ def __init__(
:paramtype is_anonymous: bool
:keyword is_archived: Is the asset archived?.
:paramtype is_archived: bool
- :keyword data_uri: [Required] Uri of the data. Usage/meaning depends on
- Microsoft.MachineLearning.ManagementFrontEnd.Contracts.V20221001.Assets.DataVersionBase.DataType.
- Required.
+ :keyword data_uri: [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330. Required.
:paramtype data_uri: str
"""
super().__init__(
@@ -7487,8 +7884,8 @@ class DataVersionBaseResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.DataVersionBase"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.DataVersionBase"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of DataVersionBase objects. If null, there are no
additional pages.
@@ -7526,7 +7923,7 @@ class OnlineScaleSettings(_serialization.Model):
"scale_type": {"Default": "DefaultScaleSettings", "TargetUtilization": "TargetUtilizationScaleSettings"}
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.scale_type: Optional[str] = None
@@ -7550,7 +7947,7 @@ class DefaultScaleSettings(OnlineScaleSettings):
"scale_type": {"key": "scaleType", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.scale_type: str = "Default"
@@ -7567,7 +7964,7 @@ class DeploymentLogs(_serialization.Model):
"content": {"key": "content", "type": "str"},
}
- def __init__(self, *, content: Optional[str] = None, **kwargs):
+ def __init__(self, *, content: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword content: The retrieved online deployment logs.
:paramtype content: str
@@ -7596,8 +7993,8 @@ def __init__(
*,
container_type: Optional[Union[str, "_models.ContainerType"]] = None,
tail: Optional[int] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword container_type: The type of container to retrieve logs from. Known values are:
"StorageInitializer" and "InferenceServer".
@@ -7633,8 +8030,8 @@ def __init__(
instance_count: int = 1,
instance_type: Optional[str] = None,
properties: Optional[Dict[str, JSON]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword instance_count: Optional number of instances or nodes used by the compute target.
:paramtype instance_count: int
@@ -7672,8 +8069,8 @@ def __init__(
instance_count: int = 1,
instance_type: Optional[str] = None,
properties: Optional[Dict[str, JSON]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword instance_count: Optional number of instances or nodes used by the compute target.
:paramtype instance_count: int
@@ -7732,8 +8129,8 @@ def __init__(
container_registry: Optional[Dict[str, JSON]] = None,
application_insights: Optional[Dict[str, JSON]] = None,
others: Optional[Dict[str, JSON]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword udr: Setting for diagnosing user defined routing.
:paramtype udr: dict[str, JSON]
@@ -7777,7 +8174,7 @@ class DiagnoseResponseResult(_serialization.Model):
"value": {"key": "value", "type": "DiagnoseResponseResultValue"},
}
- def __init__(self, *, value: Optional["_models.DiagnoseResponseResultValue"] = None, **kwargs):
+ def __init__(self, *, value: Optional["_models.DiagnoseResponseResultValue"] = None, **kwargs: Any) -> None:
"""
:keyword value:
:paramtype value: ~azure.mgmt.machinelearningservices.models.DiagnoseResponseResultValue
@@ -7839,8 +8236,8 @@ def __init__(
container_registry_results: Optional[List["_models.DiagnoseResult"]] = None,
application_insights_results: Optional[List["_models.DiagnoseResult"]] = None,
other_results: Optional[List["_models.DiagnoseResult"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword user_defined_route_results:
:paramtype user_defined_route_results:
@@ -7906,7 +8303,7 @@ class DiagnoseResult(_serialization.Model):
"message": {"key": "message", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.code = None
@@ -7925,7 +8322,7 @@ class DiagnoseWorkspaceParameters(_serialization.Model):
"value": {"key": "value", "type": "DiagnoseRequestProperties"},
}
- def __init__(self, *, value: Optional["_models.DiagnoseRequestProperties"] = None, **kwargs):
+ def __init__(self, *, value: Optional["_models.DiagnoseRequestProperties"] = None, **kwargs: Any) -> None:
"""
:keyword value: Value of Parameters.
:paramtype value: ~azure.mgmt.machinelearningservices.models.DiagnoseRequestProperties
@@ -7957,12 +8354,46 @@ class DistributionConfiguration(_serialization.Model):
_subtype_map = {"distribution_type": {"Mpi": "Mpi", "PyTorch": "PyTorch", "TensorFlow": "TensorFlow"}}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.distribution_type: Optional[str] = None
+class Docker(_serialization.Model):
+ """Docker container configuration.
+
+ :ivar additional_properties: Unmatched properties from the message are deserialized to this
+ collection.
+ :vartype additional_properties: dict[str, any]
+ :ivar privileged: Indicate whether container shall run in privileged or non-privileged mode.
+ :vartype privileged: bool
+ """
+
+ _attribute_map = {
+ "additional_properties": {"key": "", "type": "{object}"},
+ "privileged": {"key": "privileged", "type": "bool"},
+ }
+
+ def __init__(
+ self,
+ *,
+ additional_properties: Optional[Dict[str, Any]] = None,
+ privileged: Optional[bool] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword additional_properties: Unmatched properties from the message are deserialized to this
+ collection.
+ :paramtype additional_properties: dict[str, any]
+ :keyword privileged: Indicate whether container shall run in privileged or non-privileged mode.
+ :paramtype privileged: bool
+ """
+ super().__init__(**kwargs)
+ self.additional_properties = additional_properties
+ self.privileged = privileged
+
+
class EncryptionKeyVaultProperties(_serialization.Model):
"""EncryptionKeyVaultProperties.
@@ -7990,8 +8421,8 @@ class EncryptionKeyVaultProperties(_serialization.Model):
}
def __init__(
- self, *, key_vault_arm_id: str, key_identifier: str, identity_client_id: Optional[str] = None, **kwargs
- ):
+ self, *, key_vault_arm_id: str, key_identifier: str, identity_client_id: Optional[str] = None, **kwargs: Any
+ ) -> None:
"""
:keyword key_vault_arm_id: The ArmId of the keyVault where the customer owned encryption key is
present. Required.
@@ -8040,8 +8471,8 @@ def __init__(
status: Union[str, "_models.EncryptionStatus"],
key_vault_properties: "_models.EncryptionKeyVaultProperties",
identity: Optional["_models.IdentityForCmk"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword status: Indicates whether or not the encryption is enabled for the workspace.
Required. Known values are: "Enabled" and "Disabled".
@@ -8059,6 +8490,61 @@ def __init__(
self.key_vault_properties = key_vault_properties
+class Endpoint(_serialization.Model):
+ """Describes the endpoint configuration for the container.
+
+ :ivar protocol: Protocol over which communication will happen over this endpoint. Known values
+ are: "tcp", "udp", and "http".
+ :vartype protocol: str or ~azure.mgmt.machinelearningservices.models.Protocol
+ :ivar name: Name of the Endpoint.
+ :vartype name: str
+ :ivar target: Application port inside the container.
+ :vartype target: int
+ :ivar published: Port over which the application is exposed from container.
+ :vartype published: int
+ :ivar host_ip: Host IP over which the application is exposed from the container.
+ :vartype host_ip: str
+ """
+
+ _attribute_map = {
+ "protocol": {"key": "protocol", "type": "str"},
+ "name": {"key": "name", "type": "str"},
+ "target": {"key": "target", "type": "int"},
+ "published": {"key": "published", "type": "int"},
+ "host_ip": {"key": "hostIp", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ protocol: Union[str, "_models.Protocol"] = "tcp",
+ name: Optional[str] = None,
+ target: Optional[int] = None,
+ published: Optional[int] = None,
+ host_ip: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword protocol: Protocol over which communication will happen over this endpoint. Known
+ values are: "tcp", "udp", and "http".
+ :paramtype protocol: str or ~azure.mgmt.machinelearningservices.models.Protocol
+ :keyword name: Name of the Endpoint.
+ :paramtype name: str
+ :keyword target: Application port inside the container.
+ :paramtype target: int
+ :keyword published: Port over which the application is exposed from container.
+ :paramtype published: int
+ :keyword host_ip: Host IP over which the application is exposed from the container.
+ :paramtype host_ip: str
+ """
+ super().__init__(**kwargs)
+ self.protocol = protocol
+ self.name = name
+ self.target = target
+ self.published = published
+ self.host_ip = host_ip
+
+
class EndpointAuthKeys(_serialization.Model):
"""Keys for endpoint authentication.
@@ -8073,7 +8559,9 @@ class EndpointAuthKeys(_serialization.Model):
"secondary_key": {"key": "secondaryKey", "type": "str"},
}
- def __init__(self, *, primary_key: Optional[str] = None, secondary_key: Optional[str] = None, **kwargs):
+ def __init__(
+ self, *, primary_key: Optional[str] = None, secondary_key: Optional[str] = None, **kwargs: Any
+ ) -> None:
"""
:keyword primary_key: The primary key.
:paramtype primary_key: str
@@ -8112,8 +8600,8 @@ def __init__(
expiry_time_utc: int = 0,
refresh_after_time_utc: int = 0,
token_type: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword access_token: Access token for endpoint authentication.
:paramtype access_token: str
@@ -8154,7 +8642,7 @@ class ScheduleActionBase(_serialization.Model):
_subtype_map = {"action_type": {"CreateJob": "JobScheduleAction", "InvokeBatchEndpoint": "EndpointScheduleAction"}}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.action_type: Optional[str] = None
@@ -8187,7 +8675,7 @@ class EndpointScheduleAction(ScheduleActionBase):
"endpoint_invocation_definition": {"key": "endpointInvocationDefinition", "type": "object"},
}
- def __init__(self, *, endpoint_invocation_definition: JSON, **kwargs):
+ def __init__(self, *, endpoint_invocation_definition: JSON, **kwargs: Any) -> None:
"""
:keyword endpoint_invocation_definition: [Required] Defines Schedule action definition details.
@@ -8240,7 +8728,7 @@ class EnvironmentContainer(Resource):
"properties": {"key": "properties", "type": "EnvironmentContainerProperties"},
}
- def __init__(self, *, properties: "_models.EnvironmentContainerProperties", **kwargs):
+ def __init__(self, *, properties: "_models.EnvironmentContainerProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties:
@@ -8267,11 +8755,16 @@ class EnvironmentContainerProperties(AssetContainer):
:vartype latest_version: str
:ivar next_version: The next auto incremental version.
:vartype next_version: str
+ :ivar provisioning_state: Provisioning state for the environment container. Known values are:
+ "Succeeded", "Failed", "Canceled", "Creating", "Updating", and "Deleting".
+ :vartype provisioning_state: str or
+ ~azure.mgmt.machinelearningservices.models.AssetProvisioningState
"""
_validation = {
"latest_version": {"readonly": True},
"next_version": {"readonly": True},
+ "provisioning_state": {"readonly": True},
}
_attribute_map = {
@@ -8281,6 +8774,7 @@ class EnvironmentContainerProperties(AssetContainer):
"is_archived": {"key": "isArchived", "type": "bool"},
"latest_version": {"key": "latestVersion", "type": "str"},
"next_version": {"key": "nextVersion", "type": "str"},
+ "provisioning_state": {"key": "provisioningState", "type": "str"},
}
def __init__(
@@ -8290,8 +8784,8 @@ def __init__(
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -8303,6 +8797,7 @@ def __init__(
:paramtype is_archived: bool
"""
super().__init__(description=description, properties=properties, tags=tags, is_archived=is_archived, **kwargs)
+ self.provisioning_state = None
class EnvironmentContainerResourceArmPaginatedResult(_serialization.Model):
@@ -8321,8 +8816,12 @@ class EnvironmentContainerResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.EnvironmentContainer"]] = None, **kwargs
- ):
+ self,
+ *,
+ next_link: Optional[str] = None,
+ value: Optional[List["_models.EnvironmentContainer"]] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of EnvironmentContainer objects. If null, there
are no additional pages.
@@ -8335,6 +8834,49 @@ def __init__(
self.value = value
+class EnvironmentVariable(_serialization.Model):
+ """Environment Variables for the container.
+
+ :ivar additional_properties: Unmatched properties from the message are deserialized to this
+ collection.
+ :vartype additional_properties: dict[str, any]
+ :ivar type: Type of the Environment Variable. Possible values are: local - For local variable.
+ "local"
+ :vartype type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentVariableType
+ :ivar value: Value of the Environment variable.
+ :vartype value: str
+ """
+
+ _attribute_map = {
+ "additional_properties": {"key": "", "type": "{object}"},
+ "type": {"key": "type", "type": "str"},
+ "value": {"key": "value", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ additional_properties: Optional[Dict[str, Any]] = None,
+ type: Union[str, "_models.EnvironmentVariableType"] = "local",
+ value: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword additional_properties: Unmatched properties from the message are deserialized to this
+ collection.
+ :paramtype additional_properties: dict[str, any]
+ :keyword type: Type of the Environment Variable. Possible values are: local - For local
+ variable. "local"
+ :paramtype type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentVariableType
+ :keyword value: Value of the Environment variable.
+ :paramtype value: str
+ """
+ super().__init__(**kwargs)
+ self.additional_properties = additional_properties
+ self.type = type
+ self.value = value
+
+
class EnvironmentVersion(Resource):
"""Azure Resource Manager resource envelope.
@@ -8373,7 +8915,7 @@ class EnvironmentVersion(Resource):
"properties": {"key": "properties", "type": "EnvironmentVersionProperties"},
}
- def __init__(self, *, properties: "_models.EnvironmentVersionProperties", **kwargs):
+ def __init__(self, *, properties: "_models.EnvironmentVersionProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.EnvironmentVersionProperties
@@ -8436,10 +8978,17 @@ class EnvironmentVersionProperties(AssetBase): # pylint: disable=too-many-insta
~azure.mgmt.machinelearningservices.models.InferenceContainerProperties
:ivar os_type: The OS type of the environment. Known values are: "Linux" and "Windows".
:vartype os_type: str or ~azure.mgmt.machinelearningservices.models.OperatingSystemType
+ :ivar provisioning_state: Provisioning state for the environment version. Known values are:
+ "Succeeded", "Failed", "Canceled", "Creating", "Updating", and "Deleting".
+ :vartype provisioning_state: str or
+ ~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Stage in the environment lifecycle assigned to this environment.
+ :vartype stage: str
"""
_validation = {
"environment_type": {"readonly": True},
+ "provisioning_state": {"readonly": True},
}
_attribute_map = {
@@ -8455,6 +9004,8 @@ class EnvironmentVersionProperties(AssetBase): # pylint: disable=too-many-insta
"image": {"key": "image", "type": "str"},
"inference_config": {"key": "inferenceConfig", "type": "InferenceContainerProperties"},
"os_type": {"key": "osType", "type": "str"},
+ "provisioning_state": {"key": "provisioningState", "type": "str"},
+ "stage": {"key": "stage", "type": "str"},
}
def __init__(
@@ -8471,8 +9022,9 @@ def __init__(
image: Optional[str] = None,
inference_config: Optional["_models.InferenceContainerProperties"] = None,
os_type: Optional[Union[str, "_models.OperatingSystemType"]] = None,
- **kwargs
- ):
+ stage: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -8513,6 +9065,8 @@ def __init__(
~azure.mgmt.machinelearningservices.models.InferenceContainerProperties
:keyword os_type: The OS type of the environment. Known values are: "Linux" and "Windows".
:paramtype os_type: str or ~azure.mgmt.machinelearningservices.models.OperatingSystemType
+ :keyword stage: Stage in the environment lifecycle assigned to this environment.
+ :paramtype stage: str
"""
super().__init__(
description=description,
@@ -8529,6 +9083,8 @@ def __init__(
self.image = image
self.inference_config = inference_config
self.os_type = os_type
+ self.provisioning_state = None
+ self.stage = stage
class EnvironmentVersionResourceArmPaginatedResult(_serialization.Model):
@@ -8547,8 +9103,12 @@ class EnvironmentVersionResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.EnvironmentVersion"]] = None, **kwargs
- ):
+ self,
+ *,
+ next_link: Optional[str] = None,
+ value: Optional[List["_models.EnvironmentVersion"]] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of EnvironmentVersion objects. If null, there are
no additional pages.
@@ -8582,7 +9142,7 @@ class ErrorAdditionalInfo(_serialization.Model):
"info": {"key": "info", "type": "object"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.type = None
@@ -8622,7 +9182,7 @@ class ErrorDetail(_serialization.Model):
"additional_info": {"key": "additionalInfo", "type": "[ErrorAdditionalInfo]"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.code = None
@@ -8633,7 +9193,8 @@ def __init__(self, **kwargs):
class ErrorResponse(_serialization.Model):
- """Common error response for all Azure Resource Manager APIs to return error details for failed operations. (This also follows the OData error response format.).
+ """Common error response for all Azure Resource Manager APIs to return error details for failed
+ operations. (This also follows the OData error response format.).
:ivar error: The error object.
:vartype error: ~azure.mgmt.machinelearningservices.models.ErrorDetail
@@ -8643,7 +9204,7 @@ class ErrorResponse(_serialization.Model):
"error": {"key": "error", "type": "ErrorDetail"},
}
- def __init__(self, *, error: Optional["_models.ErrorDetail"] = None, **kwargs):
+ def __init__(self, *, error: Optional["_models.ErrorDetail"] = None, **kwargs: Any) -> None:
"""
:keyword error: The error object.
:paramtype error: ~azure.mgmt.machinelearningservices.models.ErrorDetail
@@ -8685,8 +9246,8 @@ def __init__(
retail_price: float,
os_type: Union[str, "_models.VMPriceOSType"],
vm_tier: Union[str, "_models.VMTier"],
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword retail_price: The price charged for using the VM. Required.
:paramtype retail_price: float
@@ -8737,8 +9298,8 @@ def __init__(
billing_currency: Union[str, "_models.BillingCurrency"],
unit_of_measure: Union[str, "_models.UnitOfMeasure"],
values: List["_models.EstimatedVMPrice"],
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword billing_currency: Three lettered code specifying the currency of the VM price.
Example: USD. Required. "USD"
@@ -8767,7 +9328,7 @@ class ExternalFQDNResponse(_serialization.Model):
"value": {"key": "value", "type": "[FQDNEndpoints]"},
}
- def __init__(self, *, value: Optional[List["_models.FQDNEndpoints"]] = None, **kwargs):
+ def __init__(self, *, value: Optional[List["_models.FQDNEndpoints"]] = None, **kwargs: Any) -> None:
"""
:keyword value:
:paramtype value: list[~azure.mgmt.machinelearningservices.models.FQDNEndpoints]
@@ -8787,7 +9348,7 @@ class FeaturizationSettings(_serialization.Model):
"dataset_language": {"key": "datasetLanguage", "type": "str"},
}
- def __init__(self, *, dataset_language: Optional[str] = None, **kwargs):
+ def __init__(self, *, dataset_language: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword dataset_language: Dataset language, useful for the text data.
:paramtype dataset_language: str
@@ -8807,7 +9368,7 @@ class FlavorData(_serialization.Model):
"data": {"key": "data", "type": "{str}"},
}
- def __init__(self, *, data: Optional[Dict[str, str]] = None, **kwargs):
+ def __init__(self, *, data: Optional[Dict[str, str]] = None, **kwargs: Any) -> None:
"""
:keyword data: Model flavor-specific data.
:paramtype data: dict[str, str]
@@ -8915,8 +9476,8 @@ def __init__(
forecasting_settings: Optional["_models.ForecastingSettings"] = None,
primary_metric: Optional[Union[str, "_models.ForecastingPrimaryMetrics"]] = None,
training_settings: Optional["_models.ForecastingTrainingSettings"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -9085,8 +9646,8 @@ def __init__(
time_column_name: Optional[str] = None,
time_series_id_column_names: Optional[List[str]] = None,
use_stl: Optional[Union[str, "_models.UseStl"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword country_or_region_for_holidays: Country or region for holidays for forecasting tasks.
These should be ISO 3166 two-letter country/region codes, for example 'US' or 'GB'.
@@ -9208,8 +9769,8 @@ def __init__(
stack_ensemble_settings: Optional["_models.StackEnsembleSettings"] = None,
allowed_training_algorithms: Optional[List[Union[str, "_models.ForecastingModels"]]] = None,
blocked_training_algorithms: Optional[List[Union[str, "_models.ForecastingModels"]]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword enable_dnn_training: Enable recommendation of DNN models.
:paramtype enable_dnn_training: bool
@@ -9268,8 +9829,8 @@ def __init__(
*,
domain_name: Optional[str] = None,
endpoint_details: Optional[List["_models.FQDNEndpointDetail"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword domain_name:
:paramtype domain_name: str
@@ -9293,7 +9854,7 @@ class FQDNEndpointDetail(_serialization.Model):
"port": {"key": "port", "type": "int"},
}
- def __init__(self, *, port: Optional[int] = None, **kwargs):
+ def __init__(self, *, port: Optional[int] = None, **kwargs: Any) -> None:
"""
:keyword port:
:paramtype port: int
@@ -9313,7 +9874,7 @@ class FQDNEndpoints(_serialization.Model):
"properties": {"key": "properties", "type": "FQDNEndpointsProperties"},
}
- def __init__(self, *, properties: Optional["_models.FQDNEndpointsProperties"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.FQDNEndpointsProperties"] = None, **kwargs: Any) -> None:
"""
:keyword properties:
:paramtype properties: ~azure.mgmt.machinelearningservices.models.FQDNEndpointsProperties
@@ -9337,8 +9898,8 @@ class FQDNEndpointsProperties(_serialization.Model):
}
def __init__(
- self, *, category: Optional[str] = None, endpoints: Optional[List["_models.FQDNEndpoint"]] = None, **kwargs
- ):
+ self, *, category: Optional[str] = None, endpoints: Optional[List["_models.FQDNEndpoint"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword category:
:paramtype category: str
@@ -9370,7 +9931,7 @@ class GridSamplingAlgorithm(SamplingAlgorithm):
"sampling_algorithm_type": {"key": "samplingAlgorithmType", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.sampling_algorithm_type: str = "Grid"
@@ -9387,7 +9948,7 @@ class HDInsightSchema(_serialization.Model):
"properties": {"key": "properties", "type": "HDInsightProperties"},
}
- def __init__(self, *, properties: Optional["_models.HDInsightProperties"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.HDInsightProperties"] = None, **kwargs: Any) -> None:
"""
:keyword properties: HDInsight compute properties.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.HDInsightProperties
@@ -9465,8 +10026,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties: HDInsight compute properties.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.HDInsightProperties
@@ -9525,8 +10086,8 @@ def __init__(
ssh_port: Optional[int] = None,
address: Optional[str] = None,
administrator_account: Optional["_models.VirtualMachineSshCredentials"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword ssh_port: Port open for ssh connections on the master node of the cluster.
:paramtype ssh_port: int
@@ -9556,7 +10117,7 @@ class IdAssetReference(AssetReferenceBase):
_validation = {
"reference_type": {"required": True},
- "asset_id": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "asset_id": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -9564,7 +10125,7 @@ class IdAssetReference(AssetReferenceBase):
"asset_id": {"key": "assetId", "type": "str"},
}
- def __init__(self, *, asset_id: str, **kwargs):
+ def __init__(self, *, asset_id: str, **kwargs: Any) -> None:
"""
:keyword asset_id: [Required] ARM resource ID of the asset. Required.
:paramtype asset_id: str
@@ -9586,7 +10147,7 @@ class IdentityForCmk(_serialization.Model):
"user_assigned_identity": {"key": "userAssignedIdentity", "type": "str"},
}
- def __init__(self, *, user_assigned_identity: Optional[str] = None, **kwargs):
+ def __init__(self, *, user_assigned_identity: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword user_assigned_identity: The ArmId of the user assigned identity that will be used to
access the customer managed key vault.
@@ -9596,23 +10157,89 @@ def __init__(self, *, user_assigned_identity: Optional[str] = None, **kwargs):
self.user_assigned_identity = user_assigned_identity
+class IdleShutdownSetting(_serialization.Model):
+ """Stops compute instance after user defined period of inactivity.
+
+ :ivar idle_time_before_shutdown: Time is defined in ISO8601 format. Minimum is 15 min, maximum
+ is 3 days.
+ :vartype idle_time_before_shutdown: str
+ """
+
+ _attribute_map = {
+ "idle_time_before_shutdown": {"key": "idleTimeBeforeShutdown", "type": "str"},
+ }
+
+ def __init__(self, *, idle_time_before_shutdown: Optional[str] = None, **kwargs: Any) -> None:
+ """
+ :keyword idle_time_before_shutdown: Time is defined in ISO8601 format. Minimum is 15 min,
+ maximum is 3 days.
+ :paramtype idle_time_before_shutdown: str
+ """
+ super().__init__(**kwargs)
+ self.idle_time_before_shutdown = idle_time_before_shutdown
+
+
+class Image(_serialization.Model):
+ """Describes the Image Specifications.
+
+ :ivar additional_properties: Unmatched properties from the message are deserialized to this
+ collection.
+ :vartype additional_properties: dict[str, any]
+ :ivar type: Type of the image. Possible values are: docker - For docker images. azureml - For
+ AzureML images. Known values are: "docker" and "azureml".
+ :vartype type: str or ~azure.mgmt.machinelearningservices.models.ImageType
+ :ivar reference: Image reference.
+ :vartype reference: str
+ """
+
+ _attribute_map = {
+ "additional_properties": {"key": "", "type": "{object}"},
+ "type": {"key": "type", "type": "str"},
+ "reference": {"key": "reference", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ additional_properties: Optional[Dict[str, Any]] = None,
+ type: Union[str, "_models.ImageType"] = "docker",
+ reference: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword additional_properties: Unmatched properties from the message are deserialized to this
+ collection.
+ :paramtype additional_properties: dict[str, any]
+ :keyword type: Type of the image. Possible values are: docker - For docker images. azureml -
+ For AzureML images. Known values are: "docker" and "azureml".
+ :paramtype type: str or ~azure.mgmt.machinelearningservices.models.ImageType
+ :keyword reference: Image reference.
+ :paramtype reference: str
+ """
+ super().__init__(**kwargs)
+ self.additional_properties = additional_properties
+ self.type = type
+ self.reference = reference
+
+
class ImageVertical(_serialization.Model):
"""Abstract class for AutoML tasks that train image (computer vision) models -
- such as Image Classification / Image Classification Multilabel / Image Object Detection / Image Instance Segmentation.
+ such as Image Classification / Image Classification Multilabel / Image Object Detection / Image
+ Instance Segmentation.
- All required parameters must be populated in order to send to Azure.
+ All required parameters must be populated in order to send to Azure.
- :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
- :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
- :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
- validation purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype validation_data_size: float
+ :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
+ :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
+ :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
+ validation purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype validation_data_size: float
"""
_validation = {
@@ -9633,8 +10260,8 @@ def __init__(
sweep_settings: Optional["_models.ImageSweepSettings"] = None,
validation_data: Optional["_models.MLTableJobInput"] = None,
validation_data_size: Optional[float] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword limit_settings: [Required] Limit settings for the AutoML job. Required.
:paramtype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
@@ -9702,8 +10329,8 @@ def __init__(
validation_data_size: Optional[float] = None,
model_settings: Optional["_models.ImageModelSettingsClassification"] = None,
search_space: Optional[List["_models.ImageModelDistributionSettingsClassification"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword limit_settings: [Required] Limit settings for the AutoML job. Required.
:paramtype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
@@ -9736,47 +10363,49 @@ def __init__(
class ImageClassification(ImageClassificationBase, AutoMLVertical): # pylint: disable=too-many-instance-attributes
- """Image Classification. Multi-class image classification is used when an image is classified with only a single label
- from a set of classes - e.g. each image is classified as either an image of a 'cat' or a 'dog' or a 'duck'.
+ """Image Classification. Multi-class image classification is used when an image is classified with
+ only a single label
+ from a set of classes - e.g. each image is classified as either an image of a 'cat' or a 'dog'
+ or a 'duck'.
- All required parameters must be populated in order to send to Azure.
+ All required parameters must be populated in order to send to Azure.
- :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
- "Warning", "Error", and "Critical".
- :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
- :ivar target_column_name: Target column name: This is prediction values column.
- Also known as label column name in context of classification tasks.
- :vartype target_column_name: str
- :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
- "Classification", "Regression", "Forecasting", "ImageClassification",
- "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
- "TextClassification", "TextClassificationMultilabel", and "TextNER".
- :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
- :ivar training_data: [Required] Training data input. Required.
- :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
- :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
- :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
- validation purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype validation_data_size: float
- :ivar model_settings: Settings used for training the model.
- :vartype model_settings:
- ~azure.mgmt.machinelearningservices.models.ImageModelSettingsClassification
- :ivar search_space: Search space for sampling different combinations of models and their
- hyperparameters.
- :vartype search_space:
- list[~azure.mgmt.machinelearningservices.models.ImageModelDistributionSettingsClassification]
- :ivar primary_metric: Primary metric to optimize for this task. Known values are:
- "AUCWeighted", "Accuracy", "NormMacroRecall", "AveragePrecisionScoreWeighted", and
- "PrecisionScoreWeighted".
- :vartype primary_metric: str or
- ~azure.mgmt.machinelearningservices.models.ClassificationPrimaryMetrics
+ :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
+ "Warning", "Error", and "Critical".
+ :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
+ :ivar target_column_name: Target column name: This is prediction values column.
+ Also known as label column name in context of classification tasks.
+ :vartype target_column_name: str
+ :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
+ "Classification", "Regression", "Forecasting", "ImageClassification",
+ "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
+ "TextClassification", "TextClassificationMultilabel", and "TextNER".
+ :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
+ :ivar training_data: [Required] Training data input. Required.
+ :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
+ :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
+ :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
+ validation purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype validation_data_size: float
+ :ivar model_settings: Settings used for training the model.
+ :vartype model_settings:
+ ~azure.mgmt.machinelearningservices.models.ImageModelSettingsClassification
+ :ivar search_space: Search space for sampling different combinations of models and their
+ hyperparameters.
+ :vartype search_space:
+ list[~azure.mgmt.machinelearningservices.models.ImageModelDistributionSettingsClassification]
+ :ivar primary_metric: Primary metric to optimize for this task. Known values are:
+ "AUCWeighted", "Accuracy", "NormMacroRecall", "AveragePrecisionScoreWeighted", and
+ "PrecisionScoreWeighted".
+ :vartype primary_metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationPrimaryMetrics
"""
_validation = {
@@ -9812,8 +10441,8 @@ def __init__(
model_settings: Optional["_models.ImageModelSettingsClassification"] = None,
search_space: Optional[List["_models.ImageModelDistributionSettingsClassification"]] = None,
primary_metric: Optional[Union[str, "_models.ClassificationPrimaryMetrics"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -9875,47 +10504,48 @@ def __init__(
class ImageClassificationMultilabel(
ImageClassificationBase, AutoMLVertical
): # pylint: disable=too-many-instance-attributes
- """Image Classification Multilabel. Multi-label image classification is used when an image could have one or more labels
+ """Image Classification Multilabel. Multi-label image classification is used when an image could
+ have one or more labels
from a set of labels - e.g. an image could be labeled with both 'cat' and 'dog'.
- All required parameters must be populated in order to send to Azure.
+ All required parameters must be populated in order to send to Azure.
- :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
- "Warning", "Error", and "Critical".
- :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
- :ivar target_column_name: Target column name: This is prediction values column.
- Also known as label column name in context of classification tasks.
- :vartype target_column_name: str
- :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
- "Classification", "Regression", "Forecasting", "ImageClassification",
- "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
- "TextClassification", "TextClassificationMultilabel", and "TextNER".
- :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
- :ivar training_data: [Required] Training data input. Required.
- :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
- :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
- :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
- validation purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype validation_data_size: float
- :ivar model_settings: Settings used for training the model.
- :vartype model_settings:
- ~azure.mgmt.machinelearningservices.models.ImageModelSettingsClassification
- :ivar search_space: Search space for sampling different combinations of models and their
- hyperparameters.
- :vartype search_space:
- list[~azure.mgmt.machinelearningservices.models.ImageModelDistributionSettingsClassification]
- :ivar primary_metric: Primary metric to optimize for this task. Known values are:
- "AUCWeighted", "Accuracy", "NormMacroRecall", "AveragePrecisionScoreWeighted",
- "PrecisionScoreWeighted", and "IOU".
- :vartype primary_metric: str or
- ~azure.mgmt.machinelearningservices.models.ClassificationMultilabelPrimaryMetrics
+ :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
+ "Warning", "Error", and "Critical".
+ :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
+ :ivar target_column_name: Target column name: This is prediction values column.
+ Also known as label column name in context of classification tasks.
+ :vartype target_column_name: str
+ :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
+ "Classification", "Regression", "Forecasting", "ImageClassification",
+ "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
+ "TextClassification", "TextClassificationMultilabel", and "TextNER".
+ :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
+ :ivar training_data: [Required] Training data input. Required.
+ :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
+ :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
+ :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
+ validation purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype validation_data_size: float
+ :ivar model_settings: Settings used for training the model.
+ :vartype model_settings:
+ ~azure.mgmt.machinelearningservices.models.ImageModelSettingsClassification
+ :ivar search_space: Search space for sampling different combinations of models and their
+ hyperparameters.
+ :vartype search_space:
+ list[~azure.mgmt.machinelearningservices.models.ImageModelDistributionSettingsClassification]
+ :ivar primary_metric: Primary metric to optimize for this task. Known values are:
+ "AUCWeighted", "Accuracy", "NormMacroRecall", "AveragePrecisionScoreWeighted",
+ "PrecisionScoreWeighted", and "IOU".
+ :vartype primary_metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationMultilabelPrimaryMetrics
"""
_validation = {
@@ -9951,8 +10581,8 @@ def __init__(
model_settings: Optional["_models.ImageModelSettingsClassification"] = None,
search_space: Optional[List["_models.ImageModelDistributionSettingsClassification"]] = None,
primary_metric: Optional[Union[str, "_models.ClassificationMultilabelPrimaryMetrics"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -10058,8 +10688,8 @@ def __init__(
validation_data_size: Optional[float] = None,
model_settings: Optional["_models.ImageModelSettingsObjectDetection"] = None,
search_space: Optional[List["_models.ImageModelDistributionSettingsObjectDetection"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword limit_settings: [Required] Limit settings for the AutoML job. Required.
:paramtype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
@@ -10094,68 +10724,69 @@ def __init__(
class ImageInstanceSegmentation(
ImageObjectDetectionBase, AutoMLVertical
): # pylint: disable=too-many-instance-attributes
- """Image Instance Segmentation. Instance segmentation is used to identify objects in an image at the pixel level,
+ """Image Instance Segmentation. Instance segmentation is used to identify objects in an image at
+ the pixel level,
drawing a polygon around each object in the image.
- All required parameters must be populated in order to send to Azure.
-
- :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
- "Warning", "Error", and "Critical".
- :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
- :ivar target_column_name: Target column name: This is prediction values column.
- Also known as label column name in context of classification tasks.
- :vartype target_column_name: str
- :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
- "Classification", "Regression", "Forecasting", "ImageClassification",
- "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
- "TextClassification", "TextClassificationMultilabel", and "TextNER".
- :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
- :ivar training_data: [Required] Training data input. Required.
- :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
- :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
- :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
- validation purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype validation_data_size: float
- :ivar model_settings: Settings used for training the model.
- :vartype model_settings:
- ~azure.mgmt.machinelearningservices.models.ImageModelSettingsObjectDetection
- :ivar search_space: Search space for sampling different combinations of models and their
- hyperparameters.
- :vartype search_space:
- list[~azure.mgmt.machinelearningservices.models.ImageModelDistributionSettingsObjectDetection]
- :ivar primary_metric: Primary metric to optimize for this task. "MeanAveragePrecision"
- :vartype primary_metric: str or
- ~azure.mgmt.machinelearningservices.models.InstanceSegmentationPrimaryMetrics
- """
-
- _validation = {
- "task_type": {"required": True},
- "training_data": {"required": True},
- "limit_settings": {"required": True},
- }
-
- _attribute_map = {
- "log_verbosity": {"key": "logVerbosity", "type": "str"},
- "target_column_name": {"key": "targetColumnName", "type": "str"},
- "task_type": {"key": "taskType", "type": "str"},
- "training_data": {"key": "trainingData", "type": "MLTableJobInput"},
- "limit_settings": {"key": "limitSettings", "type": "ImageLimitSettings"},
- "sweep_settings": {"key": "sweepSettings", "type": "ImageSweepSettings"},
- "validation_data": {"key": "validationData", "type": "MLTableJobInput"},
- "validation_data_size": {"key": "validationDataSize", "type": "float"},
- "model_settings": {"key": "modelSettings", "type": "ImageModelSettingsObjectDetection"},
- "search_space": {"key": "searchSpace", "type": "[ImageModelDistributionSettingsObjectDetection]"},
- "primary_metric": {"key": "primaryMetric", "type": "str"},
- }
+ All required parameters must be populated in order to send to Azure.
- def __init__(
+ :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
+ "Warning", "Error", and "Critical".
+ :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
+ :ivar target_column_name: Target column name: This is prediction values column.
+ Also known as label column name in context of classification tasks.
+ :vartype target_column_name: str
+ :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
+ "Classification", "Regression", "Forecasting", "ImageClassification",
+ "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
+ "TextClassification", "TextClassificationMultilabel", and "TextNER".
+ :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
+ :ivar training_data: [Required] Training data input. Required.
+ :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
+ :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
+ :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
+ validation purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype validation_data_size: float
+ :ivar model_settings: Settings used for training the model.
+ :vartype model_settings:
+ ~azure.mgmt.machinelearningservices.models.ImageModelSettingsObjectDetection
+ :ivar search_space: Search space for sampling different combinations of models and their
+ hyperparameters.
+ :vartype search_space:
+ list[~azure.mgmt.machinelearningservices.models.ImageModelDistributionSettingsObjectDetection]
+ :ivar primary_metric: Primary metric to optimize for this task. "MeanAveragePrecision"
+ :vartype primary_metric: str or
+ ~azure.mgmt.machinelearningservices.models.InstanceSegmentationPrimaryMetrics
+ """
+
+ _validation = {
+ "task_type": {"required": True},
+ "training_data": {"required": True},
+ "limit_settings": {"required": True},
+ }
+
+ _attribute_map = {
+ "log_verbosity": {"key": "logVerbosity", "type": "str"},
+ "target_column_name": {"key": "targetColumnName", "type": "str"},
+ "task_type": {"key": "taskType", "type": "str"},
+ "training_data": {"key": "trainingData", "type": "MLTableJobInput"},
+ "limit_settings": {"key": "limitSettings", "type": "ImageLimitSettings"},
+ "sweep_settings": {"key": "sweepSettings", "type": "ImageSweepSettings"},
+ "validation_data": {"key": "validationData", "type": "MLTableJobInput"},
+ "validation_data_size": {"key": "validationDataSize", "type": "float"},
+ "model_settings": {"key": "modelSettings", "type": "ImageModelSettingsObjectDetection"},
+ "search_space": {"key": "searchSpace", "type": "[ImageModelDistributionSettingsObjectDetection]"},
+ "primary_metric": {"key": "primaryMetric", "type": "str"},
+ }
+
+ def __init__(
self,
*,
training_data: "_models.MLTableJobInput",
@@ -10168,8 +10799,8 @@ def __init__(
model_settings: Optional["_models.ImageModelSettingsObjectDetection"] = None,
search_space: Optional[List["_models.ImageModelDistributionSettingsObjectDetection"]] = None,
primary_metric: Optional[Union[str, "_models.InstanceSegmentationPrimaryMetrics"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -10244,8 +10875,8 @@ class ImageLimitSettings(_serialization.Model):
}
def __init__(
- self, *, max_concurrent_trials: int = 1, max_trials: int = 1, timeout: datetime.timedelta = "P7D", **kwargs
- ):
+ self, *, max_concurrent_trials: int = 1, max_trials: int = 1, timeout: datetime.timedelta = "P7D", **kwargs: Any
+ ) -> None:
"""
:keyword max_concurrent_trials: Maximum number of concurrent AutoML iterations.
:paramtype max_concurrent_trials: int
@@ -10260,101 +10891,145 @@ def __init__(
self.timeout = timeout
+class ImageMetadata(_serialization.Model):
+ """Returns metadata about the operating system image for this compute instance.
+
+ :ivar current_image_version: Specifies the current operating system image version this compute
+ instance is running on.
+ :vartype current_image_version: str
+ :ivar latest_image_version: Specifies the latest available operating system image version.
+ :vartype latest_image_version: str
+ :ivar is_latest_os_image_version: Specifies whether this compute instance is running on the
+ latest operating system image.
+ :vartype is_latest_os_image_version: bool
+ """
+
+ _attribute_map = {
+ "current_image_version": {"key": "currentImageVersion", "type": "str"},
+ "latest_image_version": {"key": "latestImageVersion", "type": "str"},
+ "is_latest_os_image_version": {"key": "isLatestOsImageVersion", "type": "bool"},
+ }
+
+ def __init__(
+ self,
+ *,
+ current_image_version: Optional[str] = None,
+ latest_image_version: Optional[str] = None,
+ is_latest_os_image_version: Optional[bool] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword current_image_version: Specifies the current operating system image version this
+ compute instance is running on.
+ :paramtype current_image_version: str
+ :keyword latest_image_version: Specifies the latest available operating system image version.
+ :paramtype latest_image_version: str
+ :keyword is_latest_os_image_version: Specifies whether this compute instance is running on the
+ latest operating system image.
+ :paramtype is_latest_os_image_version: bool
+ """
+ super().__init__(**kwargs)
+ self.current_image_version = current_image_version
+ self.latest_image_version = latest_image_version
+ self.is_latest_os_image_version = is_latest_os_image_version
+
+
class ImageModelDistributionSettings(_serialization.Model): # pylint: disable=too-many-instance-attributes
"""Distribution expressions to sweep over values of model settings.
:code:`
Some examples are:
-
+ ```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
- `
- All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
+ ````
+ All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ...,
+ valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
- :vartype ams_gradient: str
- :ivar augmentations: Settings for using Augmentations.
- :vartype augmentations: str
- :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta1: str
- :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta2: str
- :ivar distributed: Whether to use distributer training.
- :vartype distributed: str
- :ivar early_stopping: Enable early stopping logic during training.
- :vartype early_stopping: str
- :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
- primary metric improvement
- is tracked for early stopping. Must be a positive integer.
- :vartype early_stopping_delay: str
- :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
- primary metric improvement before
- the run is stopped. Must be a positive integer.
- :vartype early_stopping_patience: str
- :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
- :vartype enable_onnx_normalization: str
- :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
- be a positive integer.
- :vartype evaluation_frequency: str
- :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
- "GradAccumulationStep" steps without
- updating the model weights while accumulating the gradients of those steps, and then using
- the accumulated gradients to compute the weight updates. Must be a positive integer.
- :vartype gradient_accumulation_step: str
- :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
- For instance, passing 2 as value for 'seresnext' means
- freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
- please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype layers_to_freeze: str
- :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
- :vartype learning_rate: str
- :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
- 'step'.
- :vartype learning_rate_scheduler: str
- :ivar model_name: Name of the model to use for training.
- For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype model_name: str
- :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
- :vartype momentum: str
- :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
- :vartype nesterov: str
- :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
- :vartype number_of_epochs: str
- :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
- :vartype number_of_workers: str
- :ivar optimizer: Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.
- :vartype optimizer: str
- :ivar random_seed: Random seed to be used when using deterministic training.
- :vartype random_seed: str
- :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
- the range [0, 1].
- :vartype step_lr_gamma: str
- :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
- positive integer.
- :vartype step_lr_step_size: str
- :ivar training_batch_size: Training batch size. Must be a positive integer.
- :vartype training_batch_size: str
- :ivar validation_batch_size: Validation batch size. Must be a positive integer.
- :vartype validation_batch_size: str
- :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
- 'warmup_cosine'. Must be a float in the range [0, 1].
- :vartype warmup_cosine_lr_cycles: str
- :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
- 'warmup_cosine'. Must be a positive integer.
- :vartype warmup_cosine_lr_warmup_epochs: str
- :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
- a float in the range[0, 1].
- :vartype weight_decay: str
+ :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
+ :vartype ams_gradient: str
+ :ivar augmentations: Settings for using Augmentations.
+ :vartype augmentations: str
+ :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta1: str
+ :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta2: str
+ :ivar distributed: Whether to use distributer training.
+ :vartype distributed: str
+ :ivar early_stopping: Enable early stopping logic during training.
+ :vartype early_stopping: str
+ :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
+ primary metric improvement
+ is tracked for early stopping. Must be a positive integer.
+ :vartype early_stopping_delay: str
+ :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
+ primary metric improvement before
+ the run is stopped. Must be a positive integer.
+ :vartype early_stopping_patience: str
+ :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
+ :vartype enable_onnx_normalization: str
+ :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
+ be a positive integer.
+ :vartype evaluation_frequency: str
+ :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
+ "GradAccumulationStep" steps without
+ updating the model weights while accumulating the gradients of those steps, and then using
+ the accumulated gradients to compute the weight updates. Must be a positive integer.
+ :vartype gradient_accumulation_step: str
+ :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
+ For instance, passing 2 as value for 'seresnext' means
+ freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
+ please
+ see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype layers_to_freeze: str
+ :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
+ :vartype learning_rate: str
+ :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
+ 'step'.
+ :vartype learning_rate_scheduler: str
+ :ivar model_name: Name of the model to use for training.
+ For more information on the available models please visit the official documentation:
+ https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype model_name: str
+ :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
+ :vartype momentum: str
+ :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
+ :vartype nesterov: str
+ :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
+ :vartype number_of_epochs: str
+ :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
+ :vartype number_of_workers: str
+ :ivar optimizer: Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.
+ :vartype optimizer: str
+ :ivar random_seed: Random seed to be used when using deterministic training.
+ :vartype random_seed: str
+ :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
+ the range [0, 1].
+ :vartype step_lr_gamma: str
+ :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
+ positive integer.
+ :vartype step_lr_step_size: str
+ :ivar training_batch_size: Training batch size. Must be a positive integer.
+ :vartype training_batch_size: str
+ :ivar validation_batch_size: Validation batch size. Must be a positive integer.
+ :vartype validation_batch_size: str
+ :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
+ 'warmup_cosine'. Must be a float in the range [0, 1].
+ :vartype warmup_cosine_lr_cycles: str
+ :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
+ 'warmup_cosine'. Must be a positive integer.
+ :vartype warmup_cosine_lr_warmup_epochs: str
+ :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
+ a float in the range[0, 1].
+ :vartype weight_decay: str
"""
_attribute_map = {
@@ -10419,8 +11094,8 @@ def __init__( # pylint: disable=too-many-locals
warmup_cosine_lr_cycles: Optional[str] = None,
warmup_cosine_lr_warmup_epochs: Optional[str] = None,
weight_decay: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:paramtype ams_gradient: str
@@ -10541,107 +11216,107 @@ class ImageModelDistributionSettingsClassification(
:code:`
Some examples are:
-
+ ```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
- `
+ ````
For more details on how to compose distribution expressions please check the documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
- :vartype ams_gradient: str
- :ivar augmentations: Settings for using Augmentations.
- :vartype augmentations: str
- :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta1: str
- :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta2: str
- :ivar distributed: Whether to use distributer training.
- :vartype distributed: str
- :ivar early_stopping: Enable early stopping logic during training.
- :vartype early_stopping: str
- :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
- primary metric improvement
- is tracked for early stopping. Must be a positive integer.
- :vartype early_stopping_delay: str
- :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
- primary metric improvement before
- the run is stopped. Must be a positive integer.
- :vartype early_stopping_patience: str
- :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
- :vartype enable_onnx_normalization: str
- :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
- be a positive integer.
- :vartype evaluation_frequency: str
- :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
- "GradAccumulationStep" steps without
- updating the model weights while accumulating the gradients of those steps, and then using
- the accumulated gradients to compute the weight updates. Must be a positive integer.
- :vartype gradient_accumulation_step: str
- :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
- For instance, passing 2 as value for 'seresnext' means
- freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
- please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype layers_to_freeze: str
- :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
- :vartype learning_rate: str
- :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
- 'step'.
- :vartype learning_rate_scheduler: str
- :ivar model_name: Name of the model to use for training.
- For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype model_name: str
- :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
- :vartype momentum: str
- :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
- :vartype nesterov: str
- :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
- :vartype number_of_epochs: str
- :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
- :vartype number_of_workers: str
- :ivar optimizer: Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.
- :vartype optimizer: str
- :ivar random_seed: Random seed to be used when using deterministic training.
- :vartype random_seed: str
- :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
- the range [0, 1].
- :vartype step_lr_gamma: str
- :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
- positive integer.
- :vartype step_lr_step_size: str
- :ivar training_batch_size: Training batch size. Must be a positive integer.
- :vartype training_batch_size: str
- :ivar validation_batch_size: Validation batch size. Must be a positive integer.
- :vartype validation_batch_size: str
- :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
- 'warmup_cosine'. Must be a float in the range [0, 1].
- :vartype warmup_cosine_lr_cycles: str
- :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
- 'warmup_cosine'. Must be a positive integer.
- :vartype warmup_cosine_lr_warmup_epochs: str
- :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
- a float in the range[0, 1].
- :vartype weight_decay: str
- :ivar training_crop_size: Image crop size that is input to the neural network for the training
- dataset. Must be a positive integer.
- :vartype training_crop_size: str
- :ivar validation_crop_size: Image crop size that is input to the neural network for the
- validation dataset. Must be a positive integer.
- :vartype validation_crop_size: str
- :ivar validation_resize_size: Image size to which to resize before cropping for validation
- dataset. Must be a positive integer.
- :vartype validation_resize_size: str
- :ivar weighted_loss: Weighted loss. The accepted values are 0 for no weighted loss.
- 1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be
- 0 or 1 or 2.
- :vartype weighted_loss: str
+ :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
+ :vartype ams_gradient: str
+ :ivar augmentations: Settings for using Augmentations.
+ :vartype augmentations: str
+ :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta1: str
+ :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta2: str
+ :ivar distributed: Whether to use distributer training.
+ :vartype distributed: str
+ :ivar early_stopping: Enable early stopping logic during training.
+ :vartype early_stopping: str
+ :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
+ primary metric improvement
+ is tracked for early stopping. Must be a positive integer.
+ :vartype early_stopping_delay: str
+ :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
+ primary metric improvement before
+ the run is stopped. Must be a positive integer.
+ :vartype early_stopping_patience: str
+ :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
+ :vartype enable_onnx_normalization: str
+ :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
+ be a positive integer.
+ :vartype evaluation_frequency: str
+ :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
+ "GradAccumulationStep" steps without
+ updating the model weights while accumulating the gradients of those steps, and then using
+ the accumulated gradients to compute the weight updates. Must be a positive integer.
+ :vartype gradient_accumulation_step: str
+ :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
+ For instance, passing 2 as value for 'seresnext' means
+ freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
+ please
+ see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype layers_to_freeze: str
+ :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
+ :vartype learning_rate: str
+ :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
+ 'step'.
+ :vartype learning_rate_scheduler: str
+ :ivar model_name: Name of the model to use for training.
+ For more information on the available models please visit the official documentation:
+ https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype model_name: str
+ :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
+ :vartype momentum: str
+ :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
+ :vartype nesterov: str
+ :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
+ :vartype number_of_epochs: str
+ :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
+ :vartype number_of_workers: str
+ :ivar optimizer: Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.
+ :vartype optimizer: str
+ :ivar random_seed: Random seed to be used when using deterministic training.
+ :vartype random_seed: str
+ :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
+ the range [0, 1].
+ :vartype step_lr_gamma: str
+ :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
+ positive integer.
+ :vartype step_lr_step_size: str
+ :ivar training_batch_size: Training batch size. Must be a positive integer.
+ :vartype training_batch_size: str
+ :ivar validation_batch_size: Validation batch size. Must be a positive integer.
+ :vartype validation_batch_size: str
+ :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
+ 'warmup_cosine'. Must be a float in the range [0, 1].
+ :vartype warmup_cosine_lr_cycles: str
+ :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
+ 'warmup_cosine'. Must be a positive integer.
+ :vartype warmup_cosine_lr_warmup_epochs: str
+ :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
+ a float in the range[0, 1].
+ :vartype weight_decay: str
+ :ivar training_crop_size: Image crop size that is input to the neural network for the training
+ dataset. Must be a positive integer.
+ :vartype training_crop_size: str
+ :ivar validation_crop_size: Image crop size that is input to the neural network for the
+ validation dataset. Must be a positive integer.
+ :vartype validation_crop_size: str
+ :ivar validation_resize_size: Image size to which to resize before cropping for validation
+ dataset. Must be a positive integer.
+ :vartype validation_resize_size: str
+ :ivar weighted_loss: Weighted loss. The accepted values are 0 for no weighted loss.
+ 1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be
+ 0 or 1 or 2.
+ :vartype weighted_loss: str
"""
_attribute_map = {
@@ -10714,8 +11389,8 @@ def __init__( # pylint: disable=too-many-locals
validation_crop_size: Optional[str] = None,
validation_resize_size: Optional[str] = None,
weighted_loss: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:paramtype ams_gradient: str
@@ -10855,146 +11530,146 @@ class ImageModelDistributionSettingsObjectDetection(
:code:`
Some examples are:
-
+ ```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
- `
+ ````
For more details on how to compose distribution expressions please check the documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
- :vartype ams_gradient: str
- :ivar augmentations: Settings for using Augmentations.
- :vartype augmentations: str
- :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta1: str
- :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta2: str
- :ivar distributed: Whether to use distributer training.
- :vartype distributed: str
- :ivar early_stopping: Enable early stopping logic during training.
- :vartype early_stopping: str
- :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
- primary metric improvement
- is tracked for early stopping. Must be a positive integer.
- :vartype early_stopping_delay: str
- :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
- primary metric improvement before
- the run is stopped. Must be a positive integer.
- :vartype early_stopping_patience: str
- :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
- :vartype enable_onnx_normalization: str
- :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
- be a positive integer.
- :vartype evaluation_frequency: str
- :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
- "GradAccumulationStep" steps without
- updating the model weights while accumulating the gradients of those steps, and then using
- the accumulated gradients to compute the weight updates. Must be a positive integer.
- :vartype gradient_accumulation_step: str
- :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
- For instance, passing 2 as value for 'seresnext' means
- freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
- please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype layers_to_freeze: str
- :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
- :vartype learning_rate: str
- :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
- 'step'.
- :vartype learning_rate_scheduler: str
- :ivar model_name: Name of the model to use for training.
- For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype model_name: str
- :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
- :vartype momentum: str
- :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
- :vartype nesterov: str
- :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
- :vartype number_of_epochs: str
- :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
- :vartype number_of_workers: str
- :ivar optimizer: Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.
- :vartype optimizer: str
- :ivar random_seed: Random seed to be used when using deterministic training.
- :vartype random_seed: str
- :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
- the range [0, 1].
- :vartype step_lr_gamma: str
- :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
- positive integer.
- :vartype step_lr_step_size: str
- :ivar training_batch_size: Training batch size. Must be a positive integer.
- :vartype training_batch_size: str
- :ivar validation_batch_size: Validation batch size. Must be a positive integer.
- :vartype validation_batch_size: str
- :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
- 'warmup_cosine'. Must be a float in the range [0, 1].
- :vartype warmup_cosine_lr_cycles: str
- :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
- 'warmup_cosine'. Must be a positive integer.
- :vartype warmup_cosine_lr_warmup_epochs: str
- :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
- a float in the range[0, 1].
- :vartype weight_decay: str
- :ivar box_detections_per_image: Maximum number of detections per image, for all classes. Must
- be a positive integer.
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype box_detections_per_image: str
- :ivar box_score_threshold: During inference, only return proposals with a classification score
- greater than
- BoxScoreThreshold. Must be a float in the range[0, 1].
- :vartype box_score_threshold: str
- :ivar image_size: Image size for train and validation. Must be a positive integer.
- Note: The training run may get into CUDA OOM if the size is too big.
- Note: This settings is only supported for the 'yolov5' algorithm.
- :vartype image_size: str
- :ivar max_size: Maximum size of the image to be rescaled before feeding it to the backbone.
- Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype max_size: str
- :ivar min_size: Minimum size of the image to be rescaled before feeding it to the backbone.
- Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype min_size: str
- :ivar model_size: Model size. Must be 'small', 'medium', 'large', or 'xlarge'.
- Note: training run may get into CUDA OOM if the model size is too big.
- Note: This settings is only supported for the 'yolov5' algorithm.
- :vartype model_size: str
- :ivar multi_scale: Enable multi-scale image by varying image size by +/- 50%.
- Note: training run may get into CUDA OOM if no sufficient GPU memory.
- Note: This settings is only supported for the 'yolov5' algorithm.
- :vartype multi_scale: str
- :ivar nms_iou_threshold: IOU threshold used during inference in NMS post processing. Must be
- float in the range [0, 1].
- :vartype nms_iou_threshold: str
- :ivar tile_grid_size: The grid size to use for tiling each image. Note: TileGridSize must not
- be
- None to enable small object detection logic. A string containing two integers in mxn format.
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype tile_grid_size: str
- :ivar tile_overlap_ratio: Overlap ratio between adjacent tiles in each dimension. Must be float
- in the range [0, 1).
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype tile_overlap_ratio: str
- :ivar tile_predictions_nms_threshold: The IOU threshold to use to perform NMS while merging
- predictions from tiles and image.
- Used in validation/ inference. Must be float in the range [0, 1].
- Note: This settings is not supported for the 'yolov5' algorithm.
- NMS: Non-maximum suppression.
- :vartype tile_predictions_nms_threshold: str
- :ivar validation_iou_threshold: IOU threshold to use when computing validation metric. Must be
- float in the range [0, 1].
- :vartype validation_iou_threshold: str
- :ivar validation_metric_type: Metric computation method to use for validation metrics. Must be
- 'none', 'coco', 'voc', or 'coco_voc'.
- :vartype validation_metric_type: str
+ :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
+ :vartype ams_gradient: str
+ :ivar augmentations: Settings for using Augmentations.
+ :vartype augmentations: str
+ :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta1: str
+ :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta2: str
+ :ivar distributed: Whether to use distributer training.
+ :vartype distributed: str
+ :ivar early_stopping: Enable early stopping logic during training.
+ :vartype early_stopping: str
+ :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
+ primary metric improvement
+ is tracked for early stopping. Must be a positive integer.
+ :vartype early_stopping_delay: str
+ :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
+ primary metric improvement before
+ the run is stopped. Must be a positive integer.
+ :vartype early_stopping_patience: str
+ :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
+ :vartype enable_onnx_normalization: str
+ :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
+ be a positive integer.
+ :vartype evaluation_frequency: str
+ :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
+ "GradAccumulationStep" steps without
+ updating the model weights while accumulating the gradients of those steps, and then using
+ the accumulated gradients to compute the weight updates. Must be a positive integer.
+ :vartype gradient_accumulation_step: str
+ :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
+ For instance, passing 2 as value for 'seresnext' means
+ freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
+ please
+ see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype layers_to_freeze: str
+ :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
+ :vartype learning_rate: str
+ :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
+ 'step'.
+ :vartype learning_rate_scheduler: str
+ :ivar model_name: Name of the model to use for training.
+ For more information on the available models please visit the official documentation:
+ https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype model_name: str
+ :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
+ :vartype momentum: str
+ :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
+ :vartype nesterov: str
+ :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
+ :vartype number_of_epochs: str
+ :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
+ :vartype number_of_workers: str
+ :ivar optimizer: Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.
+ :vartype optimizer: str
+ :ivar random_seed: Random seed to be used when using deterministic training.
+ :vartype random_seed: str
+ :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
+ the range [0, 1].
+ :vartype step_lr_gamma: str
+ :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
+ positive integer.
+ :vartype step_lr_step_size: str
+ :ivar training_batch_size: Training batch size. Must be a positive integer.
+ :vartype training_batch_size: str
+ :ivar validation_batch_size: Validation batch size. Must be a positive integer.
+ :vartype validation_batch_size: str
+ :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
+ 'warmup_cosine'. Must be a float in the range [0, 1].
+ :vartype warmup_cosine_lr_cycles: str
+ :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
+ 'warmup_cosine'. Must be a positive integer.
+ :vartype warmup_cosine_lr_warmup_epochs: str
+ :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
+ a float in the range[0, 1].
+ :vartype weight_decay: str
+ :ivar box_detections_per_image: Maximum number of detections per image, for all classes. Must
+ be a positive integer.
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype box_detections_per_image: str
+ :ivar box_score_threshold: During inference, only return proposals with a classification score
+ greater than
+ BoxScoreThreshold. Must be a float in the range[0, 1].
+ :vartype box_score_threshold: str
+ :ivar image_size: Image size for train and validation. Must be a positive integer.
+ Note: The training run may get into CUDA OOM if the size is too big.
+ Note: This settings is only supported for the 'yolov5' algorithm.
+ :vartype image_size: str
+ :ivar max_size: Maximum size of the image to be rescaled before feeding it to the backbone.
+ Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype max_size: str
+ :ivar min_size: Minimum size of the image to be rescaled before feeding it to the backbone.
+ Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype min_size: str
+ :ivar model_size: Model size. Must be 'small', 'medium', 'large', or 'xlarge'.
+ Note: training run may get into CUDA OOM if the model size is too big.
+ Note: This settings is only supported for the 'yolov5' algorithm.
+ :vartype model_size: str
+ :ivar multi_scale: Enable multi-scale image by varying image size by +/- 50%.
+ Note: training run may get into CUDA OOM if no sufficient GPU memory.
+ Note: This settings is only supported for the 'yolov5' algorithm.
+ :vartype multi_scale: str
+ :ivar nms_iou_threshold: IOU threshold used during inference in NMS post processing. Must be
+ float in the range [0, 1].
+ :vartype nms_iou_threshold: str
+ :ivar tile_grid_size: The grid size to use for tiling each image. Note: TileGridSize must not
+ be
+ None to enable small object detection logic. A string containing two integers in mxn format.
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype tile_grid_size: str
+ :ivar tile_overlap_ratio: Overlap ratio between adjacent tiles in each dimension. Must be float
+ in the range [0, 1).
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype tile_overlap_ratio: str
+ :ivar tile_predictions_nms_threshold: The IOU threshold to use to perform NMS while merging
+ predictions from tiles and image.
+ Used in validation/ inference. Must be float in the range [0, 1].
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ NMS: Non-maximum suppression.
+ :vartype tile_predictions_nms_threshold: str
+ :ivar validation_iou_threshold: IOU threshold to use when computing validation metric. Must be
+ float in the range [0, 1].
+ :vartype validation_iou_threshold: str
+ :ivar validation_metric_type: Metric computation method to use for validation metrics. Must be
+ 'none', 'coco', 'voc', or 'coco_voc'.
+ :vartype validation_metric_type: str
"""
_attribute_map = {
@@ -11085,8 +11760,8 @@ def __init__( # pylint: disable=too-many-locals
tile_predictions_nms_threshold: Optional[str] = None,
validation_iou_threshold: Optional[str] = None,
validation_metric_type: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:paramtype ams_gradient: str
@@ -11272,94 +11947,94 @@ class ImageModelSettings(_serialization.Model): # pylint: disable=too-many-inst
For more information on the available settings please visit the official documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :ivar advanced_settings: Settings for advanced scenarios.
- :vartype advanced_settings: str
- :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
- :vartype ams_gradient: bool
- :ivar augmentations: Settings for using Augmentations.
- :vartype augmentations: str
- :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta1: float
- :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta2: float
- :ivar checkpoint_frequency: Frequency to store model checkpoints. Must be a positive integer.
- :vartype checkpoint_frequency: int
- :ivar checkpoint_model: The pretrained checkpoint model for incremental training.
- :vartype checkpoint_model: ~azure.mgmt.machinelearningservices.models.MLFlowModelJobInput
- :ivar checkpoint_run_id: The id of a previous run that has a pretrained checkpoint for
- incremental training.
- :vartype checkpoint_run_id: str
- :ivar distributed: Whether to use distributed training.
- :vartype distributed: bool
- :ivar early_stopping: Enable early stopping logic during training.
- :vartype early_stopping: bool
- :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
- primary metric improvement
- is tracked for early stopping. Must be a positive integer.
- :vartype early_stopping_delay: int
- :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
- primary metric improvement before
- the run is stopped. Must be a positive integer.
- :vartype early_stopping_patience: int
- :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
- :vartype enable_onnx_normalization: bool
- :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
- be a positive integer.
- :vartype evaluation_frequency: int
- :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
- "GradAccumulationStep" steps without
- updating the model weights while accumulating the gradients of those steps, and then using
- the accumulated gradients to compute the weight updates. Must be a positive integer.
- :vartype gradient_accumulation_step: int
- :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
- For instance, passing 2 as value for 'seresnext' means
- freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
- please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype layers_to_freeze: int
- :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
- :vartype learning_rate: float
- :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
- 'step'. Known values are: "None", "WarmupCosine", and "Step".
- :vartype learning_rate_scheduler: str or
- ~azure.mgmt.machinelearningservices.models.LearningRateScheduler
- :ivar model_name: Name of the model to use for training.
- For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype model_name: str
- :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
- :vartype momentum: float
- :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
- :vartype nesterov: bool
- :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
- :vartype number_of_epochs: int
- :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
- :vartype number_of_workers: int
- :ivar optimizer: Type of optimizer. Known values are: "None", "Sgd", "Adam", and "Adamw".
- :vartype optimizer: str or ~azure.mgmt.machinelearningservices.models.StochasticOptimizer
- :ivar random_seed: Random seed to be used when using deterministic training.
- :vartype random_seed: int
- :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
- the range [0, 1].
- :vartype step_lr_gamma: float
- :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
- positive integer.
- :vartype step_lr_step_size: int
- :ivar training_batch_size: Training batch size. Must be a positive integer.
- :vartype training_batch_size: int
- :ivar validation_batch_size: Validation batch size. Must be a positive integer.
- :vartype validation_batch_size: int
- :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
- 'warmup_cosine'. Must be a float in the range [0, 1].
- :vartype warmup_cosine_lr_cycles: float
- :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
- 'warmup_cosine'. Must be a positive integer.
- :vartype warmup_cosine_lr_warmup_epochs: int
- :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
- a float in the range[0, 1].
- :vartype weight_decay: float
+ :ivar advanced_settings: Settings for advanced scenarios.
+ :vartype advanced_settings: str
+ :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
+ :vartype ams_gradient: bool
+ :ivar augmentations: Settings for using Augmentations.
+ :vartype augmentations: str
+ :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta1: float
+ :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta2: float
+ :ivar checkpoint_frequency: Frequency to store model checkpoints. Must be a positive integer.
+ :vartype checkpoint_frequency: int
+ :ivar checkpoint_model: The pretrained checkpoint model for incremental training.
+ :vartype checkpoint_model: ~azure.mgmt.machinelearningservices.models.MLFlowModelJobInput
+ :ivar checkpoint_run_id: The id of a previous run that has a pretrained checkpoint for
+ incremental training.
+ :vartype checkpoint_run_id: str
+ :ivar distributed: Whether to use distributed training.
+ :vartype distributed: bool
+ :ivar early_stopping: Enable early stopping logic during training.
+ :vartype early_stopping: bool
+ :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
+ primary metric improvement
+ is tracked for early stopping. Must be a positive integer.
+ :vartype early_stopping_delay: int
+ :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
+ primary metric improvement before
+ the run is stopped. Must be a positive integer.
+ :vartype early_stopping_patience: int
+ :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
+ :vartype enable_onnx_normalization: bool
+ :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
+ be a positive integer.
+ :vartype evaluation_frequency: int
+ :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
+ "GradAccumulationStep" steps without
+ updating the model weights while accumulating the gradients of those steps, and then using
+ the accumulated gradients to compute the weight updates. Must be a positive integer.
+ :vartype gradient_accumulation_step: int
+ :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
+ For instance, passing 2 as value for 'seresnext' means
+ freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
+ please
+ see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype layers_to_freeze: int
+ :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
+ :vartype learning_rate: float
+ :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
+ 'step'. Known values are: "None", "WarmupCosine", and "Step".
+ :vartype learning_rate_scheduler: str or
+ ~azure.mgmt.machinelearningservices.models.LearningRateScheduler
+ :ivar model_name: Name of the model to use for training.
+ For more information on the available models please visit the official documentation:
+ https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype model_name: str
+ :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
+ :vartype momentum: float
+ :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
+ :vartype nesterov: bool
+ :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
+ :vartype number_of_epochs: int
+ :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
+ :vartype number_of_workers: int
+ :ivar optimizer: Type of optimizer. Known values are: "None", "Sgd", "Adam", and "Adamw".
+ :vartype optimizer: str or ~azure.mgmt.machinelearningservices.models.StochasticOptimizer
+ :ivar random_seed: Random seed to be used when using deterministic training.
+ :vartype random_seed: int
+ :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
+ the range [0, 1].
+ :vartype step_lr_gamma: float
+ :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
+ positive integer.
+ :vartype step_lr_step_size: int
+ :ivar training_batch_size: Training batch size. Must be a positive integer.
+ :vartype training_batch_size: int
+ :ivar validation_batch_size: Validation batch size. Must be a positive integer.
+ :vartype validation_batch_size: int
+ :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
+ 'warmup_cosine'. Must be a float in the range [0, 1].
+ :vartype warmup_cosine_lr_cycles: float
+ :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
+ 'warmup_cosine'. Must be a positive integer.
+ :vartype warmup_cosine_lr_warmup_epochs: int
+ :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
+ a float in the range[0, 1].
+ :vartype weight_decay: float
"""
_attribute_map = {
@@ -11432,8 +12107,8 @@ def __init__( # pylint: disable=too-many-locals
warmup_cosine_lr_cycles: Optional[float] = None,
warmup_cosine_lr_warmup_epochs: Optional[int] = None,
weight_decay: Optional[float] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword advanced_settings: Settings for advanced scenarios.
:paramtype advanced_settings: str
@@ -11567,107 +12242,107 @@ class ImageModelSettingsClassification(ImageModelSettings): # pylint: disable=t
For more information on the available settings please visit the official documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :ivar advanced_settings: Settings for advanced scenarios.
- :vartype advanced_settings: str
- :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
- :vartype ams_gradient: bool
- :ivar augmentations: Settings for using Augmentations.
- :vartype augmentations: str
- :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta1: float
- :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta2: float
- :ivar checkpoint_frequency: Frequency to store model checkpoints. Must be a positive integer.
- :vartype checkpoint_frequency: int
- :ivar checkpoint_model: The pretrained checkpoint model for incremental training.
- :vartype checkpoint_model: ~azure.mgmt.machinelearningservices.models.MLFlowModelJobInput
- :ivar checkpoint_run_id: The id of a previous run that has a pretrained checkpoint for
- incremental training.
- :vartype checkpoint_run_id: str
- :ivar distributed: Whether to use distributed training.
- :vartype distributed: bool
- :ivar early_stopping: Enable early stopping logic during training.
- :vartype early_stopping: bool
- :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
- primary metric improvement
- is tracked for early stopping. Must be a positive integer.
- :vartype early_stopping_delay: int
- :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
- primary metric improvement before
- the run is stopped. Must be a positive integer.
- :vartype early_stopping_patience: int
- :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
- :vartype enable_onnx_normalization: bool
- :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
- be a positive integer.
- :vartype evaluation_frequency: int
- :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
- "GradAccumulationStep" steps without
- updating the model weights while accumulating the gradients of those steps, and then using
- the accumulated gradients to compute the weight updates. Must be a positive integer.
- :vartype gradient_accumulation_step: int
- :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
- For instance, passing 2 as value for 'seresnext' means
- freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
- please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype layers_to_freeze: int
- :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
- :vartype learning_rate: float
- :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
- 'step'. Known values are: "None", "WarmupCosine", and "Step".
- :vartype learning_rate_scheduler: str or
- ~azure.mgmt.machinelearningservices.models.LearningRateScheduler
- :ivar model_name: Name of the model to use for training.
- For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype model_name: str
- :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
- :vartype momentum: float
- :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
- :vartype nesterov: bool
- :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
- :vartype number_of_epochs: int
- :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
- :vartype number_of_workers: int
- :ivar optimizer: Type of optimizer. Known values are: "None", "Sgd", "Adam", and "Adamw".
- :vartype optimizer: str or ~azure.mgmt.machinelearningservices.models.StochasticOptimizer
- :ivar random_seed: Random seed to be used when using deterministic training.
- :vartype random_seed: int
- :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
- the range [0, 1].
- :vartype step_lr_gamma: float
- :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
- positive integer.
- :vartype step_lr_step_size: int
- :ivar training_batch_size: Training batch size. Must be a positive integer.
- :vartype training_batch_size: int
- :ivar validation_batch_size: Validation batch size. Must be a positive integer.
- :vartype validation_batch_size: int
- :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
- 'warmup_cosine'. Must be a float in the range [0, 1].
- :vartype warmup_cosine_lr_cycles: float
- :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
- 'warmup_cosine'. Must be a positive integer.
- :vartype warmup_cosine_lr_warmup_epochs: int
- :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
- a float in the range[0, 1].
- :vartype weight_decay: float
- :ivar training_crop_size: Image crop size that is input to the neural network for the training
- dataset. Must be a positive integer.
- :vartype training_crop_size: int
- :ivar validation_crop_size: Image crop size that is input to the neural network for the
- validation dataset. Must be a positive integer.
- :vartype validation_crop_size: int
- :ivar validation_resize_size: Image size to which to resize before cropping for validation
- dataset. Must be a positive integer.
- :vartype validation_resize_size: int
- :ivar weighted_loss: Weighted loss. The accepted values are 0 for no weighted loss.
- 1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be
- 0 or 1 or 2.
- :vartype weighted_loss: int
+ :ivar advanced_settings: Settings for advanced scenarios.
+ :vartype advanced_settings: str
+ :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
+ :vartype ams_gradient: bool
+ :ivar augmentations: Settings for using Augmentations.
+ :vartype augmentations: str
+ :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta1: float
+ :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta2: float
+ :ivar checkpoint_frequency: Frequency to store model checkpoints. Must be a positive integer.
+ :vartype checkpoint_frequency: int
+ :ivar checkpoint_model: The pretrained checkpoint model for incremental training.
+ :vartype checkpoint_model: ~azure.mgmt.machinelearningservices.models.MLFlowModelJobInput
+ :ivar checkpoint_run_id: The id of a previous run that has a pretrained checkpoint for
+ incremental training.
+ :vartype checkpoint_run_id: str
+ :ivar distributed: Whether to use distributed training.
+ :vartype distributed: bool
+ :ivar early_stopping: Enable early stopping logic during training.
+ :vartype early_stopping: bool
+ :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
+ primary metric improvement
+ is tracked for early stopping. Must be a positive integer.
+ :vartype early_stopping_delay: int
+ :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
+ primary metric improvement before
+ the run is stopped. Must be a positive integer.
+ :vartype early_stopping_patience: int
+ :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
+ :vartype enable_onnx_normalization: bool
+ :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
+ be a positive integer.
+ :vartype evaluation_frequency: int
+ :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
+ "GradAccumulationStep" steps without
+ updating the model weights while accumulating the gradients of those steps, and then using
+ the accumulated gradients to compute the weight updates. Must be a positive integer.
+ :vartype gradient_accumulation_step: int
+ :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
+ For instance, passing 2 as value for 'seresnext' means
+ freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
+ please
+ see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype layers_to_freeze: int
+ :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
+ :vartype learning_rate: float
+ :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
+ 'step'. Known values are: "None", "WarmupCosine", and "Step".
+ :vartype learning_rate_scheduler: str or
+ ~azure.mgmt.machinelearningservices.models.LearningRateScheduler
+ :ivar model_name: Name of the model to use for training.
+ For more information on the available models please visit the official documentation:
+ https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype model_name: str
+ :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
+ :vartype momentum: float
+ :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
+ :vartype nesterov: bool
+ :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
+ :vartype number_of_epochs: int
+ :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
+ :vartype number_of_workers: int
+ :ivar optimizer: Type of optimizer. Known values are: "None", "Sgd", "Adam", and "Adamw".
+ :vartype optimizer: str or ~azure.mgmt.machinelearningservices.models.StochasticOptimizer
+ :ivar random_seed: Random seed to be used when using deterministic training.
+ :vartype random_seed: int
+ :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
+ the range [0, 1].
+ :vartype step_lr_gamma: float
+ :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
+ positive integer.
+ :vartype step_lr_step_size: int
+ :ivar training_batch_size: Training batch size. Must be a positive integer.
+ :vartype training_batch_size: int
+ :ivar validation_batch_size: Validation batch size. Must be a positive integer.
+ :vartype validation_batch_size: int
+ :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
+ 'warmup_cosine'. Must be a float in the range [0, 1].
+ :vartype warmup_cosine_lr_cycles: float
+ :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
+ 'warmup_cosine'. Must be a positive integer.
+ :vartype warmup_cosine_lr_warmup_epochs: int
+ :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
+ a float in the range[0, 1].
+ :vartype weight_decay: float
+ :ivar training_crop_size: Image crop size that is input to the neural network for the training
+ dataset. Must be a positive integer.
+ :vartype training_crop_size: int
+ :ivar validation_crop_size: Image crop size that is input to the neural network for the
+ validation dataset. Must be a positive integer.
+ :vartype validation_crop_size: int
+ :ivar validation_resize_size: Image size to which to resize before cropping for validation
+ dataset. Must be a positive integer.
+ :vartype validation_resize_size: int
+ :ivar weighted_loss: Weighted loss. The accepted values are 0 for no weighted loss.
+ 1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be
+ 0 or 1 or 2.
+ :vartype weighted_loss: int
"""
_attribute_map = {
@@ -11748,8 +12423,8 @@ def __init__( # pylint: disable=too-many-locals
validation_crop_size: Optional[int] = None,
validation_resize_size: Optional[int] = None,
weighted_loss: Optional[int] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword advanced_settings: Settings for advanced scenarios.
:paramtype advanced_settings: str
@@ -11902,147 +12577,147 @@ class ImageModelSettingsObjectDetection(ImageModelSettings): # pylint: disable=
For more information on the available settings please visit the official documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :ivar advanced_settings: Settings for advanced scenarios.
- :vartype advanced_settings: str
- :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
- :vartype ams_gradient: bool
- :ivar augmentations: Settings for using Augmentations.
- :vartype augmentations: str
- :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta1: float
- :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
- [0, 1].
- :vartype beta2: float
- :ivar checkpoint_frequency: Frequency to store model checkpoints. Must be a positive integer.
- :vartype checkpoint_frequency: int
- :ivar checkpoint_model: The pretrained checkpoint model for incremental training.
- :vartype checkpoint_model: ~azure.mgmt.machinelearningservices.models.MLFlowModelJobInput
- :ivar checkpoint_run_id: The id of a previous run that has a pretrained checkpoint for
- incremental training.
- :vartype checkpoint_run_id: str
- :ivar distributed: Whether to use distributed training.
- :vartype distributed: bool
- :ivar early_stopping: Enable early stopping logic during training.
- :vartype early_stopping: bool
- :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
- primary metric improvement
- is tracked for early stopping. Must be a positive integer.
- :vartype early_stopping_delay: int
- :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
- primary metric improvement before
- the run is stopped. Must be a positive integer.
- :vartype early_stopping_patience: int
- :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
- :vartype enable_onnx_normalization: bool
- :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
- be a positive integer.
- :vartype evaluation_frequency: int
- :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
- "GradAccumulationStep" steps without
- updating the model weights while accumulating the gradients of those steps, and then using
- the accumulated gradients to compute the weight updates. Must be a positive integer.
- :vartype gradient_accumulation_step: int
- :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
- For instance, passing 2 as value for 'seresnext' means
- freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
- please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype layers_to_freeze: int
- :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
- :vartype learning_rate: float
- :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
- 'step'. Known values are: "None", "WarmupCosine", and "Step".
- :vartype learning_rate_scheduler: str or
- ~azure.mgmt.machinelearningservices.models.LearningRateScheduler
- :ivar model_name: Name of the model to use for training.
- For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
- :vartype model_name: str
- :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
- :vartype momentum: float
- :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
- :vartype nesterov: bool
- :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
- :vartype number_of_epochs: int
- :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
- :vartype number_of_workers: int
- :ivar optimizer: Type of optimizer. Known values are: "None", "Sgd", "Adam", and "Adamw".
- :vartype optimizer: str or ~azure.mgmt.machinelearningservices.models.StochasticOptimizer
- :ivar random_seed: Random seed to be used when using deterministic training.
- :vartype random_seed: int
- :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
- the range [0, 1].
- :vartype step_lr_gamma: float
- :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
- positive integer.
- :vartype step_lr_step_size: int
- :ivar training_batch_size: Training batch size. Must be a positive integer.
- :vartype training_batch_size: int
- :ivar validation_batch_size: Validation batch size. Must be a positive integer.
- :vartype validation_batch_size: int
- :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
- 'warmup_cosine'. Must be a float in the range [0, 1].
- :vartype warmup_cosine_lr_cycles: float
- :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
- 'warmup_cosine'. Must be a positive integer.
- :vartype warmup_cosine_lr_warmup_epochs: int
- :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
- a float in the range[0, 1].
- :vartype weight_decay: float
- :ivar box_detections_per_image: Maximum number of detections per image, for all classes. Must
- be a positive integer.
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype box_detections_per_image: int
- :ivar box_score_threshold: During inference, only return proposals with a classification score
- greater than
- BoxScoreThreshold. Must be a float in the range[0, 1].
- :vartype box_score_threshold: float
- :ivar image_size: Image size for train and validation. Must be a positive integer.
- Note: The training run may get into CUDA OOM if the size is too big.
- Note: This settings is only supported for the 'yolov5' algorithm.
- :vartype image_size: int
- :ivar max_size: Maximum size of the image to be rescaled before feeding it to the backbone.
- Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype max_size: int
- :ivar min_size: Minimum size of the image to be rescaled before feeding it to the backbone.
- Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype min_size: int
- :ivar model_size: Model size. Must be 'small', 'medium', 'large', or 'xlarge'.
- Note: training run may get into CUDA OOM if the model size is too big.
- Note: This settings is only supported for the 'yolov5' algorithm. Known values are: "None",
- "Small", "Medium", "Large", and "ExtraLarge".
- :vartype model_size: str or ~azure.mgmt.machinelearningservices.models.ModelSize
- :ivar multi_scale: Enable multi-scale image by varying image size by +/- 50%.
- Note: training run may get into CUDA OOM if no sufficient GPU memory.
- Note: This settings is only supported for the 'yolov5' algorithm.
- :vartype multi_scale: bool
- :ivar nms_iou_threshold: IOU threshold used during inference in NMS post processing. Must be a
- float in the range [0, 1].
- :vartype nms_iou_threshold: float
- :ivar tile_grid_size: The grid size to use for tiling each image. Note: TileGridSize must not
- be
- None to enable small object detection logic. A string containing two integers in mxn format.
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype tile_grid_size: str
- :ivar tile_overlap_ratio: Overlap ratio between adjacent tiles in each dimension. Must be float
- in the range [0, 1).
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype tile_overlap_ratio: float
- :ivar tile_predictions_nms_threshold: The IOU threshold to use to perform NMS while merging
- predictions from tiles and image.
- Used in validation/ inference. Must be float in the range [0, 1].
- Note: This settings is not supported for the 'yolov5' algorithm.
- :vartype tile_predictions_nms_threshold: float
- :ivar validation_iou_threshold: IOU threshold to use when computing validation metric. Must be
- float in the range [0, 1].
- :vartype validation_iou_threshold: float
- :ivar validation_metric_type: Metric computation method to use for validation metrics. Known
- values are: "None", "Coco", "Voc", and "CocoVoc".
- :vartype validation_metric_type: str or
- ~azure.mgmt.machinelearningservices.models.ValidationMetricType
+ :ivar advanced_settings: Settings for advanced scenarios.
+ :vartype advanced_settings: str
+ :ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
+ :vartype ams_gradient: bool
+ :ivar augmentations: Settings for using Augmentations.
+ :vartype augmentations: str
+ :ivar beta1: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta1: float
+ :ivar beta2: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range
+ [0, 1].
+ :vartype beta2: float
+ :ivar checkpoint_frequency: Frequency to store model checkpoints. Must be a positive integer.
+ :vartype checkpoint_frequency: int
+ :ivar checkpoint_model: The pretrained checkpoint model for incremental training.
+ :vartype checkpoint_model: ~azure.mgmt.machinelearningservices.models.MLFlowModelJobInput
+ :ivar checkpoint_run_id: The id of a previous run that has a pretrained checkpoint for
+ incremental training.
+ :vartype checkpoint_run_id: str
+ :ivar distributed: Whether to use distributed training.
+ :vartype distributed: bool
+ :ivar early_stopping: Enable early stopping logic during training.
+ :vartype early_stopping: bool
+ :ivar early_stopping_delay: Minimum number of epochs or validation evaluations to wait before
+ primary metric improvement
+ is tracked for early stopping. Must be a positive integer.
+ :vartype early_stopping_delay: int
+ :ivar early_stopping_patience: Minimum number of epochs or validation evaluations with no
+ primary metric improvement before
+ the run is stopped. Must be a positive integer.
+ :vartype early_stopping_patience: int
+ :ivar enable_onnx_normalization: Enable normalization when exporting ONNX model.
+ :vartype enable_onnx_normalization: bool
+ :ivar evaluation_frequency: Frequency to evaluate validation dataset to get metric scores. Must
+ be a positive integer.
+ :vartype evaluation_frequency: int
+ :ivar gradient_accumulation_step: Gradient accumulation means running a configured number of
+ "GradAccumulationStep" steps without
+ updating the model weights while accumulating the gradients of those steps, and then using
+ the accumulated gradients to compute the weight updates. Must be a positive integer.
+ :vartype gradient_accumulation_step: int
+ :ivar layers_to_freeze: Number of layers to freeze for the model. Must be a positive integer.
+ For instance, passing 2 as value for 'seresnext' means
+ freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
+ please
+ see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype layers_to_freeze: int
+ :ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
+ :vartype learning_rate: float
+ :ivar learning_rate_scheduler: Type of learning rate scheduler. Must be 'warmup_cosine' or
+ 'step'. Known values are: "None", "WarmupCosine", and "Step".
+ :vartype learning_rate_scheduler: str or
+ ~azure.mgmt.machinelearningservices.models.LearningRateScheduler
+ :ivar model_name: Name of the model to use for training.
+ For more information on the available models please visit the official documentation:
+ https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ :vartype model_name: str
+ :ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
+ :vartype momentum: float
+ :ivar nesterov: Enable nesterov when optimizer is 'sgd'.
+ :vartype nesterov: bool
+ :ivar number_of_epochs: Number of training epochs. Must be a positive integer.
+ :vartype number_of_epochs: int
+ :ivar number_of_workers: Number of data loader workers. Must be a non-negative integer.
+ :vartype number_of_workers: int
+ :ivar optimizer: Type of optimizer. Known values are: "None", "Sgd", "Adam", and "Adamw".
+ :vartype optimizer: str or ~azure.mgmt.machinelearningservices.models.StochasticOptimizer
+ :ivar random_seed: Random seed to be used when using deterministic training.
+ :vartype random_seed: int
+ :ivar step_lr_gamma: Value of gamma when learning rate scheduler is 'step'. Must be a float in
+ the range [0, 1].
+ :vartype step_lr_gamma: float
+ :ivar step_lr_step_size: Value of step size when learning rate scheduler is 'step'. Must be a
+ positive integer.
+ :vartype step_lr_step_size: int
+ :ivar training_batch_size: Training batch size. Must be a positive integer.
+ :vartype training_batch_size: int
+ :ivar validation_batch_size: Validation batch size. Must be a positive integer.
+ :vartype validation_batch_size: int
+ :ivar warmup_cosine_lr_cycles: Value of cosine cycle when learning rate scheduler is
+ 'warmup_cosine'. Must be a float in the range [0, 1].
+ :vartype warmup_cosine_lr_cycles: float
+ :ivar warmup_cosine_lr_warmup_epochs: Value of warmup epochs when learning rate scheduler is
+ 'warmup_cosine'. Must be a positive integer.
+ :vartype warmup_cosine_lr_warmup_epochs: int
+ :ivar weight_decay: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be
+ a float in the range[0, 1].
+ :vartype weight_decay: float
+ :ivar box_detections_per_image: Maximum number of detections per image, for all classes. Must
+ be a positive integer.
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype box_detections_per_image: int
+ :ivar box_score_threshold: During inference, only return proposals with a classification score
+ greater than
+ BoxScoreThreshold. Must be a float in the range[0, 1].
+ :vartype box_score_threshold: float
+ :ivar image_size: Image size for train and validation. Must be a positive integer.
+ Note: The training run may get into CUDA OOM if the size is too big.
+ Note: This settings is only supported for the 'yolov5' algorithm.
+ :vartype image_size: int
+ :ivar max_size: Maximum size of the image to be rescaled before feeding it to the backbone.
+ Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype max_size: int
+ :ivar min_size: Minimum size of the image to be rescaled before feeding it to the backbone.
+ Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype min_size: int
+ :ivar model_size: Model size. Must be 'small', 'medium', 'large', or 'xlarge'.
+ Note: training run may get into CUDA OOM if the model size is too big.
+ Note: This settings is only supported for the 'yolov5' algorithm. Known values are: "None",
+ "Small", "Medium", "Large", and "ExtraLarge".
+ :vartype model_size: str or ~azure.mgmt.machinelearningservices.models.ModelSize
+ :ivar multi_scale: Enable multi-scale image by varying image size by +/- 50%.
+ Note: training run may get into CUDA OOM if no sufficient GPU memory.
+ Note: This settings is only supported for the 'yolov5' algorithm.
+ :vartype multi_scale: bool
+ :ivar nms_iou_threshold: IOU threshold used during inference in NMS post processing. Must be a
+ float in the range [0, 1].
+ :vartype nms_iou_threshold: float
+ :ivar tile_grid_size: The grid size to use for tiling each image. Note: TileGridSize must not
+ be
+ None to enable small object detection logic. A string containing two integers in mxn format.
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype tile_grid_size: str
+ :ivar tile_overlap_ratio: Overlap ratio between adjacent tiles in each dimension. Must be float
+ in the range [0, 1).
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype tile_overlap_ratio: float
+ :ivar tile_predictions_nms_threshold: The IOU threshold to use to perform NMS while merging
+ predictions from tiles and image.
+ Used in validation/ inference. Must be float in the range [0, 1].
+ Note: This settings is not supported for the 'yolov5' algorithm.
+ :vartype tile_predictions_nms_threshold: float
+ :ivar validation_iou_threshold: IOU threshold to use when computing validation metric. Must be
+ float in the range [0, 1].
+ :vartype validation_iou_threshold: float
+ :ivar validation_metric_type: Metric computation method to use for validation metrics. Known
+ values are: "None", "Coco", "Voc", and "CocoVoc".
+ :vartype validation_metric_type: str or
+ ~azure.mgmt.machinelearningservices.models.ValidationMetricType
"""
_attribute_map = {
@@ -12141,8 +12816,8 @@ def __init__( # pylint: disable=too-many-locals
tile_predictions_nms_threshold: Optional[float] = None,
validation_iou_threshold: Optional[float] = None,
validation_metric_type: Optional[Union[str, "_models.ValidationMetricType"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword advanced_settings: Settings for advanced scenarios.
:paramtype advanced_settings: str
@@ -12340,72 +13015,73 @@ def __init__( # pylint: disable=too-many-locals
class ImageObjectDetection(ImageObjectDetectionBase, AutoMLVertical): # pylint: disable=too-many-instance-attributes
- """Image Object Detection. Object detection is used to identify objects in an image and locate each object with a
+ """Image Object Detection. Object detection is used to identify objects in an image and locate
+ each object with a
bounding box e.g. locate all dogs and cats in an image and draw a bounding box around each.
- All required parameters must be populated in order to send to Azure.
-
- :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
- "Warning", "Error", and "Critical".
- :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
- :ivar target_column_name: Target column name: This is prediction values column.
- Also known as label column name in context of classification tasks.
- :vartype target_column_name: str
- :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
- "Classification", "Regression", "Forecasting", "ImageClassification",
- "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
- "TextClassification", "TextClassificationMultilabel", and "TextNER".
- :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
- :ivar training_data: [Required] Training data input. Required.
- :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
- :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
- :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
- validation purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype validation_data_size: float
- :ivar model_settings: Settings used for training the model.
- :vartype model_settings:
- ~azure.mgmt.machinelearningservices.models.ImageModelSettingsObjectDetection
- :ivar search_space: Search space for sampling different combinations of models and their
- hyperparameters.
- :vartype search_space:
- list[~azure.mgmt.machinelearningservices.models.ImageModelDistributionSettingsObjectDetection]
- :ivar primary_metric: Primary metric to optimize for this task. "MeanAveragePrecision"
- :vartype primary_metric: str or
- ~azure.mgmt.machinelearningservices.models.ObjectDetectionPrimaryMetrics
- """
-
- _validation = {
- "task_type": {"required": True},
- "training_data": {"required": True},
- "limit_settings": {"required": True},
- }
-
- _attribute_map = {
- "log_verbosity": {"key": "logVerbosity", "type": "str"},
- "target_column_name": {"key": "targetColumnName", "type": "str"},
- "task_type": {"key": "taskType", "type": "str"},
- "training_data": {"key": "trainingData", "type": "MLTableJobInput"},
- "limit_settings": {"key": "limitSettings", "type": "ImageLimitSettings"},
- "sweep_settings": {"key": "sweepSettings", "type": "ImageSweepSettings"},
- "validation_data": {"key": "validationData", "type": "MLTableJobInput"},
- "validation_data_size": {"key": "validationDataSize", "type": "float"},
- "model_settings": {"key": "modelSettings", "type": "ImageModelSettingsObjectDetection"},
- "search_space": {"key": "searchSpace", "type": "[ImageModelDistributionSettingsObjectDetection]"},
- "primary_metric": {"key": "primaryMetric", "type": "str"},
- }
+ All required parameters must be populated in order to send to Azure.
- def __init__(
- self,
- *,
- training_data: "_models.MLTableJobInput",
- limit_settings: "_models.ImageLimitSettings",
+ :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
+ "Warning", "Error", and "Critical".
+ :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
+ :ivar target_column_name: Target column name: This is prediction values column.
+ Also known as label column name in context of classification tasks.
+ :vartype target_column_name: str
+ :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
+ "Classification", "Regression", "Forecasting", "ImageClassification",
+ "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
+ "TextClassification", "TextClassificationMultilabel", and "TextNER".
+ :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
+ :ivar training_data: [Required] Training data input. Required.
+ :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar limit_settings: [Required] Limit settings for the AutoML job. Required.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.ImageLimitSettings
+ :ivar sweep_settings: Model sweeping and hyperparameter sweeping related settings.
+ :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.ImageSweepSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
+ validation purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype validation_data_size: float
+ :ivar model_settings: Settings used for training the model.
+ :vartype model_settings:
+ ~azure.mgmt.machinelearningservices.models.ImageModelSettingsObjectDetection
+ :ivar search_space: Search space for sampling different combinations of models and their
+ hyperparameters.
+ :vartype search_space:
+ list[~azure.mgmt.machinelearningservices.models.ImageModelDistributionSettingsObjectDetection]
+ :ivar primary_metric: Primary metric to optimize for this task. "MeanAveragePrecision"
+ :vartype primary_metric: str or
+ ~azure.mgmt.machinelearningservices.models.ObjectDetectionPrimaryMetrics
+ """
+
+ _validation = {
+ "task_type": {"required": True},
+ "training_data": {"required": True},
+ "limit_settings": {"required": True},
+ }
+
+ _attribute_map = {
+ "log_verbosity": {"key": "logVerbosity", "type": "str"},
+ "target_column_name": {"key": "targetColumnName", "type": "str"},
+ "task_type": {"key": "taskType", "type": "str"},
+ "training_data": {"key": "trainingData", "type": "MLTableJobInput"},
+ "limit_settings": {"key": "limitSettings", "type": "ImageLimitSettings"},
+ "sweep_settings": {"key": "sweepSettings", "type": "ImageSweepSettings"},
+ "validation_data": {"key": "validationData", "type": "MLTableJobInput"},
+ "validation_data_size": {"key": "validationDataSize", "type": "float"},
+ "model_settings": {"key": "modelSettings", "type": "ImageModelSettingsObjectDetection"},
+ "search_space": {"key": "searchSpace", "type": "[ImageModelDistributionSettingsObjectDetection]"},
+ "primary_metric": {"key": "primaryMetric", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ training_data: "_models.MLTableJobInput",
+ limit_settings: "_models.ImageLimitSettings",
log_verbosity: Optional[Union[str, "_models.LogVerbosity"]] = None,
target_column_name: Optional[str] = None,
sweep_settings: Optional["_models.ImageSweepSettings"] = None,
@@ -12414,8 +13090,8 @@ def __init__(
model_settings: Optional["_models.ImageModelSettingsObjectDetection"] = None,
search_space: Optional[List["_models.ImageModelDistributionSettingsObjectDetection"]] = None,
primary_metric: Optional[Union[str, "_models.ObjectDetectionPrimaryMetrics"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -12499,8 +13175,8 @@ def __init__(
*,
sampling_algorithm: Union[str, "_models.SamplingAlgorithmType"],
early_termination: Optional["_models.EarlyTerminationPolicy"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword early_termination: Type of early termination policy.
:paramtype early_termination: ~azure.mgmt.machinelearningservices.models.EarlyTerminationPolicy
@@ -12538,8 +13214,8 @@ def __init__(
liveness_route: Optional["_models.Route"] = None,
readiness_route: Optional["_models.Route"] = None,
scoring_route: Optional["_models.Route"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword liveness_route: The route to check the liveness of the inference server container.
:paramtype liveness_route: ~azure.mgmt.machinelearningservices.models.Route
@@ -12574,8 +13250,8 @@ def __init__(
*,
node_selector: Optional[Dict[str, str]] = None,
resources: Optional["_models.InstanceTypeSchemaResources"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword node_selector: Node Selector.
:paramtype node_selector: dict[str, str]
@@ -12601,7 +13277,9 @@ class InstanceTypeSchemaResources(_serialization.Model):
"limits": {"key": "limits", "type": "{str}"},
}
- def __init__(self, *, requests: Optional[Dict[str, str]] = None, limits: Optional[Dict[str, str]] = None, **kwargs):
+ def __init__(
+ self, *, requests: Optional[Dict[str, str]] = None, limits: Optional[Dict[str, str]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword requests: Resource requests for this instance type.
:paramtype requests: dict[str, str]
@@ -12651,7 +13329,7 @@ class JobBase(Resource):
"properties": {"key": "properties", "type": "JobBaseProperties"},
}
- def __init__(self, *, properties: "_models.JobBaseProperties", **kwargs):
+ def __init__(self, *, properties: "_models.JobBaseProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.JobBaseProperties
@@ -12675,7 +13353,9 @@ class JobBaseResourceArmPaginatedResult(_serialization.Model):
"value": {"key": "value", "type": "[JobBase]"},
}
- def __init__(self, *, next_link: Optional[str] = None, value: Optional[List["_models.JobBase"]] = None, **kwargs):
+ def __init__(
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.JobBase"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of JobBase objects. If null, there are no
additional pages.
@@ -12727,8 +13407,8 @@ def __init__(
properties: Optional[Dict[str, JSON]] = None,
docker_args: Optional[str] = None,
shm_size: str = "2g",
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword instance_count: Optional number of instances or nodes used by the compute target.
:paramtype instance_count: int
@@ -12772,7 +13452,7 @@ class JobScheduleAction(ScheduleActionBase):
"job_definition": {"key": "jobDefinition", "type": "JobBaseProperties"},
}
- def __init__(self, *, job_definition: "_models.JobBaseProperties", **kwargs):
+ def __init__(self, *, job_definition: "_models.JobBaseProperties", **kwargs: Any) -> None:
"""
:keyword job_definition: [Required] Defines Schedule action definition details. Required.
:paramtype job_definition: ~azure.mgmt.machinelearningservices.models.JobBaseProperties
@@ -12793,6 +13473,9 @@ class JobService(_serialization.Model):
:vartype error_message: str
:ivar job_service_type: Endpoint type.
:vartype job_service_type: str
+ :ivar nodes: Nodes that user would like to start the service on.
+ If Nodes is not set or set to null, the service will only be started on leader node.
+ :vartype nodes: ~azure.mgmt.machinelearningservices.models.Nodes
:ivar port: Port for endpoint.
:vartype port: int
:ivar properties: Additional properties to set on the endpoint.
@@ -12810,6 +13493,7 @@ class JobService(_serialization.Model):
"endpoint": {"key": "endpoint", "type": "str"},
"error_message": {"key": "errorMessage", "type": "str"},
"job_service_type": {"key": "jobServiceType", "type": "str"},
+ "nodes": {"key": "nodes", "type": "Nodes"},
"port": {"key": "port", "type": "int"},
"properties": {"key": "properties", "type": "{str}"},
"status": {"key": "status", "type": "str"},
@@ -12820,15 +13504,19 @@ def __init__(
*,
endpoint: Optional[str] = None,
job_service_type: Optional[str] = None,
+ nodes: Optional["_models.Nodes"] = None,
port: Optional[int] = None,
properties: Optional[Dict[str, str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword endpoint: Url for endpoint.
:paramtype endpoint: str
:keyword job_service_type: Endpoint type.
:paramtype job_service_type: str
+ :keyword nodes: Nodes that user would like to start the service on.
+ If Nodes is not set or set to null, the service will only be started on leader node.
+ :paramtype nodes: ~azure.mgmt.machinelearningservices.models.Nodes
:keyword port: Port for endpoint.
:paramtype port: int
:keyword properties: Additional properties to set on the endpoint.
@@ -12838,6 +13526,7 @@ def __init__(
self.endpoint = endpoint
self.error_message = None
self.job_service_type = job_service_type
+ self.nodes = nodes
self.port = port
self.properties = properties
self.status = None
@@ -12854,7 +13543,7 @@ class KubernetesSchema(_serialization.Model):
"properties": {"key": "properties", "type": "KubernetesProperties"},
}
- def __init__(self, *, properties: Optional["_models.KubernetesProperties"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.KubernetesProperties"] = None, **kwargs: Any) -> None:
"""
:keyword properties: Properties of Kubernetes.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.KubernetesProperties
@@ -12932,8 +13621,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties: Properties of Kubernetes.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.KubernetesProperties
@@ -13069,8 +13758,8 @@ def __init__(
readiness_probe: Optional["_models.ProbeSettings"] = None,
request_settings: Optional["_models.OnlineRequestSettings"] = None,
scale_settings: Optional["_models.OnlineScaleSettings"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword code_configuration: Code configuration for the endpoint deployment.
:paramtype code_configuration: ~azure.mgmt.machinelearningservices.models.CodeConfiguration
@@ -13233,8 +13922,8 @@ def __init__(
request_settings: Optional["_models.OnlineRequestSettings"] = None,
scale_settings: Optional["_models.OnlineScaleSettings"] = None,
container_resource_requirements: Optional["_models.ContainerResourceRequirements"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword code_configuration: Code configuration for the endpoint deployment.
:paramtype code_configuration: ~azure.mgmt.machinelearningservices.models.CodeConfiguration
@@ -13342,8 +14031,8 @@ def __init__(
namespace: str = "default",
default_instance_type: Optional[str] = None,
instance_types: Optional[Dict[str, "_models.InstanceTypeSchema"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword relay_connection_string: Relay connection string.
:paramtype relay_connection_string: str
@@ -13396,7 +14085,7 @@ class ListAmlUserFeatureResult(_serialization.Model):
"next_link": {"key": "nextLink", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.value = None
@@ -13424,7 +14113,7 @@ class ListNotebookKeysResult(_serialization.Model):
"secondary_access_key": {"key": "secondaryAccessKey", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.primary_access_key = None
@@ -13448,7 +14137,7 @@ class ListStorageAccountKeysResult(_serialization.Model):
"user_storage_key": {"key": "userStorageKey", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.user_storage_key = None
@@ -13476,7 +14165,7 @@ class ListUsagesResult(_serialization.Model):
"next_link": {"key": "nextLink", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.value = None
@@ -13521,7 +14210,7 @@ class ListWorkspaceKeysResult(_serialization.Model):
"notebook_access_keys": {"key": "notebookAccessKeys", "type": "ListNotebookKeysResult"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.user_storage_key = None
@@ -13553,7 +14242,7 @@ class ListWorkspaceQuotas(_serialization.Model):
"next_link": {"key": "nextLink", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.value = None
@@ -13577,7 +14266,7 @@ class LiteralJobInput(JobInput):
_validation = {
"job_input_type": {"required": True},
- "value": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "value": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -13586,7 +14275,7 @@ class LiteralJobInput(JobInput):
"value": {"key": "value", "type": "str"},
}
- def __init__(self, *, value: str, description: Optional[str] = None, **kwargs):
+ def __init__(self, *, value: str, description: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword description: Description for the input.
:paramtype description: str
@@ -13635,8 +14324,8 @@ def __init__(
client_id: Optional[str] = None,
object_id: Optional[str] = None,
resource_id: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword client_id: Specifies a user-assigned identity by client ID. For system-assigned, do
not set this field.
@@ -13708,8 +14397,8 @@ def __init__(
target: Optional[str] = None,
value: Optional[str] = None,
value_format: Optional[Union[str, "_models.ValueFormat"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword category: Category of the connection. Known values are: "PythonFeed",
"ContainerRegistry", and "Git".
@@ -13772,8 +14461,8 @@ def __init__(
value: Optional[str] = None,
value_format: Optional[Union[str, "_models.ValueFormat"]] = None,
credentials: Optional["_models.WorkspaceConnectionManagedIdentity"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword category: Category of the connection. Known values are: "PythonFeed",
"ContainerRegistry", and "Git".
@@ -13887,8 +14576,8 @@ def __init__(
readiness_probe: Optional["_models.ProbeSettings"] = None,
request_settings: Optional["_models.OnlineRequestSettings"] = None,
scale_settings: Optional["_models.OnlineScaleSettings"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword code_configuration: Code configuration for the endpoint deployment.
:paramtype code_configuration: ~azure.mgmt.machinelearningservices.models.CodeConfiguration
@@ -13990,8 +14679,8 @@ def __init__(
*,
type: Union[str, "_models.ManagedServiceIdentityType"],
user_assigned_identities: Optional[Dict[str, "_models.UserAssignedIdentity"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword type: Type of managed service identity (where both SystemAssigned and UserAssigned
types are allowed). Required. Known values are: "None", "SystemAssigned", "UserAssigned", and
@@ -14012,7 +14701,8 @@ def __init__(
class MedianStoppingPolicy(EarlyTerminationPolicy):
- """Defines an early termination policy based on running averages of the primary metric of all runs.
+ """Defines an early termination policy based on running averages of the primary metric of all
+ runs.
All required parameters must be populated in order to send to Azure.
@@ -14036,7 +14726,7 @@ class MedianStoppingPolicy(EarlyTerminationPolicy):
"policy_type": {"key": "policyType", "type": "str"},
}
- def __init__(self, *, delay_evaluation: int = 0, evaluation_interval: int = 0, **kwargs):
+ def __init__(self, *, delay_evaluation: int = 0, evaluation_interval: int = 0, **kwargs: Any) -> None:
"""
:keyword delay_evaluation: Number of intervals by which to delay the first evaluation.
:paramtype delay_evaluation: int
@@ -14067,7 +14757,7 @@ class MLFlowModelJobInput(AssetJobInput, JobInput):
_validation = {
"job_input_type": {"required": True},
- "uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -14083,8 +14773,8 @@ def __init__(
uri: str,
description: Optional[str] = None,
mode: Optional[Union[str, "_models.InputDeliveryMode"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the input.
:paramtype description: str
@@ -14134,8 +14824,8 @@ def __init__(
description: Optional[str] = None,
mode: Optional[Union[str, "_models.OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the output.
:paramtype description: str
@@ -14169,9 +14859,8 @@ class MLTableData(DataVersionBaseProperties):
:ivar data_type: [Required] Specifies the type of data. Required. Known values are: "uri_file",
"uri_folder", and "mltable".
:vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
- :ivar data_uri: [Required] Uri of the data. Usage/meaning depends on
- Microsoft.MachineLearning.ManagementFrontEnd.Contracts.V20221001.Assets.DataVersionBase.DataType.
- Required.
+ :ivar data_uri: [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330. Required.
:vartype data_uri: str
:ivar referenced_uris: Uris referenced in the MLTable definition (required for lineage).
:vartype referenced_uris: list[str]
@@ -14179,7 +14868,7 @@ class MLTableData(DataVersionBaseProperties):
_validation = {
"data_type": {"required": True},
- "data_uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "data_uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -14203,8 +14892,8 @@ def __init__(
is_anonymous: bool = False,
is_archived: bool = False,
referenced_uris: Optional[List[str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -14216,9 +14905,8 @@ def __init__(
:paramtype is_anonymous: bool
:keyword is_archived: Is the asset archived?.
:paramtype is_archived: bool
- :keyword data_uri: [Required] Uri of the data. Usage/meaning depends on
- Microsoft.MachineLearning.ManagementFrontEnd.Contracts.V20221001.Assets.DataVersionBase.DataType.
- Required.
+ :keyword data_uri: [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330. Required.
:paramtype data_uri: str
:keyword referenced_uris: Uris referenced in the MLTable definition (required for lineage).
:paramtype referenced_uris: list[str]
@@ -14256,7 +14944,7 @@ class MLTableJobInput(AssetJobInput, JobInput):
_validation = {
"job_input_type": {"required": True},
- "uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -14272,8 +14960,8 @@ def __init__(
uri: str,
description: Optional[str] = None,
mode: Optional[Union[str, "_models.InputDeliveryMode"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the input.
:paramtype description: str
@@ -14323,8 +15011,8 @@ def __init__(
description: Optional[str] = None,
mode: Optional[Union[str, "_models.OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the output.
:paramtype description: str
@@ -14378,7 +15066,7 @@ class ModelContainer(Resource):
"properties": {"key": "properties", "type": "ModelContainerProperties"},
}
- def __init__(self, *, properties: "_models.ModelContainerProperties", **kwargs):
+ def __init__(self, *, properties: "_models.ModelContainerProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.ModelContainerProperties
@@ -14404,11 +15092,16 @@ class ModelContainerProperties(AssetContainer):
:vartype latest_version: str
:ivar next_version: The next auto incremental version.
:vartype next_version: str
+ :ivar provisioning_state: Provisioning state for the model container. Known values are:
+ "Succeeded", "Failed", "Canceled", "Creating", "Updating", and "Deleting".
+ :vartype provisioning_state: str or
+ ~azure.mgmt.machinelearningservices.models.AssetProvisioningState
"""
_validation = {
"latest_version": {"readonly": True},
"next_version": {"readonly": True},
+ "provisioning_state": {"readonly": True},
}
_attribute_map = {
@@ -14418,6 +15111,7 @@ class ModelContainerProperties(AssetContainer):
"is_archived": {"key": "isArchived", "type": "bool"},
"latest_version": {"key": "latestVersion", "type": "str"},
"next_version": {"key": "nextVersion", "type": "str"},
+ "provisioning_state": {"key": "provisioningState", "type": "str"},
}
def __init__(
@@ -14427,8 +15121,8 @@ def __init__(
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -14440,6 +15134,7 @@ def __init__(
:paramtype is_archived: bool
"""
super().__init__(description=description, properties=properties, tags=tags, is_archived=is_archived, **kwargs)
+ self.provisioning_state = None
class ModelContainerResourceArmPaginatedResult(_serialization.Model):
@@ -14458,8 +15153,8 @@ class ModelContainerResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.ModelContainer"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.ModelContainer"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of ModelContainer objects. If null, there are no
additional pages.
@@ -14510,7 +15205,7 @@ class ModelVersion(Resource):
"properties": {"key": "properties", "type": "ModelVersionProperties"},
}
- def __init__(self, *, properties: "_models.ModelVersionProperties", **kwargs):
+ def __init__(self, *, properties: "_models.ModelVersionProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.ModelVersionProperties
@@ -14519,9 +15214,11 @@ def __init__(self, *, properties: "_models.ModelVersionProperties", **kwargs):
self.properties = properties
-class ModelVersionProperties(AssetBase):
+class ModelVersionProperties(AssetBase): # pylint: disable=too-many-instance-attributes
"""Model asset version details.
+ Variables are only populated by the server, and will be ignored when sending a request.
+
:ivar description: The asset description text.
:vartype description: str
:ivar properties: The asset property dictionary.
@@ -14540,8 +15237,18 @@ class ModelVersionProperties(AssetBase):
:vartype model_type: str
:ivar model_uri: The URI path to the model contents.
:vartype model_uri: str
+ :ivar provisioning_state: Provisioning state for the model version. Known values are:
+ "Succeeded", "Failed", "Canceled", "Creating", "Updating", and "Deleting".
+ :vartype provisioning_state: str or
+ ~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Stage in the model lifecycle assigned to this model.
+ :vartype stage: str
"""
+ _validation = {
+ "provisioning_state": {"readonly": True},
+ }
+
_attribute_map = {
"description": {"key": "description", "type": "str"},
"properties": {"key": "properties", "type": "{str}"},
@@ -14552,6 +15259,8 @@ class ModelVersionProperties(AssetBase):
"job_name": {"key": "jobName", "type": "str"},
"model_type": {"key": "modelType", "type": "str"},
"model_uri": {"key": "modelUri", "type": "str"},
+ "provisioning_state": {"key": "provisioningState", "type": "str"},
+ "stage": {"key": "stage", "type": "str"},
}
def __init__(
@@ -14566,8 +15275,9 @@ def __init__(
job_name: Optional[str] = None,
model_type: Optional[str] = None,
model_uri: Optional[str] = None,
- **kwargs
- ):
+ stage: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -14587,6 +15297,8 @@ def __init__(
:paramtype model_type: str
:keyword model_uri: The URI path to the model contents.
:paramtype model_uri: str
+ :keyword stage: Stage in the model lifecycle assigned to this model.
+ :paramtype stage: str
"""
super().__init__(
description=description,
@@ -14600,6 +15312,8 @@ def __init__(
self.job_name = job_name
self.model_type = model_type
self.model_uri = model_uri
+ self.provisioning_state = None
+ self.stage = stage
class ModelVersionResourceArmPaginatedResult(_serialization.Model):
@@ -14618,8 +15332,8 @@ class ModelVersionResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.ModelVersion"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.ModelVersion"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of ModelVersion objects. If null, there are no
additional pages.
@@ -14653,7 +15367,7 @@ class Mpi(DistributionConfiguration):
"process_count_per_instance": {"key": "processCountPerInstance", "type": "int"},
}
- def __init__(self, *, process_count_per_instance: Optional[int] = None, **kwargs):
+ def __init__(self, *, process_count_per_instance: Optional[int] = None, **kwargs: Any) -> None:
"""
:keyword process_count_per_instance: Number of processes per MPI node.
:paramtype process_count_per_instance: int
@@ -14667,13 +15381,13 @@ class NlpVertical(_serialization.Model):
"""Abstract class for NLP related AutoML tasks.
NLP - Natural Language Processing.
- :ivar featurization_settings: Featurization inputs needed for AutoML job.
- :vartype featurization_settings:
- ~azure.mgmt.machinelearningservices.models.NlpVerticalFeaturizationSettings
- :ivar limit_settings: Execution constraints for AutoMLJob.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.NlpVerticalLimitSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar featurization_settings: Featurization inputs needed for AutoML job.
+ :vartype featurization_settings:
+ ~azure.mgmt.machinelearningservices.models.NlpVerticalFeaturizationSettings
+ :ivar limit_settings: Execution constraints for AutoMLJob.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.NlpVerticalLimitSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
"""
_attribute_map = {
@@ -14688,8 +15402,8 @@ def __init__(
featurization_settings: Optional["_models.NlpVerticalFeaturizationSettings"] = None,
limit_settings: Optional["_models.NlpVerticalLimitSettings"] = None,
validation_data: Optional["_models.MLTableJobInput"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword featurization_settings: Featurization inputs needed for AutoML job.
:paramtype featurization_settings:
@@ -14716,7 +15430,7 @@ class NlpVerticalFeaturizationSettings(FeaturizationSettings):
"dataset_language": {"key": "datasetLanguage", "type": "str"},
}
- def __init__(self, *, dataset_language: Optional[str] = None, **kwargs):
+ def __init__(self, *, dataset_language: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword dataset_language: Dataset language, useful for the text data.
:paramtype dataset_language: str
@@ -14742,13 +15456,8 @@ class NlpVerticalLimitSettings(_serialization.Model):
}
def __init__(
- self,
- *,
- max_concurrent_trials: int = 1,
- max_trials: int = 1,
- timeout: Optional[datetime.timedelta] = None,
- **kwargs
- ):
+ self, *, max_concurrent_trials: int = 1, max_trials: int = 1, timeout: datetime.timedelta = "P7D", **kwargs: Any
+ ) -> None:
"""
:keyword max_concurrent_trials: Maximum Concurrent AutoML iterations.
:paramtype max_concurrent_trials: int
@@ -14800,7 +15509,7 @@ class NodeStateCounts(_serialization.Model):
"preempted_node_count": {"key": "preemptedNodeCount", "type": "int"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.idle_node_count = None
@@ -14849,8 +15558,8 @@ def __init__(
target: Optional[str] = None,
value: Optional[str] = None,
value_format: Optional[Union[str, "_models.ValueFormat"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword category: Category of the connection. Known values are: "PythonFeed",
"ContainerRegistry", and "Git".
@@ -14884,7 +15593,7 @@ class NoneDatastoreCredentials(DatastoreCredentials):
"credentials_type": {"key": "credentialsType", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.credentials_type: str = "None"
@@ -14935,7 +15644,7 @@ class NotebookAccessTokenResult(_serialization.Model):
"scope": {"key": "scope", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.notebook_resource_id = None
@@ -14962,7 +15671,9 @@ class NotebookPreparationError(_serialization.Model):
"status_code": {"key": "statusCode", "type": "int"},
}
- def __init__(self, *, error_message: Optional[str] = None, status_code: Optional[int] = None, **kwargs):
+ def __init__(
+ self, *, error_message: Optional[str] = None, status_code: Optional[int] = None, **kwargs: Any
+ ) -> None:
"""
:keyword error_message:
:paramtype error_message: str
@@ -14998,8 +15709,8 @@ def __init__(
fqdn: Optional[str] = None,
resource_id: Optional[str] = None,
notebook_preparation_error: Optional["_models.NotebookPreparationError"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword fqdn:
:paramtype fqdn: str
@@ -15029,7 +15740,7 @@ class Objective(_serialization.Model):
_validation = {
"goal": {"required": True},
- "primary_metric": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "primary_metric": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -15037,7 +15748,7 @@ class Objective(_serialization.Model):
"primary_metric": {"key": "primaryMetric", "type": "str"},
}
- def __init__(self, *, goal: Union[str, "_models.Goal"], primary_metric: str, **kwargs):
+ def __init__(self, *, goal: Union[str, "_models.Goal"], primary_metric: str, **kwargs: Any) -> None:
"""
:keyword goal: [Required] Defines supported metric goals for hyperparameter tuning. Required.
Known values are: "Minimize" and "Maximize".
@@ -15114,8 +15825,8 @@ def __init__(
identity: Optional["_models.ManagedServiceIdentity"] = None,
kind: Optional[str] = None,
sku: Optional["_models.Sku"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword tags: Resource tags.
:paramtype tags: dict[str, str]
@@ -15154,8 +15865,12 @@ class OnlineDeploymentTrackedResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.OnlineDeployment"]] = None, **kwargs
- ):
+ self,
+ *,
+ next_link: Optional[str] = None,
+ value: Optional[List["_models.OnlineDeployment"]] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of OnlineDeployment objects. If null, there are
no additional pages.
@@ -15232,8 +15947,8 @@ def __init__(
identity: Optional["_models.ManagedServiceIdentity"] = None,
kind: Optional[str] = None,
sku: Optional["_models.Sku"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword tags: Resource tags.
:paramtype tags: dict[str, str]
@@ -15256,7 +15971,7 @@ def __init__(
self.sku = sku
-class OnlineEndpointProperties(EndpointPropertiesBase):
+class OnlineEndpointProperties(EndpointPropertiesBase): # pylint: disable=too-many-instance-attributes
"""Online endpoint configuration.
Variables are only populated by the server, and will be ignored when sending a request.
@@ -15282,6 +15997,9 @@ class OnlineEndpointProperties(EndpointPropertiesBase):
:ivar compute: ARM resource ID of the compute if it exists.
optional.
:vartype compute: str
+ :ivar mirror_traffic: Percentage of traffic to be mirrored to each deployment without using
+ returned scoring. Traffic values need to sum to utmost 50.
+ :vartype mirror_traffic: dict[str, int]
:ivar provisioning_state: Provisioning state for the endpoint. Known values are: "Creating",
"Deleting", "Succeeded", "Failed", "Updating", and "Canceled".
:vartype provisioning_state: str or
@@ -15310,6 +16028,7 @@ class OnlineEndpointProperties(EndpointPropertiesBase):
"scoring_uri": {"key": "scoringUri", "type": "str"},
"swagger_uri": {"key": "swaggerUri", "type": "str"},
"compute": {"key": "compute", "type": "str"},
+ "mirror_traffic": {"key": "mirrorTraffic", "type": "{int}"},
"provisioning_state": {"key": "provisioningState", "type": "str"},
"public_network_access": {"key": "publicNetworkAccess", "type": "str"},
"traffic": {"key": "traffic", "type": "{int}"},
@@ -15323,10 +16042,11 @@ def __init__(
keys: Optional["_models.EndpointAuthKeys"] = None,
properties: Optional[Dict[str, str]] = None,
compute: Optional[str] = None,
+ mirror_traffic: Optional[Dict[str, int]] = None,
public_network_access: Optional[Union[str, "_models.PublicNetworkAccessType"]] = None,
traffic: Optional[Dict[str, int]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword auth_mode: [Required] Use 'Key' for key based authentication and 'AMLToken' for Azure
Machine Learning token-based authentication. 'Key' doesn't expire but 'AMLToken' does.
@@ -15343,6 +16063,9 @@ def __init__(
:keyword compute: ARM resource ID of the compute if it exists.
optional.
:paramtype compute: str
+ :keyword mirror_traffic: Percentage of traffic to be mirrored to each deployment without using
+ returned scoring. Traffic values need to sum to utmost 50.
+ :paramtype mirror_traffic: dict[str, int]
:keyword public_network_access: Set to "Enabled" for endpoints that should allow public access
when Private Link is enabled. Known values are: "Enabled" and "Disabled".
:paramtype public_network_access: str or
@@ -15353,6 +16076,7 @@ def __init__(
"""
super().__init__(auth_mode=auth_mode, description=description, keys=keys, properties=properties, **kwargs)
self.compute = compute
+ self.mirror_traffic = mirror_traffic
self.provisioning_state = None
self.public_network_access = public_network_access
self.traffic = traffic
@@ -15374,8 +16098,8 @@ class OnlineEndpointTrackedResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.OnlineEndpoint"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.OnlineEndpoint"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of OnlineEndpoint objects. If null, there are no
additional pages.
@@ -15415,8 +16139,8 @@ def __init__(
max_concurrent_requests_per_instance: int = 1,
max_queue_wait: datetime.timedelta = "PT0.5S",
request_timeout: datetime.timedelta = "PT5S",
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword max_concurrent_requests_per_instance: The number of maximum concurrent requests per
node allowed per deployment. Defaults to 1.
@@ -15459,7 +16183,7 @@ class OutputPathAssetReference(AssetReferenceBase):
"path": {"key": "path", "type": "str"},
}
- def __init__(self, *, job_id: Optional[str] = None, path: Optional[str] = None, **kwargs):
+ def __init__(self, *, job_id: Optional[str] = None, path: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword job_id: ARM resource ID of the job.
:paramtype job_id: str
@@ -15487,8 +16211,8 @@ class PaginatedComputeResourcesList(_serialization.Model):
}
def __init__(
- self, *, value: Optional[List["_models.ComputeResource"]] = None, next_link: Optional[str] = None, **kwargs
- ):
+ self, *, value: Optional[List["_models.ComputeResource"]] = None, next_link: Optional[str] = None, **kwargs: Any
+ ) -> None:
"""
:keyword value: An array of Machine Learning compute objects wrapped in ARM resource envelope.
:paramtype value: list[~azure.mgmt.machinelearningservices.models.ComputeResource]
@@ -15511,7 +16235,7 @@ class PartialBatchDeployment(_serialization.Model):
"description": {"key": "description", "type": "str"},
}
- def __init__(self, *, description: Optional[str] = None, **kwargs):
+ def __init__(self, *, description: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword description: Description of the endpoint deployment.
:paramtype description: str
@@ -15539,8 +16263,8 @@ def __init__(
*,
properties: Optional["_models.PartialBatchDeployment"] = None,
tags: Optional[Dict[str, str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties: Additional attributes of the entity.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.PartialBatchDeployment
@@ -15575,8 +16299,8 @@ def __init__(
*,
type: Optional[Union[str, "_models.ManagedServiceIdentityType"]] = None,
user_assigned_identities: Optional[Dict[str, JSON]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword type: Managed service identity (system assigned and/or user assigned identities).
Known values are: "None", "SystemAssigned", "UserAssigned", and "SystemAssigned,UserAssigned".
@@ -15603,7 +16327,7 @@ class PartialMinimalTrackedResource(_serialization.Model):
"tags": {"key": "tags", "type": "{str}"},
}
- def __init__(self, *, tags: Optional[Dict[str, str]] = None, **kwargs):
+ def __init__(self, *, tags: Optional[Dict[str, str]] = None, **kwargs: Any) -> None:
"""
:keyword tags: Resource tags.
:paramtype tags: dict[str, str]
@@ -15631,8 +16355,8 @@ def __init__(
*,
tags: Optional[Dict[str, str]] = None,
identity: Optional["_models.PartialManagedServiceIdentity"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword tags: Resource tags.
:paramtype tags: dict[str, str]
@@ -15657,7 +16381,9 @@ class PartialMinimalTrackedResourceWithSku(PartialMinimalTrackedResource):
"sku": {"key": "sku", "type": "PartialSku"},
}
- def __init__(self, *, tags: Optional[Dict[str, str]] = None, sku: Optional["_models.PartialSku"] = None, **kwargs):
+ def __init__(
+ self, *, tags: Optional[Dict[str, str]] = None, sku: Optional["_models.PartialSku"] = None, **kwargs: Any
+ ) -> None:
"""
:keyword tags: Resource tags.
:paramtype tags: dict[str, str]
@@ -15668,6 +16394,47 @@ def __init__(self, *, tags: Optional[Dict[str, str]] = None, sku: Optional["_mod
self.sku = sku
+class PartialRegistryPartialTrackedResource(_serialization.Model):
+ """Strictly used in update requests.
+
+ :ivar identity: Managed service identity (system assigned and/or user assigned identities).
+ :vartype identity:
+ ~azure.mgmt.machinelearningservices.models.RegistryPartialManagedServiceIdentity
+ :ivar sku: Sku details required for ARM contract for Autoscaling.
+ :vartype sku: ~azure.mgmt.machinelearningservices.models.PartialSku
+ :ivar tags: Resource tags.
+ :vartype tags: dict[str, str]
+ """
+
+ _attribute_map = {
+ "identity": {"key": "identity", "type": "RegistryPartialManagedServiceIdentity"},
+ "sku": {"key": "sku", "type": "PartialSku"},
+ "tags": {"key": "tags", "type": "{str}"},
+ }
+
+ def __init__(
+ self,
+ *,
+ identity: Optional["_models.RegistryPartialManagedServiceIdentity"] = None,
+ sku: Optional["_models.PartialSku"] = None,
+ tags: Optional[Dict[str, str]] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword identity: Managed service identity (system assigned and/or user assigned identities).
+ :paramtype identity:
+ ~azure.mgmt.machinelearningservices.models.RegistryPartialManagedServiceIdentity
+ :keyword sku: Sku details required for ARM contract for Autoscaling.
+ :paramtype sku: ~azure.mgmt.machinelearningservices.models.PartialSku
+ :keyword tags: Resource tags.
+ :paramtype tags: dict[str, str]
+ """
+ super().__init__(**kwargs)
+ self.identity = identity
+ self.sku = sku
+ self.tags = tags
+
+
class PartialSku(_serialization.Model):
"""Common SKU definition.
@@ -15704,8 +16471,8 @@ def __init__(
name: Optional[str] = None,
size: Optional[str] = None,
tier: Optional[Union[str, "_models.SkuTier"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword capacity: If the SKU supports scale out/in then the capacity integer should be
included. If scale out/in is not possible for the resource this may be omitted.
@@ -15752,7 +16519,7 @@ class Password(_serialization.Model):
"value": {"key": "value", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.name = None
@@ -15802,8 +16569,8 @@ def __init__(
value: Optional[str] = None,
value_format: Optional[Union[str, "_models.ValueFormat"]] = None,
credentials: Optional["_models.WorkspaceConnectionPersonalAccessToken"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword category: Category of the connection. Known values are: "PythonFeed",
"ContainerRegistry", and "Git".
@@ -15823,6 +16590,120 @@ def __init__(
self.credentials = credentials
+class PendingUploadCredentialDto(_serialization.Model):
+ """PendingUploadCredentialDto.
+
+ You probably want to use the sub-classes and not this class directly. Known sub-classes are:
+ SASCredentialDto
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar credential_type: [Required] Credential type used to authentication with storage.
+ Required. "SAS"
+ :vartype credential_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialType
+ """
+
+ _validation = {
+ "credential_type": {"required": True},
+ }
+
+ _attribute_map = {
+ "credential_type": {"key": "credentialType", "type": "str"},
+ }
+
+ _subtype_map = {"credential_type": {"SAS": "SASCredentialDto"}}
+
+ def __init__(self, **kwargs: Any) -> None:
+ """ """
+ super().__init__(**kwargs)
+ self.credential_type: Optional[str] = None
+
+
+class PendingUploadRequestDto(_serialization.Model):
+ """PendingUploadRequestDto.
+
+ :ivar pending_upload_id: If PendingUploadId = null then random guid will be used.
+ :vartype pending_upload_id: str
+ :ivar pending_upload_type: TemporaryBlobReference is the only supported type. Known values are:
+ "None" and "TemporaryBlobReference".
+ :vartype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+
+ _attribute_map = {
+ "pending_upload_id": {"key": "pendingUploadId", "type": "str"},
+ "pending_upload_type": {"key": "pendingUploadType", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ pending_upload_id: Optional[str] = None,
+ pending_upload_type: Optional[Union[str, "_models.PendingUploadType"]] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword pending_upload_id: If PendingUploadId = null then random guid will be used.
+ :paramtype pending_upload_id: str
+ :keyword pending_upload_type: TemporaryBlobReference is the only supported type. Known values
+ are: "None" and "TemporaryBlobReference".
+ :paramtype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+ super().__init__(**kwargs)
+ self.pending_upload_id = pending_upload_id
+ self.pending_upload_type = pending_upload_type
+
+
+class PendingUploadResponseDto(_serialization.Model):
+ """PendingUploadResponseDto.
+
+ :ivar blob_reference_for_consumption: Container level read, write, list SAS.
+ :vartype blob_reference_for_consumption:
+ ~azure.mgmt.machinelearningservices.models.BlobReferenceForConsumptionDto
+ :ivar pending_upload_id: ID for this upload request.
+ :vartype pending_upload_id: str
+ :ivar pending_upload_type: TemporaryBlobReference is the only supported type. Known values are:
+ "None" and "TemporaryBlobReference".
+ :vartype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+
+ _attribute_map = {
+ "blob_reference_for_consumption": {
+ "key": "blobReferenceForConsumption",
+ "type": "BlobReferenceForConsumptionDto",
+ },
+ "pending_upload_id": {"key": "pendingUploadId", "type": "str"},
+ "pending_upload_type": {"key": "pendingUploadType", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ blob_reference_for_consumption: Optional["_models.BlobReferenceForConsumptionDto"] = None,
+ pending_upload_id: Optional[str] = None,
+ pending_upload_type: Optional[Union[str, "_models.PendingUploadType"]] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword blob_reference_for_consumption: Container level read, write, list SAS.
+ :paramtype blob_reference_for_consumption:
+ ~azure.mgmt.machinelearningservices.models.BlobReferenceForConsumptionDto
+ :keyword pending_upload_id: ID for this upload request.
+ :paramtype pending_upload_id: str
+ :keyword pending_upload_type: TemporaryBlobReference is the only supported type. Known values
+ are: "None" and "TemporaryBlobReference".
+ :paramtype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+ super().__init__(**kwargs)
+ self.blob_reference_for_consumption = blob_reference_for_consumption
+ self.pending_upload_id = pending_upload_id
+ self.pending_upload_type = pending_upload_type
+
+
class PersonalComputeInstanceSettings(_serialization.Model):
"""Settings for a personal compute instance.
@@ -15834,7 +16715,7 @@ class PersonalComputeInstanceSettings(_serialization.Model):
"assigned_user": {"key": "assignedUser", "type": "AssignedUser"},
}
- def __init__(self, *, assigned_user: Optional["_models.AssignedUser"] = None, **kwargs):
+ def __init__(self, *, assigned_user: Optional["_models.AssignedUser"] = None, **kwargs: Any) -> None:
"""
:keyword assigned_user: A user explicitly assigned to a personal compute instance.
:paramtype assigned_user: ~azure.mgmt.machinelearningservices.models.AssignedUser
@@ -15936,8 +16817,8 @@ def __init__(
outputs: Optional[Dict[str, "_models.JobOutput"]] = None,
settings: Optional[JSON] = None,
source_job_id: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -16002,25 +16883,20 @@ class PrivateEndpoint(_serialization.Model):
:ivar id: The ARM identifier for Private Endpoint.
:vartype id: str
- :ivar subnet_arm_id: The ARM identifier for Subnet resource that private endpoint links to.
- :vartype subnet_arm_id: str
"""
_validation = {
"id": {"readonly": True},
- "subnet_arm_id": {"readonly": True},
}
_attribute_map = {
"id": {"key": "id", "type": "str"},
- "subnet_arm_id": {"key": "subnetArmId", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.id = None
- self.subnet_arm_id = None
class PrivateEndpointConnection(Resource): # pylint: disable=too-many-instance-attributes
@@ -16093,8 +16969,8 @@ def __init__(
sku: Optional["_models.Sku"] = None,
private_endpoint: Optional["_models.PrivateEndpoint"] = None,
private_link_service_connection_state: Optional["_models.PrivateLinkServiceConnectionState"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword identity: The identity of the resource.
:paramtype identity: ~azure.mgmt.machinelearningservices.models.ManagedServiceIdentity
@@ -16132,7 +17008,7 @@ class PrivateEndpointConnectionListResult(_serialization.Model):
"value": {"key": "value", "type": "[PrivateEndpointConnection]"},
}
- def __init__(self, *, value: Optional[List["_models.PrivateEndpointConnection"]] = None, **kwargs):
+ def __init__(self, *, value: Optional[List["_models.PrivateEndpointConnection"]] = None, **kwargs: Any) -> None:
"""
:keyword value: Array of private endpoint connections.
:paramtype value: list[~azure.mgmt.machinelearningservices.models.PrivateEndpointConnection]
@@ -16141,6 +17017,35 @@ def __init__(self, *, value: Optional[List["_models.PrivateEndpointConnection"]]
self.value = value
+class PrivateEndpointResource(PrivateEndpoint):
+ """The PE network resource that is linked to this PE connection.
+
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ :ivar id: The ARM identifier for Private Endpoint.
+ :vartype id: str
+ :ivar subnet_arm_id: The subnetId that the private endpoint is connected to.
+ :vartype subnet_arm_id: str
+ """
+
+ _validation = {
+ "id": {"readonly": True},
+ }
+
+ _attribute_map = {
+ "id": {"key": "id", "type": "str"},
+ "subnet_arm_id": {"key": "subnetArmId", "type": "str"},
+ }
+
+ def __init__(self, *, subnet_arm_id: Optional[str] = None, **kwargs: Any) -> None:
+ """
+ :keyword subnet_arm_id: The subnetId that the private endpoint is connected to.
+ :paramtype subnet_arm_id: str
+ """
+ super().__init__(**kwargs)
+ self.subnet_arm_id = subnet_arm_id
+
+
class PrivateLinkResource(Resource): # pylint: disable=too-many-instance-attributes
"""A private link resource.
@@ -16204,8 +17109,8 @@ def __init__(
tags: Optional[Dict[str, str]] = None,
sku: Optional["_models.Sku"] = None,
required_zone_names: Optional[List[str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword identity: The identity of the resource.
:paramtype identity: ~azure.mgmt.machinelearningservices.models.ManagedServiceIdentity
@@ -16239,7 +17144,7 @@ class PrivateLinkResourceListResult(_serialization.Model):
"value": {"key": "value", "type": "[PrivateLinkResource]"},
}
- def __init__(self, *, value: Optional[List["_models.PrivateLinkResource"]] = None, **kwargs):
+ def __init__(self, *, value: Optional[List["_models.PrivateLinkResource"]] = None, **kwargs: Any) -> None:
"""
:keyword value: Array of private link resources.
:paramtype value: list[~azure.mgmt.machinelearningservices.models.PrivateLinkResource]
@@ -16249,7 +17154,8 @@ def __init__(self, *, value: Optional[List["_models.PrivateLinkResource"]] = Non
class PrivateLinkServiceConnectionState(_serialization.Model):
- """A collection of information about the state of the connection between service consumer and provider.
+ """A collection of information about the state of the connection between service consumer and
+ provider.
:ivar status: Indicates whether the connection has been Approved/Rejected/Removed by the owner
of the service. Known values are: "Pending", "Approved", "Rejected", "Disconnected", and
@@ -16275,8 +17181,8 @@ def __init__(
status: Optional[Union[str, "_models.PrivateEndpointServiceConnectionStatus"]] = None,
description: Optional[str] = None,
actions_required: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword status: Indicates whether the connection has been Approved/Rejected/Removed by the
owner of the service. Known values are: "Pending", "Approved", "Rejected", "Disconnected", and
@@ -16326,8 +17232,8 @@ def __init__(
period: datetime.timedelta = "PT10S",
success_threshold: int = 1,
timeout: datetime.timedelta = "PT2S",
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword failure_threshold: The number of failures to allow before returning an unhealthy
status.
@@ -16370,7 +17276,7 @@ class PyTorch(DistributionConfiguration):
"process_count_per_instance": {"key": "processCountPerInstance", "type": "int"},
}
- def __init__(self, *, process_count_per_instance: Optional[int] = None, **kwargs):
+ def __init__(self, *, process_count_per_instance: Optional[int] = None, **kwargs: Any) -> None:
"""
:keyword process_count_per_instance: Number of processes per node.
:paramtype process_count_per_instance: int
@@ -16407,8 +17313,8 @@ def __init__(
type: Optional[str] = None,
limit: Optional[int] = None,
unit: Optional[Union[str, "_models.QuotaUnit"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword id: Specifies the resource ID.
:paramtype id: str
@@ -16441,8 +17347,12 @@ class QuotaUpdateParameters(_serialization.Model):
}
def __init__(
- self, *, value: Optional[List["_models.QuotaBaseProperties"]] = None, location: Optional[str] = None, **kwargs
- ):
+ self,
+ *,
+ value: Optional[List["_models.QuotaBaseProperties"]] = None,
+ location: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword value: The list for update quota.
:paramtype value: list[~azure.mgmt.machinelearningservices.models.QuotaBaseProperties]
@@ -16485,8 +17395,8 @@ def __init__(
*,
rule: Optional[Union[str, "_models.RandomSamplingAlgorithmRule"]] = None,
seed: Optional[int] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword rule: The specific type of random algorithm. Known values are: "Random" and "Sobol".
:paramtype rule: str or ~azure.mgmt.machinelearningservices.models.RandomSamplingAlgorithmRule
@@ -16499,6 +17409,65 @@ def __init__(
self.seed = seed
+class Recurrence(_serialization.Model):
+ """The workflow trigger recurrence for ComputeStartStop schedule type.
+
+ :ivar frequency: [Required] The frequency to trigger schedule. Known values are: "Minute",
+ "Hour", "Day", "Week", and "Month".
+ :vartype frequency: str or ~azure.mgmt.machinelearningservices.models.RecurrenceFrequency
+ :ivar interval: [Required] Specifies schedule interval in conjunction with frequency.
+ :vartype interval: int
+ :ivar start_time: The start time in yyyy-MM-ddTHH:mm:ss format.
+ :vartype start_time: str
+ :ivar time_zone: Specifies time zone in which the schedule runs.
+ TimeZone should follow Windows time zone format. Refer:
+ https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ :vartype time_zone: str
+ :ivar schedule: [Required] The recurrence schedule.
+ :vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
+ """
+
+ _attribute_map = {
+ "frequency": {"key": "frequency", "type": "str"},
+ "interval": {"key": "interval", "type": "int"},
+ "start_time": {"key": "startTime", "type": "str"},
+ "time_zone": {"key": "timeZone", "type": "str"},
+ "schedule": {"key": "schedule", "type": "RecurrenceSchedule"},
+ }
+
+ def __init__(
+ self,
+ *,
+ frequency: Optional[Union[str, "_models.RecurrenceFrequency"]] = None,
+ interval: Optional[int] = None,
+ start_time: Optional[str] = None,
+ time_zone: str = "UTC",
+ schedule: Optional["_models.RecurrenceSchedule"] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword frequency: [Required] The frequency to trigger schedule. Known values are: "Minute",
+ "Hour", "Day", "Week", and "Month".
+ :paramtype frequency: str or ~azure.mgmt.machinelearningservices.models.RecurrenceFrequency
+ :keyword interval: [Required] Specifies schedule interval in conjunction with frequency.
+ :paramtype interval: int
+ :keyword start_time: The start time in yyyy-MM-ddTHH:mm:ss format.
+ :paramtype start_time: str
+ :keyword time_zone: Specifies time zone in which the schedule runs.
+ TimeZone should follow Windows time zone format. Refer:
+ https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ :paramtype time_zone: str
+ :keyword schedule: [Required] The recurrence schedule.
+ :paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
+ """
+ super().__init__(**kwargs)
+ self.frequency = frequency
+ self.interval = interval
+ self.start_time = start_time
+ self.time_zone = time_zone
+ self.schedule = schedule
+
+
class RecurrenceSchedule(_serialization.Model):
"""RecurrenceSchedule.
@@ -16533,8 +17502,8 @@ def __init__(
minutes: List[int],
month_days: Optional[List[int]] = None,
week_days: Optional[List[Union[str, "_models.WeekDay"]]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword hours: [Required] List of hours for the schedule. Required.
:paramtype hours: list[int]
@@ -16605,8 +17574,8 @@ def __init__(
start_time: Optional[str] = None,
time_zone: str = "UTC",
schedule: Optional["_models.RecurrenceSchedule"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword end_time: Specifies end time of schedule in ISO 8601, but without a UTC offset. Refer
https://en.wikipedia.org/wiki/ISO_8601.
@@ -16653,56 +17622,449 @@ class RegenerateEndpointKeysRequest(_serialization.Model):
}
_attribute_map = {
- "key_type": {"key": "keyType", "type": "str"},
- "key_value": {"key": "keyValue", "type": "str"},
+ "key_type": {"key": "keyType", "type": "str"},
+ "key_value": {"key": "keyValue", "type": "str"},
+ }
+
+ def __init__(
+ self, *, key_type: Union[str, "_models.KeyType"], key_value: Optional[str] = None, **kwargs: Any
+ ) -> None:
+ """
+ :keyword key_type: [Required] Specification for which type of key to generate. Primary or
+ Secondary. Required. Known values are: "Primary" and "Secondary".
+ :paramtype key_type: str or ~azure.mgmt.machinelearningservices.models.KeyType
+ :keyword key_value: The value the key is set to.
+ :paramtype key_value: str
+ """
+ super().__init__(**kwargs)
+ self.key_type = key_type
+ self.key_value = key_value
+
+
+class Registry(TrackedResource): # pylint: disable=too-many-instance-attributes
+ """Registry.
+
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar id: Fully qualified resource ID for the resource. Ex -
+ /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}.
+ :vartype id: str
+ :ivar name: The name of the resource.
+ :vartype name: str
+ :ivar type: The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or
+ "Microsoft.Storage/storageAccounts".
+ :vartype type: str
+ :ivar system_data: Azure Resource Manager metadata containing createdBy and modifiedBy
+ information.
+ :vartype system_data: ~azure.mgmt.machinelearningservices.models.SystemData
+ :ivar tags: Resource tags.
+ :vartype tags: dict[str, str]
+ :ivar location: The geo-location where the resource lives. Required.
+ :vartype location: str
+ :ivar identity: Managed service identity (system assigned and/or user assigned identities).
+ :vartype identity: ~azure.mgmt.machinelearningservices.models.ManagedServiceIdentity
+ :ivar kind: Metadata used by portal/tooling/etc to render different UX experiences for
+ resources of the same type.
+ :vartype kind: str
+ :ivar sku: Sku details required for ARM contract for Autoscaling.
+ :vartype sku: ~azure.mgmt.machinelearningservices.models.Sku
+ :ivar discovery_url: Discovery URL for the Registry.
+ :vartype discovery_url: str
+ :ivar intellectual_property_publisher: IntellectualPropertyPublisher for the registry.
+ :vartype intellectual_property_publisher: str
+ :ivar managed_resource_group: ResourceId of the managed RG if the registry has system created
+ resources.
+ :vartype managed_resource_group: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ :ivar ml_flow_registry_uri: MLFlow Registry URI for the Registry.
+ :vartype ml_flow_registry_uri: str
+ :ivar registry_private_endpoint_connections: Private endpoint connections info used for pending
+ connections in private link portal.
+ :vartype registry_private_endpoint_connections:
+ list[~azure.mgmt.machinelearningservices.models.RegistryPrivateEndpointConnection]
+ :ivar public_network_access: Is the Registry accessible from the internet?
+ Possible values: "Enabled" or "Disabled".
+ :vartype public_network_access: str
+ :ivar region_details: Details of each region the registry is in.
+ :vartype region_details:
+ list[~azure.mgmt.machinelearningservices.models.RegistryRegionArmDetails]
+ """
+
+ _validation = {
+ "id": {"readonly": True},
+ "name": {"readonly": True},
+ "type": {"readonly": True},
+ "system_data": {"readonly": True},
+ "location": {"required": True},
+ }
+
+ _attribute_map = {
+ "id": {"key": "id", "type": "str"},
+ "name": {"key": "name", "type": "str"},
+ "type": {"key": "type", "type": "str"},
+ "system_data": {"key": "systemData", "type": "SystemData"},
+ "tags": {"key": "tags", "type": "{str}"},
+ "location": {"key": "location", "type": "str"},
+ "identity": {"key": "identity", "type": "ManagedServiceIdentity"},
+ "kind": {"key": "kind", "type": "str"},
+ "sku": {"key": "sku", "type": "Sku"},
+ "discovery_url": {"key": "properties.discoveryUrl", "type": "str"},
+ "intellectual_property_publisher": {"key": "properties.intellectualPropertyPublisher", "type": "str"},
+ "managed_resource_group": {"key": "properties.managedResourceGroup", "type": "ArmResourceId"},
+ "ml_flow_registry_uri": {"key": "properties.mlFlowRegistryUri", "type": "str"},
+ "registry_private_endpoint_connections": {
+ "key": "properties.registryPrivateEndpointConnections",
+ "type": "[RegistryPrivateEndpointConnection]",
+ },
+ "public_network_access": {"key": "properties.publicNetworkAccess", "type": "str"},
+ "region_details": {"key": "properties.regionDetails", "type": "[RegistryRegionArmDetails]"},
+ }
+
+ def __init__(
+ self,
+ *,
+ location: str,
+ tags: Optional[Dict[str, str]] = None,
+ identity: Optional["_models.ManagedServiceIdentity"] = None,
+ kind: Optional[str] = None,
+ sku: Optional["_models.Sku"] = None,
+ discovery_url: Optional[str] = None,
+ intellectual_property_publisher: Optional[str] = None,
+ managed_resource_group: Optional["_models.ArmResourceId"] = None,
+ ml_flow_registry_uri: Optional[str] = None,
+ registry_private_endpoint_connections: Optional[List["_models.RegistryPrivateEndpointConnection"]] = None,
+ public_network_access: Optional[str] = None,
+ region_details: Optional[List["_models.RegistryRegionArmDetails"]] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword tags: Resource tags.
+ :paramtype tags: dict[str, str]
+ :keyword location: The geo-location where the resource lives. Required.
+ :paramtype location: str
+ :keyword identity: Managed service identity (system assigned and/or user assigned identities).
+ :paramtype identity: ~azure.mgmt.machinelearningservices.models.ManagedServiceIdentity
+ :keyword kind: Metadata used by portal/tooling/etc to render different UX experiences for
+ resources of the same type.
+ :paramtype kind: str
+ :keyword sku: Sku details required for ARM contract for Autoscaling.
+ :paramtype sku: ~azure.mgmt.machinelearningservices.models.Sku
+ :keyword discovery_url: Discovery URL for the Registry.
+ :paramtype discovery_url: str
+ :keyword intellectual_property_publisher: IntellectualPropertyPublisher for the registry.
+ :paramtype intellectual_property_publisher: str
+ :keyword managed_resource_group: ResourceId of the managed RG if the registry has system
+ created resources.
+ :paramtype managed_resource_group: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ :keyword ml_flow_registry_uri: MLFlow Registry URI for the Registry.
+ :paramtype ml_flow_registry_uri: str
+ :keyword registry_private_endpoint_connections: Private endpoint connections info used for
+ pending connections in private link portal.
+ :paramtype registry_private_endpoint_connections:
+ list[~azure.mgmt.machinelearningservices.models.RegistryPrivateEndpointConnection]
+ :keyword public_network_access: Is the Registry accessible from the internet?
+ Possible values: "Enabled" or "Disabled".
+ :paramtype public_network_access: str
+ :keyword region_details: Details of each region the registry is in.
+ :paramtype region_details:
+ list[~azure.mgmt.machinelearningservices.models.RegistryRegionArmDetails]
+ """
+ super().__init__(tags=tags, location=location, **kwargs)
+ self.identity = identity
+ self.kind = kind
+ self.sku = sku
+ self.discovery_url = discovery_url
+ self.intellectual_property_publisher = intellectual_property_publisher
+ self.managed_resource_group = managed_resource_group
+ self.ml_flow_registry_uri = ml_flow_registry_uri
+ self.registry_private_endpoint_connections = registry_private_endpoint_connections
+ self.public_network_access = public_network_access
+ self.region_details = region_details
+
+
+class RegistryListCredentialsResult(_serialization.Model):
+ """RegistryListCredentialsResult.
+
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ :ivar location:
+ :vartype location: str
+ :ivar username:
+ :vartype username: str
+ :ivar passwords:
+ :vartype passwords: list[~azure.mgmt.machinelearningservices.models.Password]
+ """
+
+ _validation = {
+ "location": {"readonly": True},
+ "username": {"readonly": True},
+ }
+
+ _attribute_map = {
+ "location": {"key": "location", "type": "str"},
+ "username": {"key": "username", "type": "str"},
+ "passwords": {"key": "passwords", "type": "[Password]"},
+ }
+
+ def __init__(self, *, passwords: Optional[List["_models.Password"]] = None, **kwargs: Any) -> None:
+ """
+ :keyword passwords:
+ :paramtype passwords: list[~azure.mgmt.machinelearningservices.models.Password]
+ """
+ super().__init__(**kwargs)
+ self.location = None
+ self.username = None
+ self.passwords = passwords
+
+
+class RegistryPartialManagedServiceIdentity(ManagedServiceIdentity):
+ """Managed service identity (system assigned and/or user assigned identities).
+
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar principal_id: The service principal ID of the system assigned identity. This property
+ will only be provided for a system assigned identity.
+ :vartype principal_id: str
+ :ivar tenant_id: The tenant ID of the system assigned identity. This property will only be
+ provided for a system assigned identity.
+ :vartype tenant_id: str
+ :ivar type: Type of managed service identity (where both SystemAssigned and UserAssigned types
+ are allowed). Required. Known values are: "None", "SystemAssigned", "UserAssigned", and
+ "SystemAssigned,UserAssigned".
+ :vartype type: str or ~azure.mgmt.machinelearningservices.models.ManagedServiceIdentityType
+ :ivar user_assigned_identities: The set of user assigned identities associated with the
+ resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form:
+ '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}.
+ The dictionary values can be empty objects ({}) in requests.
+ :vartype user_assigned_identities: dict[str,
+ ~azure.mgmt.machinelearningservices.models.UserAssignedIdentity]
+ """
+
+ _validation = {
+ "principal_id": {"readonly": True},
+ "tenant_id": {"readonly": True},
+ "type": {"required": True},
+ }
+
+ _attribute_map = {
+ "principal_id": {"key": "principalId", "type": "str"},
+ "tenant_id": {"key": "tenantId", "type": "str"},
+ "type": {"key": "type", "type": "str"},
+ "user_assigned_identities": {"key": "userAssignedIdentities", "type": "{UserAssignedIdentity}"},
+ }
+
+ def __init__(
+ self,
+ *,
+ type: Union[str, "_models.ManagedServiceIdentityType"],
+ user_assigned_identities: Optional[Dict[str, "_models.UserAssignedIdentity"]] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword type: Type of managed service identity (where both SystemAssigned and UserAssigned
+ types are allowed). Required. Known values are: "None", "SystemAssigned", "UserAssigned", and
+ "SystemAssigned,UserAssigned".
+ :paramtype type: str or ~azure.mgmt.machinelearningservices.models.ManagedServiceIdentityType
+ :keyword user_assigned_identities: The set of user assigned identities associated with the
+ resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form:
+ '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}.
+ The dictionary values can be empty objects ({}) in requests.
+ :paramtype user_assigned_identities: dict[str,
+ ~azure.mgmt.machinelearningservices.models.UserAssignedIdentity]
+ """
+ super().__init__(type=type, user_assigned_identities=user_assigned_identities, **kwargs)
+
+
+class RegistryPrivateEndpointConnection(_serialization.Model):
+ """Private endpoint connection definition.
+
+ :ivar id: This is the private endpoint connection name created on SRP
+ Full resource id:
+ /subscriptions/{subId}/resourceGroups/{rgName}/providers/Microsoft.MachineLearningServices/{resourceType}/{resourceName}/registryPrivateEndpointConnections/{peConnectionName}.
+ :vartype id: str
+ :ivar location: Same as workspace location.
+ :vartype location: str
+ :ivar group_ids: The group ids.
+ :vartype group_ids: list[str]
+ :ivar private_endpoint: The PE network resource that is linked to this PE connection.
+ :vartype private_endpoint: ~azure.mgmt.machinelearningservices.models.PrivateEndpointResource
+ :ivar registry_private_link_service_connection_state: The connection state.
+ :vartype registry_private_link_service_connection_state:
+ ~azure.mgmt.machinelearningservices.models.RegistryPrivateLinkServiceConnectionState
+ :ivar provisioning_state: One of null, "Succeeded", "Provisioning", "Failed". While not
+ approved, it's null.
+ :vartype provisioning_state: str
+ """
+
+ _attribute_map = {
+ "id": {"key": "id", "type": "str"},
+ "location": {"key": "location", "type": "str"},
+ "group_ids": {"key": "properties.groupIds", "type": "[str]"},
+ "private_endpoint": {"key": "properties.privateEndpoint", "type": "PrivateEndpointResource"},
+ "registry_private_link_service_connection_state": {
+ "key": "properties.registryPrivateLinkServiceConnectionState",
+ "type": "RegistryPrivateLinkServiceConnectionState",
+ },
+ "provisioning_state": {"key": "properties.provisioningState", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ id: Optional[str] = None, # pylint: disable=redefined-builtin
+ location: Optional[str] = None,
+ group_ids: Optional[List[str]] = None,
+ private_endpoint: Optional["_models.PrivateEndpointResource"] = None,
+ registry_private_link_service_connection_state: Optional[
+ "_models.RegistryPrivateLinkServiceConnectionState"
+ ] = None,
+ provisioning_state: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword id: This is the private endpoint connection name created on SRP
+ Full resource id:
+ /subscriptions/{subId}/resourceGroups/{rgName}/providers/Microsoft.MachineLearningServices/{resourceType}/{resourceName}/registryPrivateEndpointConnections/{peConnectionName}.
+ :paramtype id: str
+ :keyword location: Same as workspace location.
+ :paramtype location: str
+ :keyword group_ids: The group ids.
+ :paramtype group_ids: list[str]
+ :keyword private_endpoint: The PE network resource that is linked to this PE connection.
+ :paramtype private_endpoint: ~azure.mgmt.machinelearningservices.models.PrivateEndpointResource
+ :keyword registry_private_link_service_connection_state: The connection state.
+ :paramtype registry_private_link_service_connection_state:
+ ~azure.mgmt.machinelearningservices.models.RegistryPrivateLinkServiceConnectionState
+ :keyword provisioning_state: One of null, "Succeeded", "Provisioning", "Failed". While not
+ approved, it's null.
+ :paramtype provisioning_state: str
+ """
+ super().__init__(**kwargs)
+ self.id = id
+ self.location = location
+ self.group_ids = group_ids
+ self.private_endpoint = private_endpoint
+ self.registry_private_link_service_connection_state = registry_private_link_service_connection_state
+ self.provisioning_state = provisioning_state
+
+
+class RegistryPrivateLinkServiceConnectionState(_serialization.Model):
+ """The connection state.
+
+ :ivar actions_required: Some RP chose "None". Other RPs use this for region expansion.
+ :vartype actions_required: str
+ :ivar description: User-defined message that, per NRP doc, may be used for approval-related
+ message.
+ :vartype description: str
+ :ivar status: Connection status of the service consumer with the service provider. Known values
+ are: "Approved", "Pending", "Rejected", and "Disconnected".
+ :vartype status: str or
+ ~azure.mgmt.machinelearningservices.models.EndpointServiceConnectionStatus
+ """
+
+ _attribute_map = {
+ "actions_required": {"key": "actionsRequired", "type": "str"},
+ "description": {"key": "description", "type": "str"},
+ "status": {"key": "status", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ actions_required: Optional[str] = None,
+ description: Optional[str] = None,
+ status: Optional[Union[str, "_models.EndpointServiceConnectionStatus"]] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword actions_required: Some RP chose "None". Other RPs use this for region expansion.
+ :paramtype actions_required: str
+ :keyword description: User-defined message that, per NRP doc, may be used for approval-related
+ message.
+ :paramtype description: str
+ :keyword status: Connection status of the service consumer with the service provider. Known
+ values are: "Approved", "Pending", "Rejected", and "Disconnected".
+ :paramtype status: str or
+ ~azure.mgmt.machinelearningservices.models.EndpointServiceConnectionStatus
+ """
+ super().__init__(**kwargs)
+ self.actions_required = actions_required
+ self.description = description
+ self.status = status
+
+
+class RegistryRegionArmDetails(_serialization.Model):
+ """Details for each region the registry is in.
+
+ :ivar acr_details: List of ACR accounts.
+ :vartype acr_details: list[~azure.mgmt.machinelearningservices.models.AcrDetails]
+ :ivar location: The location where the registry exists.
+ :vartype location: str
+ :ivar storage_account_details: List of storage accounts.
+ :vartype storage_account_details:
+ list[~azure.mgmt.machinelearningservices.models.StorageAccountDetails]
+ """
+
+ _attribute_map = {
+ "acr_details": {"key": "acrDetails", "type": "[AcrDetails]"},
+ "location": {"key": "location", "type": "str"},
+ "storage_account_details": {"key": "storageAccountDetails", "type": "[StorageAccountDetails]"},
}
- def __init__(self, *, key_type: Union[str, "_models.KeyType"], key_value: Optional[str] = None, **kwargs):
+ def __init__(
+ self,
+ *,
+ acr_details: Optional[List["_models.AcrDetails"]] = None,
+ location: Optional[str] = None,
+ storage_account_details: Optional[List["_models.StorageAccountDetails"]] = None,
+ **kwargs: Any
+ ) -> None:
"""
- :keyword key_type: [Required] Specification for which type of key to generate. Primary or
- Secondary. Required. Known values are: "Primary" and "Secondary".
- :paramtype key_type: str or ~azure.mgmt.machinelearningservices.models.KeyType
- :keyword key_value: The value the key is set to.
- :paramtype key_value: str
+ :keyword acr_details: List of ACR accounts.
+ :paramtype acr_details: list[~azure.mgmt.machinelearningservices.models.AcrDetails]
+ :keyword location: The location where the registry exists.
+ :paramtype location: str
+ :keyword storage_account_details: List of storage accounts.
+ :paramtype storage_account_details:
+ list[~azure.mgmt.machinelearningservices.models.StorageAccountDetails]
"""
super().__init__(**kwargs)
- self.key_type = key_type
- self.key_value = key_value
-
+ self.acr_details = acr_details
+ self.location = location
+ self.storage_account_details = storage_account_details
-class RegistryListCredentialsResult(_serialization.Model):
- """RegistryListCredentialsResult.
- Variables are only populated by the server, and will be ignored when sending a request.
+class RegistryTrackedResourceArmPaginatedResult(_serialization.Model):
+ """A paginated list of Registry entities.
- :ivar location:
- :vartype location: str
- :ivar username:
- :vartype username: str
- :ivar passwords:
- :vartype passwords: list[~azure.mgmt.machinelearningservices.models.Password]
+ :ivar next_link: The link to the next page of Registry objects. If null, there are no
+ additional pages.
+ :vartype next_link: str
+ :ivar value: An array of objects of type Registry.
+ :vartype value: list[~azure.mgmt.machinelearningservices.models.Registry]
"""
- _validation = {
- "location": {"readonly": True},
- "username": {"readonly": True},
- }
-
_attribute_map = {
- "location": {"key": "location", "type": "str"},
- "username": {"key": "username", "type": "str"},
- "passwords": {"key": "passwords", "type": "[Password]"},
+ "next_link": {"key": "nextLink", "type": "str"},
+ "value": {"key": "value", "type": "[Registry]"},
}
- def __init__(self, *, passwords: Optional[List["_models.Password"]] = None, **kwargs):
+ def __init__(
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.Registry"]] = None, **kwargs: Any
+ ) -> None:
"""
- :keyword passwords:
- :paramtype passwords: list[~azure.mgmt.machinelearningservices.models.Password]
+ :keyword next_link: The link to the next page of Registry objects. If null, there are no
+ additional pages.
+ :paramtype next_link: str
+ :keyword value: An array of objects of type Registry.
+ :paramtype value: list[~azure.mgmt.machinelearningservices.models.Registry]
"""
super().__init__(**kwargs)
- self.location = None
- self.username = None
- self.passwords = passwords
+ self.next_link = next_link
+ self.value = value
class Regression(TableVertical, AutoMLVertical): # pylint: disable=too-many-instance-attributes
@@ -16800,8 +18162,8 @@ def __init__(
weight_column_name: Optional[str] = None,
primary_metric: Optional[Union[str, "_models.RegressionPrimaryMetrics"]] = None,
training_settings: Optional["_models.RegressionTrainingSettings"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -16933,8 +18295,8 @@ def __init__(
stack_ensemble_settings: Optional["_models.StackEnsembleSettings"] = None,
allowed_training_algorithms: Optional[List[Union[str, "_models.RegressionModels"]]] = None,
blocked_training_algorithms: Optional[List[Union[str, "_models.RegressionModels"]]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword enable_dnn_training: Enable recommendation of DNN models.
:paramtype enable_dnn_training: bool
@@ -16991,7 +18353,7 @@ class ResourceId(_serialization.Model):
"id": {"key": "id", "type": "str"},
}
- def __init__(self, *, id: str, **kwargs): # pylint: disable=redefined-builtin
+ def __init__(self, *, id: str, **kwargs: Any) -> None: # pylint: disable=redefined-builtin
"""
:keyword id: The ID of the resource. Required.
:paramtype id: str
@@ -17021,7 +18383,7 @@ class ResourceName(_serialization.Model):
"localized_value": {"key": "localizedValue", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.value = None
@@ -17065,7 +18427,7 @@ class ResourceQuota(_serialization.Model):
"unit": {"key": "unit", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.id = None
@@ -17088,7 +18450,7 @@ class Route(_serialization.Model):
"""
_validation = {
- "path": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "path": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
"port": {"required": True},
}
@@ -17097,7 +18459,7 @@ class Route(_serialization.Model):
"port": {"key": "port", "type": "int"},
}
- def __init__(self, *, path: str, port: int, **kwargs):
+ def __init__(self, *, path: str, port: int, **kwargs: Any) -> None:
"""
:keyword path: [Required] The path for the route. Required.
:paramtype path: str
@@ -17152,8 +18514,8 @@ def __init__(
value: Optional[str] = None,
value_format: Optional[Union[str, "_models.ValueFormat"]] = None,
credentials: Optional["_models.WorkspaceConnectionSharedAccessSignature"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword category: Category of the connection. Known values are: "PythonFeed",
"ContainerRegistry", and "Git".
@@ -17173,6 +18535,38 @@ def __init__(
self.credentials = credentials
+class SASCredentialDto(PendingUploadCredentialDto):
+ """SASCredentialDto.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar credential_type: [Required] Credential type used to authentication with storage.
+ Required. "SAS"
+ :vartype credential_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialType
+ :ivar sas_uri: Full SAS Uri, including the storage, container/blob path and SAS token.
+ :vartype sas_uri: str
+ """
+
+ _validation = {
+ "credential_type": {"required": True},
+ }
+
+ _attribute_map = {
+ "credential_type": {"key": "credentialType", "type": "str"},
+ "sas_uri": {"key": "sasUri", "type": "str"},
+ }
+
+ def __init__(self, *, sas_uri: Optional[str] = None, **kwargs: Any) -> None:
+ """
+ :keyword sas_uri: Full SAS Uri, including the storage, container/blob path and SAS token.
+ :paramtype sas_uri: str
+ """
+ super().__init__(**kwargs)
+ self.credential_type: str = "SAS"
+ self.sas_uri = sas_uri
+
+
class SasDatastoreCredentials(DatastoreCredentials):
"""SAS datastore credentials configuration.
@@ -17195,7 +18589,7 @@ class SasDatastoreCredentials(DatastoreCredentials):
"secrets": {"key": "secrets", "type": "SasDatastoreSecrets"},
}
- def __init__(self, *, secrets: "_models.SasDatastoreSecrets", **kwargs):
+ def __init__(self, *, secrets: "_models.SasDatastoreSecrets", **kwargs: Any) -> None:
"""
:keyword secrets: [Required] Storage container secrets. Required.
:paramtype secrets: ~azure.mgmt.machinelearningservices.models.SasDatastoreSecrets
@@ -17226,7 +18620,7 @@ class SasDatastoreSecrets(DatastoreSecrets):
"sas_token": {"key": "sasToken", "type": "str"},
}
- def __init__(self, *, sas_token: Optional[str] = None, **kwargs):
+ def __init__(self, *, sas_token: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword sas_token: Storage container SAS token.
:paramtype sas_token: str
@@ -17266,8 +18660,8 @@ def __init__(
max_node_count: int,
min_node_count: int = 0,
node_idle_time_before_scale_down: Optional[datetime.timedelta] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword max_node_count: Max number of nodes to use. Required.
:paramtype max_node_count: int
@@ -17294,7 +18688,7 @@ class ScaleSettingsInformation(_serialization.Model):
"scale_settings": {"key": "scaleSettings", "type": "ScaleSettings"},
}
- def __init__(self, *, scale_settings: Optional["_models.ScaleSettings"] = None, **kwargs):
+ def __init__(self, *, scale_settings: Optional["_models.ScaleSettings"] = None, **kwargs: Any) -> None:
"""
:keyword scale_settings: scale settings for AML Compute.
:paramtype scale_settings: ~azure.mgmt.machinelearningservices.models.ScaleSettings
@@ -17341,7 +18735,7 @@ class Schedule(Resource):
"properties": {"key": "properties", "type": "ScheduleProperties"},
}
- def __init__(self, *, properties: "_models.ScheduleProperties", **kwargs):
+ def __init__(self, *, properties: "_models.ScheduleProperties", **kwargs: Any) -> None:
"""
:keyword properties: [Required] Additional attributes of the entity. Required.
:paramtype properties: ~azure.mgmt.machinelearningservices.models.ScheduleProperties
@@ -17375,8 +18769,8 @@ def __init__(
id: Optional[str] = None, # pylint: disable=redefined-builtin
provisioning_status: Optional[Union[str, "_models.ScheduleProvisioningState"]] = None,
status: Optional[Union[str, "_models.ScheduleStatus"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword id: A system assigned id for the schedule.
:paramtype id: str
@@ -17448,8 +18842,8 @@ def __init__(
tags: Optional[Dict[str, str]] = None,
display_name: Optional[str] = None,
is_enabled: bool = True,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -17489,7 +18883,9 @@ class ScheduleResourceArmPaginatedResult(_serialization.Model):
"value": {"key": "value", "type": "[Schedule]"},
}
- def __init__(self, *, next_link: Optional[str] = None, value: Optional[List["_models.Schedule"]] = None, **kwargs):
+ def __init__(
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.Schedule"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of Schedule objects. If null, there are no
additional pages.
@@ -17529,8 +18925,8 @@ def __init__(
script_data: Optional[str] = None,
script_arguments: Optional[str] = None,
timeout: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword script_source: The storage source of the script: workspace.
:paramtype script_source: str
@@ -17567,8 +18963,8 @@ def __init__(
*,
startup_script: Optional["_models.ScriptReference"] = None,
creation_script: Optional["_models.ScriptReference"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword startup_script: Script that's run every time the machine starts.
:paramtype startup_script: ~azure.mgmt.machinelearningservices.models.ScriptReference
@@ -17591,7 +18987,7 @@ class ServiceManagedResourcesSettings(_serialization.Model):
"cosmos_db": {"key": "cosmosDb", "type": "CosmosDbSettings"},
}
- def __init__(self, *, cosmos_db: Optional["_models.CosmosDbSettings"] = None, **kwargs):
+ def __init__(self, *, cosmos_db: Optional["_models.CosmosDbSettings"] = None, **kwargs: Any) -> None:
"""
:keyword cosmos_db: The settings for the service managed cosmosdb account.
:paramtype cosmos_db: ~azure.mgmt.machinelearningservices.models.CosmosDbSettings
@@ -17644,8 +19040,8 @@ def __init__(
tenant_id: str,
authority_url: Optional[str] = None,
resource_url: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword authority_url: Authority URL used for authentication.
:paramtype authority_url: str
@@ -17689,7 +19085,7 @@ class ServicePrincipalDatastoreSecrets(DatastoreSecrets):
"client_secret": {"key": "clientSecret", "type": "str"},
}
- def __init__(self, *, client_secret: Optional[str] = None, **kwargs):
+ def __init__(self, *, client_secret: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword client_secret: Service principal secret.
:paramtype client_secret: str
@@ -17710,7 +19106,7 @@ class SetupScripts(_serialization.Model):
"scripts": {"key": "scripts", "type": "ScriptsToExecute"},
}
- def __init__(self, *, scripts: Optional["_models.ScriptsToExecute"] = None, **kwargs):
+ def __init__(self, *, scripts: Optional["_models.ScriptsToExecute"] = None, **kwargs: Any) -> None:
"""
:keyword scripts: Customized setup scripts.
:paramtype scripts: ~azure.mgmt.machinelearningservices.models.ScriptsToExecute
@@ -17753,8 +19149,8 @@ def __init__(
group_id: Optional[str] = None,
request_message: Optional[str] = None,
status: Optional[Union[str, "_models.PrivateEndpointServiceConnectionStatus"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword name: Unique name of the private link.
:paramtype name: str
@@ -17820,8 +19216,8 @@ def __init__(
size: Optional[str] = None,
family: Optional[str] = None,
capacity: Optional[int] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword name: The name of the SKU. Ex - P3. It is typically a letter+number code. Required.
:paramtype name: str
@@ -17875,8 +19271,8 @@ def __init__(
maximum: int = 0,
minimum: int = 0,
scale_type: Optional[Union[str, "_models.SkuScaleType"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword default: Gets or sets the default capacity.
:paramtype default: int
@@ -17919,8 +19315,12 @@ class SkuResource(_serialization.Model):
}
def __init__(
- self, *, capacity: Optional["_models.SkuCapacity"] = None, sku: Optional["_models.SkuSetting"] = None, **kwargs
- ):
+ self,
+ *,
+ capacity: Optional["_models.SkuCapacity"] = None,
+ sku: Optional["_models.SkuSetting"] = None,
+ **kwargs: Any
+ ) -> None:
"""
:keyword capacity: Gets or sets the Sku Capacity.
:paramtype capacity: ~azure.mgmt.machinelearningservices.models.SkuCapacity
@@ -17949,8 +19349,8 @@ class SkuResourceArmPaginatedResult(_serialization.Model):
}
def __init__(
- self, *, next_link: Optional[str] = None, value: Optional[List["_models.SkuResource"]] = None, **kwargs
- ):
+ self, *, next_link: Optional[str] = None, value: Optional[List["_models.SkuResource"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword next_link: The link to the next page of SkuResource objects. If null, there are no
additional pages.
@@ -17978,7 +19378,7 @@ class SkuSetting(_serialization.Model):
"""
_validation = {
- "name": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "name": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -17986,7 +19386,7 @@ class SkuSetting(_serialization.Model):
"tier": {"key": "tier", "type": "str"},
}
- def __init__(self, *, name: str, tier: Optional[Union[str, "_models.SkuTier"]] = None, **kwargs):
+ def __init__(self, *, name: str, tier: Optional[Union[str, "_models.SkuTier"]] = None, **kwargs: Any) -> None:
"""
:keyword name: [Required] The name of the SKU. Ex - P3. It is typically a letter+number code.
Required.
@@ -18037,8 +19437,8 @@ def __init__(
cname: Optional[str] = None,
leaf_domain_label: Optional[str] = None,
overwrite_existing_domain: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword status: Enable or disable ssl for scoring. Known values are: "Disabled", "Enabled",
and "Auto".
@@ -18093,8 +19493,8 @@ def __init__(
stack_meta_learner_k_wargs: Optional[JSON] = None,
stack_meta_learner_train_percentage: float = 0.2,
stack_meta_learner_type: Optional[Union[str, "_models.StackMetaLearnerType"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword stack_meta_learner_k_wargs: Optional parameters to pass to the initializer of the
meta-learner.
@@ -18116,6 +19516,46 @@ def __init__(
self.stack_meta_learner_type = stack_meta_learner_type
+class StorageAccountDetails(_serialization.Model):
+ """Details of storage account to be used for the Registry.
+
+ :ivar system_created_storage_account: Details of system created storage account to be used for
+ the registry.
+ :vartype system_created_storage_account:
+ ~azure.mgmt.machinelearningservices.models.SystemCreatedStorageAccount
+ :ivar user_created_storage_account: Details of user created storage account to be used for the
+ registry.
+ :vartype user_created_storage_account:
+ ~azure.mgmt.machinelearningservices.models.UserCreatedStorageAccount
+ """
+
+ _attribute_map = {
+ "system_created_storage_account": {"key": "systemCreatedStorageAccount", "type": "SystemCreatedStorageAccount"},
+ "user_created_storage_account": {"key": "userCreatedStorageAccount", "type": "UserCreatedStorageAccount"},
+ }
+
+ def __init__(
+ self,
+ *,
+ system_created_storage_account: Optional["_models.SystemCreatedStorageAccount"] = None,
+ user_created_storage_account: Optional["_models.UserCreatedStorageAccount"] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword system_created_storage_account: Details of system created storage account to be used
+ for the registry.
+ :paramtype system_created_storage_account:
+ ~azure.mgmt.machinelearningservices.models.SystemCreatedStorageAccount
+ :keyword user_created_storage_account: Details of user created storage account to be used for
+ the registry.
+ :paramtype user_created_storage_account:
+ ~azure.mgmt.machinelearningservices.models.UserCreatedStorageAccount
+ """
+ super().__init__(**kwargs)
+ self.system_created_storage_account = system_created_storage_account
+ self.user_created_storage_account = user_created_storage_account
+
+
class SweepJob(JobBaseProperties): # pylint: disable=too-many-instance-attributes
"""Sweep job definition.
@@ -18227,8 +19667,8 @@ def __init__(
inputs: Optional[Dict[str, "_models.JobInput"]] = None,
limits: Optional["_models.SweepJobLimits"] = None,
outputs: Optional[Dict[str, "_models.JobOutput"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -18335,8 +19775,8 @@ def __init__(
max_concurrent_trials: Optional[int] = None,
max_total_trials: Optional[int] = None,
trial_timeout: Optional[datetime.timedelta] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword timeout: The max run duration in ISO 8601 format, after which the job will be
cancelled. Only supports duration with precision as low as Seconds.
@@ -18424,8 +19864,8 @@ def __init__(
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
properties: Optional["_models.SynapseSparkProperties"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword compute_location: Location for the underlying compute.
:paramtype compute_location: str
@@ -18501,8 +19941,8 @@ def __init__(
resource_group: Optional[str] = None,
workspace_name: Optional[str] = None,
pool_name: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword auto_scale_properties: Auto scale properties.
:paramtype auto_scale_properties:
@@ -18540,6 +19980,114 @@ def __init__(
self.pool_name = pool_name
+class SystemCreatedAcrAccount(_serialization.Model):
+ """SystemCreatedAcrAccount.
+
+ :ivar acr_account_name: Name of the ACR account.
+ :vartype acr_account_name: str
+ :ivar acr_account_sku: SKU of the ACR account.
+ :vartype acr_account_sku: str
+ :ivar arm_resource_id: This is populated once the ACR account is created.
+ :vartype arm_resource_id: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ """
+
+ _attribute_map = {
+ "acr_account_name": {"key": "acrAccountName", "type": "str"},
+ "acr_account_sku": {"key": "acrAccountSku", "type": "str"},
+ "arm_resource_id": {"key": "armResourceId", "type": "ArmResourceId"},
+ }
+
+ def __init__(
+ self,
+ *,
+ acr_account_name: Optional[str] = None,
+ acr_account_sku: Optional[str] = None,
+ arm_resource_id: Optional["_models.ArmResourceId"] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword acr_account_name: Name of the ACR account.
+ :paramtype acr_account_name: str
+ :keyword acr_account_sku: SKU of the ACR account.
+ :paramtype acr_account_sku: str
+ :keyword arm_resource_id: This is populated once the ACR account is created.
+ :paramtype arm_resource_id: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ """
+ super().__init__(**kwargs)
+ self.acr_account_name = acr_account_name
+ self.acr_account_sku = acr_account_sku
+ self.arm_resource_id = arm_resource_id
+
+
+class SystemCreatedStorageAccount(_serialization.Model):
+ """SystemCreatedStorageAccount.
+
+ :ivar allow_blob_public_access: Public blob access allowed.
+ :vartype allow_blob_public_access: bool
+ :ivar arm_resource_id: This is populated once the storage account is created.
+ :vartype arm_resource_id: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ :ivar storage_account_hns_enabled: HNS enabled for storage account.
+ :vartype storage_account_hns_enabled: bool
+ :ivar storage_account_name: Name of the storage account.
+ :vartype storage_account_name: str
+ :ivar storage_account_type: Allowed values:
+ "Standard_LRS",
+ "Standard_GRS",
+ "Standard_RAGRS",
+ "Standard_ZRS",
+ "Standard_GZRS",
+ "Standard_RAGZRS",
+ "Premium_LRS",
+ "Premium_ZRS".
+ :vartype storage_account_type: str
+ """
+
+ _attribute_map = {
+ "allow_blob_public_access": {"key": "allowBlobPublicAccess", "type": "bool"},
+ "arm_resource_id": {"key": "armResourceId", "type": "ArmResourceId"},
+ "storage_account_hns_enabled": {"key": "storageAccountHnsEnabled", "type": "bool"},
+ "storage_account_name": {"key": "storageAccountName", "type": "str"},
+ "storage_account_type": {"key": "storageAccountType", "type": "str"},
+ }
+
+ def __init__(
+ self,
+ *,
+ allow_blob_public_access: Optional[bool] = None,
+ arm_resource_id: Optional["_models.ArmResourceId"] = None,
+ storage_account_hns_enabled: Optional[bool] = None,
+ storage_account_name: Optional[str] = None,
+ storage_account_type: Optional[str] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword allow_blob_public_access: Public blob access allowed.
+ :paramtype allow_blob_public_access: bool
+ :keyword arm_resource_id: This is populated once the storage account is created.
+ :paramtype arm_resource_id: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ :keyword storage_account_hns_enabled: HNS enabled for storage account.
+ :paramtype storage_account_hns_enabled: bool
+ :keyword storage_account_name: Name of the storage account.
+ :paramtype storage_account_name: str
+ :keyword storage_account_type: Allowed values:
+ "Standard_LRS",
+ "Standard_GRS",
+ "Standard_RAGRS",
+ "Standard_ZRS",
+ "Standard_GZRS",
+ "Standard_RAGZRS",
+ "Premium_LRS",
+ "Premium_ZRS".
+ :paramtype storage_account_type: str
+ """
+ super().__init__(**kwargs)
+ self.allow_blob_public_access = allow_blob_public_access
+ self.arm_resource_id = arm_resource_id
+ self.storage_account_hns_enabled = storage_account_hns_enabled
+ self.storage_account_name = storage_account_name
+ self.storage_account_type = storage_account_type
+
+
class SystemData(_serialization.Model):
"""Metadata pertaining to creation and last modification of the resource.
@@ -18577,8 +20125,8 @@ def __init__(
last_modified_by: Optional[str] = None,
last_modified_by_type: Optional[Union[str, "_models.CreatedByType"]] = None,
last_modified_at: Optional[datetime.datetime] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword created_by: The identity that created the resource.
:paramtype created_by: str
@@ -18630,7 +20178,7 @@ class SystemService(_serialization.Model):
"version": {"key": "version", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.system_service_type = None
@@ -18682,8 +20230,8 @@ def __init__(
enable_dnn_featurization: bool = False,
mode: Optional[Union[str, "_models.FeaturizationMode"]] = None,
transformer_params: Optional[Dict[str, List["_models.ColumnTransformer"]]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword dataset_language: Dataset language, useful for the text data.
:paramtype dataset_language: str
@@ -18755,8 +20303,8 @@ def __init__(
max_trials: int = 1000,
timeout: datetime.timedelta = "PT6H",
trial_timeout: datetime.timedelta = "PT30M",
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword enable_early_termination: Enable early termination, determines whether or not if
AutoMLJob will terminate early if there is no score improvement in last 20 iterations.
@@ -18823,8 +20371,8 @@ def __init__(
min_instances: int = 1,
polling_interval: datetime.timedelta = "PT1S",
target_utilization_percentage: int = 70,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword max_instances: The maximum number of instances that the deployment can scale to. The
quota will be reserved for max_instances.
@@ -18869,7 +20417,7 @@ class TensorFlow(DistributionConfiguration):
"worker_count": {"key": "workerCount", "type": "int"},
}
- def __init__(self, *, parameter_server_count: int = 0, worker_count: Optional[int] = None, **kwargs):
+ def __init__(self, *, parameter_server_count: int = 0, worker_count: Optional[int] = None, **kwargs: Any) -> None:
"""
:keyword parameter_server_count: Number of parameter server tasks.
:paramtype parameter_server_count: int
@@ -18886,33 +20434,33 @@ class TextClassification(NlpVertical, AutoMLVertical):
"""Text Classification task in AutoML NLP vertical.
NLP - Natural Language Processing.
- All required parameters must be populated in order to send to Azure.
+ All required parameters must be populated in order to send to Azure.
- :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
- "Warning", "Error", and "Critical".
- :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
- :ivar target_column_name: Target column name: This is prediction values column.
- Also known as label column name in context of classification tasks.
- :vartype target_column_name: str
- :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
- "Classification", "Regression", "Forecasting", "ImageClassification",
- "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
- "TextClassification", "TextClassificationMultilabel", and "TextNER".
- :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
- :ivar training_data: [Required] Training data input. Required.
- :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar featurization_settings: Featurization inputs needed for AutoML job.
- :vartype featurization_settings:
- ~azure.mgmt.machinelearningservices.models.NlpVerticalFeaturizationSettings
- :ivar limit_settings: Execution constraints for AutoMLJob.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.NlpVerticalLimitSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar primary_metric: Primary metric for Text-Classification task. Known values are:
- "AUCWeighted", "Accuracy", "NormMacroRecall", "AveragePrecisionScoreWeighted", and
- "PrecisionScoreWeighted".
- :vartype primary_metric: str or
- ~azure.mgmt.machinelearningservices.models.ClassificationPrimaryMetrics
+ :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
+ "Warning", "Error", and "Critical".
+ :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
+ :ivar target_column_name: Target column name: This is prediction values column.
+ Also known as label column name in context of classification tasks.
+ :vartype target_column_name: str
+ :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
+ "Classification", "Regression", "Forecasting", "ImageClassification",
+ "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
+ "TextClassification", "TextClassificationMultilabel", and "TextNER".
+ :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
+ :ivar training_data: [Required] Training data input. Required.
+ :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar featurization_settings: Featurization inputs needed for AutoML job.
+ :vartype featurization_settings:
+ ~azure.mgmt.machinelearningservices.models.NlpVerticalFeaturizationSettings
+ :ivar limit_settings: Execution constraints for AutoMLJob.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.NlpVerticalLimitSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar primary_metric: Primary metric for Text-Classification task. Known values are:
+ "AUCWeighted", "Accuracy", "NormMacroRecall", "AveragePrecisionScoreWeighted", and
+ "PrecisionScoreWeighted".
+ :vartype primary_metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationPrimaryMetrics
"""
_validation = {
@@ -18941,8 +20489,8 @@ def __init__(
limit_settings: Optional["_models.NlpVerticalLimitSettings"] = None,
validation_data: Optional["_models.MLTableJobInput"] = None,
primary_metric: Optional[Union[str, "_models.ClassificationPrimaryMetrics"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -18988,36 +20536,36 @@ class TextClassificationMultilabel(NlpVertical, AutoMLVertical):
"""Text Classification Multilabel task in AutoML NLP vertical.
NLP - Natural Language Processing.
- Variables are only populated by the server, and will be ignored when sending a request.
+ Variables are only populated by the server, and will be ignored when sending a request.
- All required parameters must be populated in order to send to Azure.
+ All required parameters must be populated in order to send to Azure.
- :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
- "Warning", "Error", and "Critical".
- :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
- :ivar target_column_name: Target column name: This is prediction values column.
- Also known as label column name in context of classification tasks.
- :vartype target_column_name: str
- :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
- "Classification", "Regression", "Forecasting", "ImageClassification",
- "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
- "TextClassification", "TextClassificationMultilabel", and "TextNER".
- :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
- :ivar training_data: [Required] Training data input. Required.
- :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar featurization_settings: Featurization inputs needed for AutoML job.
- :vartype featurization_settings:
- ~azure.mgmt.machinelearningservices.models.NlpVerticalFeaturizationSettings
- :ivar limit_settings: Execution constraints for AutoMLJob.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.NlpVerticalLimitSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar primary_metric: Primary metric for Text-Classification-Multilabel task.
- Currently only Accuracy is supported as primary metric, hence user need not set it explicitly.
- Known values are: "AUCWeighted", "Accuracy", "NormMacroRecall",
- "AveragePrecisionScoreWeighted", "PrecisionScoreWeighted", and "IOU".
- :vartype primary_metric: str or
- ~azure.mgmt.machinelearningservices.models.ClassificationMultilabelPrimaryMetrics
+ :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
+ "Warning", "Error", and "Critical".
+ :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
+ :ivar target_column_name: Target column name: This is prediction values column.
+ Also known as label column name in context of classification tasks.
+ :vartype target_column_name: str
+ :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
+ "Classification", "Regression", "Forecasting", "ImageClassification",
+ "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
+ "TextClassification", "TextClassificationMultilabel", and "TextNER".
+ :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
+ :ivar training_data: [Required] Training data input. Required.
+ :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar featurization_settings: Featurization inputs needed for AutoML job.
+ :vartype featurization_settings:
+ ~azure.mgmt.machinelearningservices.models.NlpVerticalFeaturizationSettings
+ :ivar limit_settings: Execution constraints for AutoMLJob.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.NlpVerticalLimitSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar primary_metric: Primary metric for Text-Classification-Multilabel task.
+ Currently only Accuracy is supported as primary metric, hence user need not set it explicitly.
+ Known values are: "AUCWeighted", "Accuracy", "NormMacroRecall",
+ "AveragePrecisionScoreWeighted", "PrecisionScoreWeighted", and "IOU".
+ :vartype primary_metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationMultilabelPrimaryMetrics
"""
_validation = {
@@ -19046,8 +20594,8 @@ def __init__(
featurization_settings: Optional["_models.NlpVerticalFeaturizationSettings"] = None,
limit_settings: Optional["_models.NlpVerticalLimitSettings"] = None,
validation_data: Optional["_models.MLTableJobInput"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -19089,36 +20637,36 @@ class TextNer(NlpVertical, AutoMLVertical):
NER - Named Entity Recognition.
NLP - Natural Language Processing.
- Variables are only populated by the server, and will be ignored when sending a request.
+ Variables are only populated by the server, and will be ignored when sending a request.
- All required parameters must be populated in order to send to Azure.
+ All required parameters must be populated in order to send to Azure.
- :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
- "Warning", "Error", and "Critical".
- :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
- :ivar target_column_name: Target column name: This is prediction values column.
- Also known as label column name in context of classification tasks.
- :vartype target_column_name: str
- :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
- "Classification", "Regression", "Forecasting", "ImageClassification",
- "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
- "TextClassification", "TextClassificationMultilabel", and "TextNER".
- :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
- :ivar training_data: [Required] Training data input. Required.
- :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar featurization_settings: Featurization inputs needed for AutoML job.
- :vartype featurization_settings:
- ~azure.mgmt.machinelearningservices.models.NlpVerticalFeaturizationSettings
- :ivar limit_settings: Execution constraints for AutoMLJob.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.NlpVerticalLimitSettings
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar primary_metric: Primary metric for Text-NER task.
- Only 'Accuracy' is supported for Text-NER, so user need not set this explicitly. Known values
- are: "AUCWeighted", "Accuracy", "NormMacroRecall", "AveragePrecisionScoreWeighted", and
- "PrecisionScoreWeighted".
- :vartype primary_metric: str or
- ~azure.mgmt.machinelearningservices.models.ClassificationPrimaryMetrics
+ :ivar log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
+ "Warning", "Error", and "Critical".
+ :vartype log_verbosity: str or ~azure.mgmt.machinelearningservices.models.LogVerbosity
+ :ivar target_column_name: Target column name: This is prediction values column.
+ Also known as label column name in context of classification tasks.
+ :vartype target_column_name: str
+ :ivar task_type: [Required] Task type for AutoMLJob. Required. Known values are:
+ "Classification", "Regression", "Forecasting", "ImageClassification",
+ "ImageClassificationMultilabel", "ImageObjectDetection", "ImageInstanceSegmentation",
+ "TextClassification", "TextClassificationMultilabel", and "TextNER".
+ :vartype task_type: str or ~azure.mgmt.machinelearningservices.models.TaskType
+ :ivar training_data: [Required] Training data input. Required.
+ :vartype training_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar featurization_settings: Featurization inputs needed for AutoML job.
+ :vartype featurization_settings:
+ ~azure.mgmt.machinelearningservices.models.NlpVerticalFeaturizationSettings
+ :ivar limit_settings: Execution constraints for AutoMLJob.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.NlpVerticalLimitSettings
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar primary_metric: Primary metric for Text-NER task.
+ Only 'Accuracy' is supported for Text-NER, so user need not set this explicitly. Known values
+ are: "AUCWeighted", "Accuracy", "NormMacroRecall", "AveragePrecisionScoreWeighted", and
+ "PrecisionScoreWeighted".
+ :vartype primary_metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationPrimaryMetrics
"""
_validation = {
@@ -19147,8 +20695,8 @@ def __init__(
featurization_settings: Optional["_models.NlpVerticalFeaturizationSettings"] = None,
limit_settings: Optional["_models.NlpVerticalLimitSettings"] = None,
validation_data: Optional["_models.MLTableJobInput"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword log_verbosity: Log verbosity for the job. Known values are: "NotSet", "Debug", "Info",
"Warning", "Error", and "Critical".
@@ -19185,6 +20733,26 @@ def __init__(
self.validation_data = validation_data
+class TmpfsOptions(_serialization.Model):
+ """Describes the tmpfs options for the container.
+
+ :ivar size: Mention the Tmpfs size.
+ :vartype size: int
+ """
+
+ _attribute_map = {
+ "size": {"key": "size", "type": "int"},
+ }
+
+ def __init__(self, *, size: Optional[int] = None, **kwargs: Any) -> None:
+ """
+ :keyword size: Mention the Tmpfs size.
+ :paramtype size: int
+ """
+ super().__init__(**kwargs)
+ self.size = size
+
+
class TrialComponent(_serialization.Model):
"""Trial component definition.
@@ -19209,7 +20777,7 @@ class TrialComponent(_serialization.Model):
_validation = {
"command": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
- "environment_id": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "environment_id": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -19230,8 +20798,8 @@ def __init__(
distribution: Optional["_models.DistributionConfiguration"] = None,
environment_variables: Optional[Dict[str, str]] = None,
resources: Optional["_models.JobResourceConfiguration"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword code_id: ARM resource ID of the code asset.
:paramtype code_id: str
@@ -19278,7 +20846,7 @@ class TritonModelJobInput(AssetJobInput, JobInput):
_validation = {
"job_input_type": {"required": True},
- "uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -19294,8 +20862,8 @@ def __init__(
uri: str,
description: Optional[str] = None,
mode: Optional[Union[str, "_models.InputDeliveryMode"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the input.
:paramtype description: str
@@ -19345,8 +20913,8 @@ def __init__(
description: Optional[str] = None,
mode: Optional[Union[str, "_models.OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the output.
:paramtype description: str
@@ -19363,7 +20931,8 @@ def __init__(
class TruncationSelectionPolicy(EarlyTerminationPolicy):
- """Defines an early termination policy that cancels a given percentage of runs at each evaluation interval.
+ """Defines an early termination policy that cancels a given percentage of runs at each evaluation
+ interval.
All required parameters must be populated in order to send to Azure.
@@ -19391,8 +20960,8 @@ class TruncationSelectionPolicy(EarlyTerminationPolicy):
}
def __init__(
- self, *, delay_evaluation: int = 0, evaluation_interval: int = 0, truncation_percentage: int = 0, **kwargs
- ):
+ self, *, delay_evaluation: int = 0, evaluation_interval: int = 0, truncation_percentage: int = 0, **kwargs: Any
+ ) -> None:
"""
:keyword delay_evaluation: Number of intervals by which to delay the first evaluation.
:paramtype delay_evaluation: int
@@ -19439,7 +21008,9 @@ class UpdateWorkspaceQuotas(_serialization.Model):
"status": {"key": "status", "type": "str"},
}
- def __init__(self, *, limit: Optional[int] = None, status: Optional[Union[str, "_models.Status"]] = None, **kwargs):
+ def __init__(
+ self, *, limit: Optional[int] = None, status: Optional[Union[str, "_models.Status"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword limit: The maximum permitted quota of the resource.
:paramtype limit: int
@@ -19478,7 +21049,7 @@ class UpdateWorkspaceQuotasResult(_serialization.Model):
"next_link": {"key": "nextLink", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.value = None
@@ -19503,15 +21074,14 @@ class UriFileDataVersion(DataVersionBaseProperties):
:ivar data_type: [Required] Specifies the type of data. Required. Known values are: "uri_file",
"uri_folder", and "mltable".
:vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
- :ivar data_uri: [Required] Uri of the data. Usage/meaning depends on
- Microsoft.MachineLearning.ManagementFrontEnd.Contracts.V20221001.Assets.DataVersionBase.DataType.
- Required.
+ :ivar data_uri: [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330. Required.
:vartype data_uri: str
"""
_validation = {
"data_type": {"required": True},
- "data_uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "data_uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -19533,8 +21103,8 @@ def __init__(
tags: Optional[Dict[str, str]] = None,
is_anonymous: bool = False,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -19546,9 +21116,8 @@ def __init__(
:paramtype is_anonymous: bool
:keyword is_archived: Is the asset archived?.
:paramtype is_archived: bool
- :keyword data_uri: [Required] Uri of the data. Usage/meaning depends on
- Microsoft.MachineLearning.ManagementFrontEnd.Contracts.V20221001.Assets.DataVersionBase.DataType.
- Required.
+ :keyword data_uri: [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330. Required.
:paramtype data_uri: str
"""
super().__init__(
@@ -19583,7 +21152,7 @@ class UriFileJobInput(AssetJobInput, JobInput):
_validation = {
"job_input_type": {"required": True},
- "uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -19599,8 +21168,8 @@ def __init__(
uri: str,
description: Optional[str] = None,
mode: Optional[Union[str, "_models.InputDeliveryMode"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the input.
:paramtype description: str
@@ -19650,8 +21219,8 @@ def __init__(
description: Optional[str] = None,
mode: Optional[Union[str, "_models.OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the output.
:paramtype description: str
@@ -19685,15 +21254,14 @@ class UriFolderDataVersion(DataVersionBaseProperties):
:ivar data_type: [Required] Specifies the type of data. Required. Known values are: "uri_file",
"uri_folder", and "mltable".
:vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
- :ivar data_uri: [Required] Uri of the data. Usage/meaning depends on
- Microsoft.MachineLearning.ManagementFrontEnd.Contracts.V20221001.Assets.DataVersionBase.DataType.
- Required.
+ :ivar data_uri: [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330. Required.
:vartype data_uri: str
"""
_validation = {
"data_type": {"required": True},
- "data_uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "data_uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -19715,8 +21283,8 @@ def __init__(
tags: Optional[Dict[str, str]] = None,
is_anonymous: bool = False,
is_archived: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: The asset description text.
:paramtype description: str
@@ -19728,9 +21296,8 @@ def __init__(
:paramtype is_anonymous: bool
:keyword is_archived: Is the asset archived?.
:paramtype is_archived: bool
- :keyword data_uri: [Required] Uri of the data. Usage/meaning depends on
- Microsoft.MachineLearning.ManagementFrontEnd.Contracts.V20221001.Assets.DataVersionBase.DataType.
- Required.
+ :keyword data_uri: [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330. Required.
:paramtype data_uri: str
"""
super().__init__(
@@ -19765,7 +21332,7 @@ class UriFolderJobInput(AssetJobInput, JobInput):
_validation = {
"job_input_type": {"required": True},
- "uri": {"required": True, "pattern": r"[a-zA-Z0-9_]"},
+ "uri": {"required": True, "min_length": 1, "pattern": r"[a-zA-Z0-9_]"},
}
_attribute_map = {
@@ -19781,8 +21348,8 @@ def __init__(
uri: str,
description: Optional[str] = None,
mode: Optional[Union[str, "_models.InputDeliveryMode"]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the input.
:paramtype description: str
@@ -19832,8 +21399,8 @@ def __init__(
description: Optional[str] = None,
mode: Optional[Union[str, "_models.OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword description: Description for the output.
:paramtype description: str
@@ -19890,7 +21457,7 @@ class Usage(_serialization.Model):
"name": {"key": "name", "type": "UsageName"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.id = None
@@ -19923,7 +21490,7 @@ class UsageName(_serialization.Model):
"localized_value": {"key": "localizedValue", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.value = None
@@ -19960,8 +21527,8 @@ def __init__(
admin_user_name: str,
admin_user_ssh_public_key: Optional[str] = None,
admin_user_password: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword admin_user_name: Name of the administrator user account which can be used to SSH to
nodes. Required.
@@ -19998,13 +21565,53 @@ class UserAssignedIdentity(_serialization.Model):
"client_id": {"key": "clientId", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.principal_id = None
self.client_id = None
+class UserCreatedAcrAccount(_serialization.Model):
+ """UserCreatedAcrAccount.
+
+ :ivar arm_resource_id: ARM ResourceId of a resource.
+ :vartype arm_resource_id: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ """
+
+ _attribute_map = {
+ "arm_resource_id": {"key": "armResourceId", "type": "ArmResourceId"},
+ }
+
+ def __init__(self, *, arm_resource_id: Optional["_models.ArmResourceId"] = None, **kwargs: Any) -> None:
+ """
+ :keyword arm_resource_id: ARM ResourceId of a resource.
+ :paramtype arm_resource_id: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ """
+ super().__init__(**kwargs)
+ self.arm_resource_id = arm_resource_id
+
+
+class UserCreatedStorageAccount(_serialization.Model):
+ """UserCreatedStorageAccount.
+
+ :ivar arm_resource_id: ARM ResourceId of a resource.
+ :vartype arm_resource_id: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ """
+
+ _attribute_map = {
+ "arm_resource_id": {"key": "armResourceId", "type": "ArmResourceId"},
+ }
+
+ def __init__(self, *, arm_resource_id: Optional["_models.ArmResourceId"] = None, **kwargs: Any) -> None:
+ """
+ :keyword arm_resource_id: ARM ResourceId of a resource.
+ :paramtype arm_resource_id: ~azure.mgmt.machinelearningservices.models.ArmResourceId
+ """
+ super().__init__(**kwargs)
+ self.arm_resource_id = arm_resource_id
+
+
class UserIdentity(IdentityConfiguration):
"""User identity configuration.
@@ -20024,7 +21631,7 @@ class UserIdentity(IdentityConfiguration):
"identity_type": {"key": "identityType", "type": "str"},
}
- def __init__(self, **kwargs):
+ def __init__(self, **kwargs: Any) -> None:
""" """
super().__init__(**kwargs)
self.identity_type: str = "UserIdentity"
@@ -20073,8 +21680,8 @@ def __init__(
value: Optional[str] = None,
value_format: Optional[Union[str, "_models.ValueFormat"]] = None,
credentials: Optional["_models.WorkspaceConnectionUsernamePassword"] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword category: Category of the connection. Known values are: "PythonFeed",
"ContainerRegistry", and "Git".
@@ -20105,7 +21712,7 @@ class VirtualMachineSchema(_serialization.Model):
"properties": {"key": "properties", "type": "VirtualMachineSchemaProperties"},
}
- def __init__(self, *, properties: Optional["_models.VirtualMachineSchemaProperties"] = None, **kwargs):
+ def __init__(self, *, properties: Optional["_models.VirtualMachineSchemaProperties"] = None, **kwargs: Any) -> None:
"""
:keyword properties:
:paramtype properties:
@@ -20184,8 +21791,8 @@ def __init__(
description: Optional[str] = None,
resource_id: Optional[str] = None,
disable_local_auth: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword properties:
:paramtype properties:
@@ -20238,7 +21845,7 @@ class VirtualMachineImage(_serialization.Model):
"id": {"key": "id", "type": "str"},
}
- def __init__(self, *, id: str, **kwargs): # pylint: disable=redefined-builtin
+ def __init__(self, *, id: str, **kwargs: Any) -> None: # pylint: disable=redefined-builtin
"""
:keyword id: Virtual Machine image path. Required.
:paramtype id: str
@@ -20284,8 +21891,8 @@ def __init__(
address: Optional[str] = None,
administrator_account: Optional["_models.VirtualMachineSshCredentials"] = None,
is_notebook_instance_compute: Optional[bool] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword virtual_machine_size: Virtual Machine size.
:paramtype virtual_machine_size: str
@@ -20323,7 +21930,9 @@ class VirtualMachineSecretsSchema(_serialization.Model):
"administrator_account": {"key": "administratorAccount", "type": "VirtualMachineSshCredentials"},
}
- def __init__(self, *, administrator_account: Optional["_models.VirtualMachineSshCredentials"] = None, **kwargs):
+ def __init__(
+ self, *, administrator_account: Optional["_models.VirtualMachineSshCredentials"] = None, **kwargs: Any
+ ) -> None:
"""
:keyword administrator_account: Admin credentials for virtual machine.
:paramtype administrator_account:
@@ -20356,7 +21965,9 @@ class VirtualMachineSecrets(ComputeSecrets, VirtualMachineSecretsSchema):
"compute_type": {"key": "computeType", "type": "str"},
}
- def __init__(self, *, administrator_account: Optional["_models.VirtualMachineSshCredentials"] = None, **kwargs):
+ def __init__(
+ self, *, administrator_account: Optional["_models.VirtualMachineSshCredentials"] = None, **kwargs: Any
+ ) -> None:
"""
:keyword administrator_account: Admin credentials for virtual machine.
:paramtype administrator_account:
@@ -20429,8 +22040,8 @@ def __init__(
*,
estimated_vm_prices: Optional["_models.EstimatedVMPrices"] = None,
supported_compute_types: Optional[List[str]] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword estimated_vm_prices: The estimated price information for using a VM.
:paramtype estimated_vm_prices: ~azure.mgmt.machinelearningservices.models.EstimatedVMPrices
@@ -20463,7 +22074,7 @@ class VirtualMachineSizeListResult(_serialization.Model):
"value": {"key": "value", "type": "[VirtualMachineSize]"},
}
- def __init__(self, *, value: Optional[List["_models.VirtualMachineSize"]] = None, **kwargs):
+ def __init__(self, *, value: Optional[List["_models.VirtualMachineSize"]] = None, **kwargs: Any) -> None:
"""
:keyword value: The list of virtual machine sizes supported by AmlCompute.
:paramtype value: list[~azure.mgmt.machinelearningservices.models.VirtualMachineSize]
@@ -20499,8 +22110,8 @@ def __init__(
password: Optional[str] = None,
public_key_data: Optional[str] = None,
private_key_data: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword username: Username of admin account.
:paramtype username: str
@@ -20518,6 +22129,103 @@ def __init__(
self.private_key_data = private_key_data
+class VolumeDefinition(_serialization.Model):
+ """Describes the volume configuration for the container.
+
+ :ivar type: Type of Volume Definition. Possible Values: bind,volume,tmpfs,npipe. Known values
+ are: "bind", "volume", "tmpfs", and "npipe".
+ :vartype type: str or ~azure.mgmt.machinelearningservices.models.VolumeDefinitionType
+ :ivar read_only: Indicate whether to mount volume as readOnly. Default value for this is false.
+ :vartype read_only: bool
+ :ivar source: Source of the mount. For bind mounts this is the host path.
+ :vartype source: str
+ :ivar target: Target of the mount. For bind mounts this is the path in the container.
+ :vartype target: str
+ :ivar consistency: Consistency of the volume.
+ :vartype consistency: str
+ :ivar bind: Bind Options of the mount.
+ :vartype bind: ~azure.mgmt.machinelearningservices.models.BindOptions
+ :ivar volume: Volume Options of the mount.
+ :vartype volume: ~azure.mgmt.machinelearningservices.models.VolumeOptions
+ :ivar tmpfs: tmpfs option of the mount.
+ :vartype tmpfs: ~azure.mgmt.machinelearningservices.models.TmpfsOptions
+ """
+
+ _attribute_map = {
+ "type": {"key": "type", "type": "str"},
+ "read_only": {"key": "readOnly", "type": "bool"},
+ "source": {"key": "source", "type": "str"},
+ "target": {"key": "target", "type": "str"},
+ "consistency": {"key": "consistency", "type": "str"},
+ "bind": {"key": "bind", "type": "BindOptions"},
+ "volume": {"key": "volume", "type": "VolumeOptions"},
+ "tmpfs": {"key": "tmpfs", "type": "TmpfsOptions"},
+ }
+
+ def __init__(
+ self,
+ *,
+ type: Union[str, "_models.VolumeDefinitionType"] = "bind",
+ read_only: Optional[bool] = None,
+ source: Optional[str] = None,
+ target: Optional[str] = None,
+ consistency: Optional[str] = None,
+ bind: Optional["_models.BindOptions"] = None,
+ volume: Optional["_models.VolumeOptions"] = None,
+ tmpfs: Optional["_models.TmpfsOptions"] = None,
+ **kwargs: Any
+ ) -> None:
+ """
+ :keyword type: Type of Volume Definition. Possible Values: bind,volume,tmpfs,npipe. Known
+ values are: "bind", "volume", "tmpfs", and "npipe".
+ :paramtype type: str or ~azure.mgmt.machinelearningservices.models.VolumeDefinitionType
+ :keyword read_only: Indicate whether to mount volume as readOnly. Default value for this is
+ false.
+ :paramtype read_only: bool
+ :keyword source: Source of the mount. For bind mounts this is the host path.
+ :paramtype source: str
+ :keyword target: Target of the mount. For bind mounts this is the path in the container.
+ :paramtype target: str
+ :keyword consistency: Consistency of the volume.
+ :paramtype consistency: str
+ :keyword bind: Bind Options of the mount.
+ :paramtype bind: ~azure.mgmt.machinelearningservices.models.BindOptions
+ :keyword volume: Volume Options of the mount.
+ :paramtype volume: ~azure.mgmt.machinelearningservices.models.VolumeOptions
+ :keyword tmpfs: tmpfs option of the mount.
+ :paramtype tmpfs: ~azure.mgmt.machinelearningservices.models.TmpfsOptions
+ """
+ super().__init__(**kwargs)
+ self.type = type
+ self.read_only = read_only
+ self.source = source
+ self.target = target
+ self.consistency = consistency
+ self.bind = bind
+ self.volume = volume
+ self.tmpfs = tmpfs
+
+
+class VolumeOptions(_serialization.Model):
+ """Describes the volume options for the container.
+
+ :ivar nocopy: Indicate whether volume is nocopy.
+ :vartype nocopy: bool
+ """
+
+ _attribute_map = {
+ "nocopy": {"key": "nocopy", "type": "bool"},
+ }
+
+ def __init__(self, *, nocopy: Optional[bool] = None, **kwargs: Any) -> None:
+ """
+ :keyword nocopy: Indicate whether volume is nocopy.
+ :paramtype nocopy: bool
+ """
+ super().__init__(**kwargs)
+ self.nocopy = nocopy
+
+
class Workspace(Resource): # pylint: disable=too-many-instance-attributes
"""An object that represents a machine learning workspace.
@@ -20697,8 +22405,8 @@ def __init__( # pylint: disable=too-many-locals
service_managed_resources_settings: Optional["_models.ServiceManagedResourcesSettings"] = None,
primary_user_assigned_identity: Optional[str] = None,
v1_legacy_mode: bool = False,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword identity: The identity of the resource.
:paramtype identity: ~azure.mgmt.machinelearningservices.models.ManagedServiceIdentity
@@ -20800,7 +22508,7 @@ class WorkspaceConnectionManagedIdentity(_serialization.Model):
"client_id": {"key": "clientId", "type": "str"},
}
- def __init__(self, *, resource_id: Optional[str] = None, client_id: Optional[str] = None, **kwargs):
+ def __init__(self, *, resource_id: Optional[str] = None, client_id: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword resource_id:
:paramtype resource_id: str
@@ -20823,7 +22531,7 @@ class WorkspaceConnectionPersonalAccessToken(_serialization.Model):
"pat": {"key": "pat", "type": "str"},
}
- def __init__(self, *, pat: Optional[str] = None, **kwargs):
+ def __init__(self, *, pat: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword pat:
:paramtype pat: str
@@ -20870,7 +22578,7 @@ class WorkspaceConnectionPropertiesV2BasicResource(Resource):
"properties": {"key": "properties", "type": "WorkspaceConnectionPropertiesV2"},
}
- def __init__(self, *, properties: "_models.WorkspaceConnectionPropertiesV2", **kwargs):
+ def __init__(self, *, properties: "_models.WorkspaceConnectionPropertiesV2", **kwargs: Any) -> None:
"""
:keyword properties: Required.
:paramtype properties:
@@ -20902,8 +22610,8 @@ class WorkspaceConnectionPropertiesV2BasicResourceArmPaginatedResult(_serializat
}
def __init__(
- self, *, value: Optional[List["_models.WorkspaceConnectionPropertiesV2BasicResource"]] = None, **kwargs
- ):
+ self, *, value: Optional[List["_models.WorkspaceConnectionPropertiesV2BasicResource"]] = None, **kwargs: Any
+ ) -> None:
"""
:keyword value:
:paramtype value:
@@ -20925,7 +22633,7 @@ class WorkspaceConnectionSharedAccessSignature(_serialization.Model):
"sas": {"key": "sas", "type": "str"},
}
- def __init__(self, *, sas: Optional[str] = None, **kwargs):
+ def __init__(self, *, sas: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword sas:
:paramtype sas: str
@@ -20948,7 +22656,7 @@ class WorkspaceConnectionUsernamePassword(_serialization.Model):
"password": {"key": "password", "type": "str"},
}
- def __init__(self, *, username: Optional[str] = None, password: Optional[str] = None, **kwargs):
+ def __init__(self, *, username: Optional[str] = None, password: Optional[str] = None, **kwargs: Any) -> None:
"""
:keyword username:
:paramtype username: str
@@ -20976,7 +22684,9 @@ class WorkspaceListResult(_serialization.Model):
"next_link": {"key": "nextLink", "type": "str"},
}
- def __init__(self, *, value: Optional[List["_models.Workspace"]] = None, next_link: Optional[str] = None, **kwargs):
+ def __init__(
+ self, *, value: Optional[List["_models.Workspace"]] = None, next_link: Optional[str] = None, **kwargs: Any
+ ) -> None:
"""
:keyword value: The list of machine learning workspaces. Since this list may be incomplete, the
nextLink field should be used to request the next list of machine learning workspaces.
@@ -21052,8 +22762,8 @@ def __init__(
public_network_access: Optional[Union[str, "_models.PublicNetworkAccess"]] = None,
application_insights: Optional[str] = None,
container_registry: Optional[str] = None,
- **kwargs
- ):
+ **kwargs: Any
+ ) -> None:
"""
:keyword tags: The resource tags for the machine learning workspace.
:paramtype tags: dict[str, str]
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/__init__.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/__init__.py
index 0065485916d9..4967e3af6930 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/__init__.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/__init__.py
@@ -15,6 +15,16 @@
from ._private_endpoint_connections_operations import PrivateEndpointConnectionsOperations
from ._private_link_resources_operations import PrivateLinkResourcesOperations
from ._workspace_connections_operations import WorkspaceConnectionsOperations
+from ._registry_code_containers_operations import RegistryCodeContainersOperations
+from ._registry_code_versions_operations import RegistryCodeVersionsOperations
+from ._registry_component_containers_operations import RegistryComponentContainersOperations
+from ._registry_component_versions_operations import RegistryComponentVersionsOperations
+from ._registry_data_containers_operations import RegistryDataContainersOperations
+from ._registry_data_versions_operations import RegistryDataVersionsOperations
+from ._registry_environment_containers_operations import RegistryEnvironmentContainersOperations
+from ._registry_environment_versions_operations import RegistryEnvironmentVersionsOperations
+from ._registry_model_containers_operations import RegistryModelContainersOperations
+from ._registry_model_versions_operations import RegistryModelVersionsOperations
from ._batch_endpoints_operations import BatchEndpointsOperations
from ._batch_deployments_operations import BatchDeploymentsOperations
from ._code_containers_operations import CodeContainersOperations
@@ -32,6 +42,7 @@
from ._online_endpoints_operations import OnlineEndpointsOperations
from ._online_deployments_operations import OnlineDeploymentsOperations
from ._schedules_operations import SchedulesOperations
+from ._registries_operations import RegistriesOperations
from ._workspace_features_operations import WorkspaceFeaturesOperations
from ._patch import __all__ as _patch_all
@@ -48,6 +59,16 @@
"PrivateEndpointConnectionsOperations",
"PrivateLinkResourcesOperations",
"WorkspaceConnectionsOperations",
+ "RegistryCodeContainersOperations",
+ "RegistryCodeVersionsOperations",
+ "RegistryComponentContainersOperations",
+ "RegistryComponentVersionsOperations",
+ "RegistryDataContainersOperations",
+ "RegistryDataVersionsOperations",
+ "RegistryEnvironmentContainersOperations",
+ "RegistryEnvironmentVersionsOperations",
+ "RegistryModelContainersOperations",
+ "RegistryModelVersionsOperations",
"BatchEndpointsOperations",
"BatchDeploymentsOperations",
"CodeContainersOperations",
@@ -65,6 +86,7 @@
"OnlineEndpointsOperations",
"OnlineDeploymentsOperations",
"SchedulesOperations",
+ "RegistriesOperations",
"WorkspaceFeaturesOperations",
]
__all__.extend([p for p in _patch_all if p not in __all__])
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_batch_deployments_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_batch_deployments_operations.py
index 944b8300d2f5..4156f1f82974 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_batch_deployments_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_batch_deployments_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -32,10 +31,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -57,7 +52,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -70,7 +65,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -102,7 +99,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -115,7 +112,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
"deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
}
@@ -142,7 +141,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -155,7 +154,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
"deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
}
@@ -182,7 +183,7 @@ def build_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -196,7 +197,9 @@ def build_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url(
"endpoint_name", endpoint_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
),
@@ -229,7 +232,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -243,7 +246,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url(
"endpoint_name", endpoint_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
),
@@ -321,9 +326,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.BatchDeploymentTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -381,8 +384,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -413,9 +417,7 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -432,8 +434,9 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -490,9 +493,7 @@ def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -516,7 +517,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -567,9 +570,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.BatchDeployment] = kwargs.pop("cls", None)
request = build_get_request(
@@ -586,8 +587,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -628,9 +630,7 @@ def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.BatchDeployment]] = kwargs.pop("cls", None)
@@ -659,8 +659,9 @@ def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -805,8 +806,8 @@ def begin_update(
:type endpoint_name: str
:param deployment_name: The identifier for the Batch inference deployment. Required.
:type deployment_name: str
- :param body: Batch inference deployment definition object. Is either a model type or a IO type.
- Required.
+ :param body: Batch inference deployment definition object. Is either a
+ PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties type or a IO type. Required.
:type body:
~azure.mgmt.machinelearningservices.models.PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties
or IO
@@ -830,9 +831,7 @@ def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchDeployment] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -899,9 +898,7 @@ def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchDeployment] = kwargs.pop("cls", None)
@@ -930,8 +927,9 @@ def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1077,8 +1075,8 @@ def begin_create_or_update(
:type endpoint_name: str
:param deployment_name: The identifier for the Batch inference deployment. Required.
:type deployment_name: str
- :param body: Batch inference deployment definition object. Is either a model type or a IO type.
- Required.
+ :param body: Batch inference deployment definition object. Is either a BatchDeployment type or
+ a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.BatchDeployment or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1100,9 +1098,7 @@ def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchDeployment] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -1131,7 +1127,9 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_batch_endpoints_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_batch_endpoints_operations.py
index 5813ab488a03..746fda3ea073 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_batch_endpoints_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_batch_endpoints_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -32,10 +31,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -55,7 +50,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -68,7 +63,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -92,7 +89,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -105,7 +102,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -126,7 +125,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -139,7 +138,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -160,7 +161,7 @@ def build_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -174,7 +175,9 @@ def build_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url(
"endpoint_name", endpoint_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
),
@@ -199,7 +202,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -213,7 +216,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url(
"endpoint_name", endpoint_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
),
@@ -238,7 +243,7 @@ def build_list_keys_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -251,7 +256,9 @@ def build_list_keys_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -315,9 +322,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.BatchEndpointTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -373,8 +378,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -405,9 +411,7 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -423,8 +427,9 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -479,9 +484,7 @@ def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -504,7 +507,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -553,9 +558,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.BatchEndpoint] = kwargs.pop("cls", None)
request = build_get_request(
@@ -571,8 +574,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -612,9 +616,7 @@ def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.BatchEndpoint]] = kwargs.pop("cls", None)
@@ -642,8 +644,9 @@ def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -777,8 +780,8 @@ def begin_update(
:type workspace_name: str
:param endpoint_name: Name for the Batch inference endpoint. Required.
:type endpoint_name: str
- :param body: Mutable batch inference endpoint definition object. Is either a model type or a IO
- type. Required.
+ :param body: Mutable batch inference endpoint definition object. Is either a
+ PartialMinimalTrackedResourceWithIdentity type or a IO type. Required.
:type body:
~azure.mgmt.machinelearningservices.models.PartialMinimalTrackedResourceWithIdentity or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -800,9 +803,7 @@ def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchEndpoint] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -867,9 +868,7 @@ def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchEndpoint] = kwargs.pop("cls", None)
@@ -897,8 +896,9 @@ def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1033,8 +1033,8 @@ def begin_create_or_update(
:type workspace_name: str
:param endpoint_name: Name for the Batch inference endpoint. Required.
:type endpoint_name: str
- :param body: Batch inference endpoint definition object. Is either a model type or a IO type.
- Required.
+ :param body: Batch inference endpoint definition object. Is either a BatchEndpoint type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.BatchEndpoint or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1055,9 +1055,7 @@ def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.BatchEndpoint] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -1085,7 +1083,9 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -1134,9 +1134,7 @@ def list_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EndpointAuthKeys] = kwargs.pop("cls", None)
request = build_list_keys_request(
@@ -1152,8 +1150,9 @@ def list_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_code_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_code_containers_operations.py
index 637d9072c910..2dddf77791a1 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_code_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_code_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -47,7 +42,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -60,7 +55,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -82,7 +79,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -95,7 +92,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -116,7 +115,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -129,7 +128,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -150,7 +151,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -164,7 +165,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
}
@@ -223,9 +226,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.CodeContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -280,8 +281,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -329,9 +331,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -347,8 +347,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -394,9 +395,7 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -412,8 +411,9 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -520,7 +520,7 @@ def create_or_update(
:type workspace_name: str
:param name: Container name. This is case-sensitive. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
+ :param body: Container entity to create or update. Is either a CodeContainer type or a IO type.
Required.
:type body: ~azure.mgmt.machinelearningservices.models.CodeContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -542,9 +542,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
@@ -572,8 +570,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_code_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_code_versions_operations.py
index 561baa83676c..d74c6c721703 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_code_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_code_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -50,12 +45,14 @@ def build_list_request(
order_by: Optional[str] = None,
top: Optional[int] = None,
skip: Optional[str] = None,
+ hash: Optional[str] = None,
+ hash_version: Optional[str] = None,
**kwargs: Any
) -> HttpRequest:
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -68,7 +65,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -82,6 +81,10 @@ def build_list_request(
_params["$top"] = _SERIALIZER.query("top", top, "int")
if skip is not None:
_params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+ if hash is not None:
+ _params["hash"] = _SERIALIZER.query("hash", hash, "str")
+ if hash_version is not None:
+ _params["hashVersion"] = _SERIALIZER.query("hash_version", hash_version, "str")
# Construct headers
_headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
@@ -95,7 +98,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -108,7 +111,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -130,7 +135,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -143,7 +148,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -165,7 +172,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -179,7 +186,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -197,6 +206,46 @@ def build_create_or_update_request(
return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+def build_create_or_get_start_pending_upload_request( # pylint: disable=name-too-long
+ resource_group_name: str, workspace_name: str, name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}/startPendingUpload",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
class CodeVersionsOperations:
"""
.. warning::
@@ -225,6 +274,8 @@ def list(
order_by: Optional[str] = None,
top: Optional[int] = None,
skip: Optional[str] = None,
+ hash: Optional[str] = None,
+ hash_version: Optional[str] = None,
**kwargs: Any
) -> Iterable["_models.CodeVersion"]:
"""List versions.
@@ -244,6 +295,11 @@ def list(
:type top: int
:param skip: Continuation token for pagination. Default value is None.
:type skip: str
+ :param hash: If specified, return CodeVersion assets with specified content hash value,
+ regardless of name. Default value is None.
+ :type hash: str
+ :param hash_version: Hash algorithm version when listing by hash. Default value is None.
+ :type hash_version: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CodeVersion or the result of cls(response)
:rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.CodeVersion]
@@ -252,9 +308,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.CodeVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -276,6 +330,8 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ hash=hash,
+ hash_version=hash_version,
api_version=api_version,
template_url=self.list.metadata["url"],
headers=_headers,
@@ -312,8 +368,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -363,9 +420,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -382,8 +437,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -433,9 +489,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
request = build_get_request(
@@ -452,8 +506,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -569,7 +624,8 @@ def create_or_update(
:type name: str
:param version: Version identifier. This is case-sensitive. Required.
:type version: str
- :param body: Version entity to create or update. Is either a model type or a IO type. Required.
+ :param body: Version entity to create or update. Is either a CodeVersion type or a IO type.
+ Required.
:type body: ~azure.mgmt.machinelearningservices.models.CodeVersion or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -590,9 +646,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
@@ -621,8 +675,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -646,3 +701,172 @@ def create_or_update(
create_or_update.metadata = {
"url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}"
}
+
+ @overload
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ workspace_name: str,
+ name: str,
+ version: str,
+ body: _models.PendingUploadRequestDto,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace. Required.
+ :type workspace_name: str
+ :param name: Container name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ workspace_name: str,
+ name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace. Required.
+ :type workspace_name: str
+ :param name: Container name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ workspace_name: str,
+ name: str,
+ version: str,
+ body: Union[_models.PendingUploadRequestDto, IO],
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace. Required.
+ :type workspace_name: str
+ :param name: Container name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Is either a PendingUploadRequestDto type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.PendingUploadResponseDto] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PendingUploadRequestDto")
+
+ request = build_create_or_get_start_pending_upload_request(
+ resource_group_name=resource_group_name,
+ workspace_name=workspace_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.create_or_get_start_pending_upload.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("PendingUploadResponseDto", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_start_pending_upload.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}/startPendingUpload"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_component_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_component_containers_operations.py
index 4b9361f4a37c..3662c37781c8 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_component_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_component_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -53,7 +48,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -66,7 +61,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -90,7 +87,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -103,7 +100,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -124,7 +123,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -137,7 +136,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -158,7 +159,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -172,7 +173,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
}
@@ -240,9 +243,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComponentContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -298,8 +299,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -347,9 +349,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -365,8 +365,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -414,9 +415,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -432,8 +431,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -540,8 +540,8 @@ def create_or_update(
:type workspace_name: str
:param name: Container name. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
- Required.
+ :param body: Container entity to create or update. Is either a ComponentContainer type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.ComponentContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -562,9 +562,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
@@ -592,8 +590,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_component_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_component_versions_operations.py
index 5e99740483db..8a7029a00f9b 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_component_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_component_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -56,7 +51,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -69,7 +64,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -98,7 +95,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -111,7 +108,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -133,7 +132,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -146,7 +145,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -168,7 +169,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -182,7 +183,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -260,9 +263,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComponentVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -321,8 +322,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -372,9 +374,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -391,8 +391,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -442,9 +443,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
request = build_get_request(
@@ -461,8 +460,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -578,7 +578,8 @@ def create_or_update(
:type name: str
:param version: Version identifier. Required.
:type version: str
- :param body: Version entity to create or update. Is either a model type or a IO type. Required.
+ :param body: Version entity to create or update. Is either a ComponentVersion type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.ComponentVersion or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -599,9 +600,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
@@ -630,8 +629,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_compute_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_compute_operations.py
index 51927e5687de..9c765109a500 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_compute_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_compute_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -32,10 +31,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -49,7 +44,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -62,7 +57,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -84,7 +81,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -97,7 +94,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -118,7 +117,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -132,7 +131,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -155,7 +156,7 @@ def build_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -169,7 +170,9 @@ def build_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -198,7 +201,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -211,7 +214,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -235,7 +240,7 @@ def build_list_nodes_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -248,7 +253,9 @@ def build_list_nodes_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -269,7 +276,7 @@ def build_list_keys_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -282,7 +289,9 @@ def build_list_keys_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -303,7 +312,7 @@ def build_start_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -316,7 +325,9 @@ def build_start_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -337,7 +348,7 @@ def build_stop_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -350,7 +361,9 @@ def build_stop_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -371,7 +384,7 @@ def build_restart_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -384,7 +397,9 @@ def build_restart_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"computeName": _SERIALIZER.url("compute_name", compute_name, "str"),
}
@@ -440,9 +455,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.PaginatedComputeResourcesList] = kwargs.pop("cls", None)
error_map = {
@@ -497,8 +510,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -545,9 +559,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
request = build_get_request(
@@ -563,8 +575,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -604,9 +617,7 @@ def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
@@ -634,8 +645,9 @@ def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -769,8 +781,8 @@ def begin_create_or_update(
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute. Required.
:type compute_name: str
- :param parameters: Payload with Machine Learning compute definition. Is either a model type or
- a IO type. Required.
+ :param parameters: Payload with Machine Learning compute definition. Is either a
+ ComputeResource type or a IO type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.ComputeResource or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -792,9 +804,7 @@ def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -859,9 +869,7 @@ def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
@@ -889,8 +897,9 @@ def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1012,8 +1021,8 @@ def begin_update(
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute. Required.
:type compute_name: str
- :param parameters: Additional parameters for cluster update. Is either a model type or a IO
- type. Required.
+ :param parameters: Additional parameters for cluster update. Is either a
+ ClusterUpdateParameters type or a IO type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.ClusterUpdateParameters or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1035,9 +1044,7 @@ def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ComputeResource] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -1102,9 +1109,7 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -1121,8 +1126,9 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1184,9 +1190,7 @@ def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1251,9 +1255,7 @@ def list_nodes(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.AmlComputeNodesInformation] = kwargs.pop("cls", None)
error_map = {
@@ -1308,8 +1310,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1355,9 +1358,7 @@ def list_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ComputeSecrets] = kwargs.pop("cls", None)
request = build_list_keys_request(
@@ -1373,8 +1374,9 @@ def list_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1409,9 +1411,7 @@ def _start_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_start_request(
@@ -1427,8 +1427,9 @@ def _start_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1473,9 +1474,7 @@ def begin_start(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1530,9 +1529,7 @@ def _stop_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_stop_request(
@@ -1548,8 +1545,9 @@ def _stop_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1594,9 +1592,7 @@ def begin_stop(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1651,9 +1647,7 @@ def _restart_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_restart_request(
@@ -1669,8 +1663,9 @@ def _restart_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1715,9 +1710,7 @@ def begin_restart(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_data_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_data_containers_operations.py
index 3b5d3acc38c6..63084343602f 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_data_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_data_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -53,7 +48,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -66,7 +61,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -90,7 +87,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -103,7 +100,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -124,7 +123,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -137,7 +136,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -158,7 +159,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -172,7 +173,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
}
@@ -239,9 +242,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DataContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -297,8 +298,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -346,9 +348,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -364,8 +364,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -411,9 +412,7 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -429,8 +428,9 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -537,7 +537,7 @@ def create_or_update(
:type workspace_name: str
:param name: Container name. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
+ :param body: Container entity to create or update. Is either a DataContainer type or a IO type.
Required.
:type body: ~azure.mgmt.machinelearningservices.models.DataContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -559,9 +559,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
@@ -589,8 +587,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_data_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_data_versions_operations.py
index 092363a5e2f3..0333ed5d9153 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_data_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_data_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -57,7 +52,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -70,7 +65,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -101,7 +98,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -114,7 +111,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -136,7 +135,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -149,7 +148,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -171,7 +172,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -185,7 +186,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -271,9 +274,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DataVersionBaseResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -333,8 +334,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -384,9 +386,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -403,8 +403,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -454,9 +455,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
request = build_get_request(
@@ -473,8 +472,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -590,7 +590,8 @@ def create_or_update(
:type name: str
:param version: Version identifier. Required.
:type version: str
- :param body: Version entity to create or update. Is either a model type or a IO type. Required.
+ :param body: Version entity to create or update. Is either a DataVersionBase type or a IO type.
+ Required.
:type body: ~azure.mgmt.machinelearningservices.models.DataVersionBase or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -611,9 +612,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
@@ -642,8 +641,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_datastores_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_datastores_operations.py
index bc01c32a0983..597558f22241 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_datastores_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_datastores_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, List, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -58,7 +53,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -71,7 +66,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -105,7 +102,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -118,7 +115,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -139,7 +138,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -152,7 +151,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -179,7 +180,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -193,7 +194,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
}
@@ -218,7 +221,7 @@ def build_list_secrets_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -231,7 +234,9 @@ def build_list_secrets_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -310,9 +315,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DatastoreResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -373,8 +376,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -422,9 +426,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -440,8 +442,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -487,9 +490,7 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.Datastore] = kwargs.pop("cls", None)
request = build_get_request(
@@ -505,8 +506,9 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -620,7 +622,7 @@ def create_or_update(
:type workspace_name: str
:param name: Datastore name. Required.
:type name: str
- :param body: Datastore entity to create or update. Is either a model type or a IO type.
+ :param body: Datastore entity to create or update. Is either a Datastore type or a IO type.
Required.
:type body: ~azure.mgmt.machinelearningservices.models.Datastore or IO
:param skip_validation: Flag to skip validation. Default value is False.
@@ -644,9 +646,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Datastore] = kwargs.pop("cls", None)
@@ -675,8 +675,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -732,9 +733,7 @@ def list_secrets(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.DatastoreSecrets] = kwargs.pop("cls", None)
request = build_list_secrets_request(
@@ -750,8 +749,9 @@ def list_secrets(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_environment_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_environment_containers_operations.py
index d80de1f2b3c7..dae5f6f1e232 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_environment_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_environment_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -53,7 +48,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -66,7 +61,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -90,7 +87,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -103,7 +100,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -124,7 +123,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -137,7 +136,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -158,7 +159,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -172,7 +173,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
}
@@ -241,9 +244,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EnvironmentContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -299,8 +300,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -348,9 +350,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -366,8 +366,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -415,9 +416,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -433,8 +432,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -541,8 +541,8 @@ def create_or_update(
:type workspace_name: str
:param name: Container name. This is case-sensitive. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
- Required.
+ :param body: Container entity to create or update. Is either a EnvironmentContainer type or a
+ IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.EnvironmentContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -563,9 +563,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
@@ -593,8 +591,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_environment_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_environment_versions_operations.py
index d898cb3c67dd..0227cfd5d9f6 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_environment_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_environment_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -56,7 +51,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -69,7 +64,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -98,7 +95,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -111,7 +108,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -133,7 +132,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -146,7 +145,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -168,7 +169,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -182,7 +183,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -260,9 +263,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EnvironmentVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -321,8 +322,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -372,9 +374,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -391,8 +391,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -442,9 +443,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
request = build_get_request(
@@ -461,8 +460,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -578,7 +578,8 @@ def create_or_update(
:type name: str
:param version: Version of EnvironmentVersion. Required.
:type version: str
- :param body: Definition of EnvironmentVersion. Is either a model type or a IO type. Required.
+ :param body: Definition of EnvironmentVersion. Is either a EnvironmentVersion type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.EnvironmentVersion or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -599,9 +600,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
@@ -630,8 +629,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_jobs_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_jobs_operations.py
index cd8bd0bd0c47..1de8a15576f8 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_jobs_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_jobs_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -32,10 +31,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -57,7 +52,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -70,7 +65,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -98,7 +95,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -111,7 +108,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"id": _SERIALIZER.url("id", id, "str"),
}
@@ -132,7 +131,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -145,7 +144,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"id": _SERIALIZER.url("id", id, "str"),
}
@@ -166,7 +167,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -180,7 +181,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"id": _SERIALIZER.url("id", id, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
}
@@ -203,7 +206,7 @@ def build_cancel_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -216,7 +219,9 @@ def build_cancel_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"id": _SERIALIZER.url("id", id, "str"),
}
@@ -287,9 +292,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.JobBaseResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -347,8 +350,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -379,9 +383,7 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -397,8 +399,9 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -451,9 +454,7 @@ def begin_delete(self, resource_group_name: str, workspace_name: str, id: str, *
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -476,7 +477,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -523,9 +526,7 @@ def get(self, resource_group_name: str, workspace_name: str, id: str, **kwargs:
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.JobBase] = kwargs.pop("cls", None)
request = build_get_request(
@@ -541,8 +542,9 @@ def get(self, resource_group_name: str, workspace_name: str, id: str, **kwargs:
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -644,7 +646,7 @@ def create_or_update(
:type workspace_name: str
:param id: The name and identifier for the Job. This is case-sensitive. Required.
:type id: str
- :param body: Job definition object. Is either a model type or a IO type. Required.
+ :param body: Job definition object. Is either a JobBase type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.JobBase or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -665,9 +667,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.JobBase] = kwargs.pop("cls", None)
@@ -695,8 +695,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -735,9 +736,7 @@ def _cancel_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_cancel_request(
@@ -753,8 +752,9 @@ def _cancel_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -804,9 +804,7 @@ def begin_cancel(self, resource_group_name: str, workspace_name: str, id: str, *
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_model_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_model_containers_operations.py
index 2c416fba2772..38fa44a89051 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_model_containers_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_model_containers_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -54,7 +49,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -67,7 +62,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -93,7 +90,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -106,7 +103,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -127,7 +126,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -140,7 +139,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -161,7 +162,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -175,7 +176,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
}
@@ -245,9 +248,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ModelContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -304,8 +305,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -353,9 +355,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -371,8 +371,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -418,9 +419,7 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
request = build_get_request(
@@ -436,8 +435,9 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -544,8 +544,8 @@ def create_or_update(
:type workspace_name: str
:param name: Container name. This is case-sensitive. Required.
:type name: str
- :param body: Container entity to create or update. Is either a model type or a IO type.
- Required.
+ :param body: Container entity to create or update. Is either a ModelContainer type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.ModelContainer or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -566,9 +566,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
@@ -596,8 +594,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_model_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_model_versions_operations.py
index 775841fe3ae4..da0bc05e9b3e 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_model_versions_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_model_versions_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -62,7 +57,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -75,7 +70,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -116,7 +113,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -129,7 +126,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -151,7 +150,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -164,7 +163,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -186,7 +187,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -200,7 +201,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
"version": _SERIALIZER.url("version", version, "str"),
}
@@ -297,9 +300,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ModelVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -364,8 +365,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -415,9 +417,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -434,8 +434,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -485,9 +486,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
request = build_get_request(
@@ -504,8 +503,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -621,7 +621,8 @@ def create_or_update(
:type name: str
:param version: Version identifier. This is case-sensitive. Required.
:type version: str
- :param body: Version entity to create or update. Is either a model type or a IO type. Required.
+ :param body: Version entity to create or update. Is either a ModelVersion type or a IO type.
+ Required.
:type body: ~azure.mgmt.machinelearningservices.models.ModelVersion or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -642,9 +643,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
@@ -673,8 +672,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_online_deployments_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_online_deployments_operations.py
index cf048b3e2993..846fb23a1323 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_online_deployments_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_online_deployments_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -32,10 +31,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -57,7 +52,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -70,7 +65,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -102,7 +99,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -115,7 +112,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
"deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
}
@@ -142,7 +141,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -155,7 +154,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
"deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
}
@@ -182,7 +183,7 @@ def build_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -196,7 +197,9 @@ def build_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url(
"endpoint_name", endpoint_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
),
@@ -229,7 +232,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -243,7 +246,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url(
"endpoint_name", endpoint_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
),
@@ -276,7 +281,7 @@ def build_get_logs_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -290,7 +295,9 @@ def build_get_logs_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
"deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
}
@@ -322,7 +329,7 @@ def build_list_skus_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -335,7 +342,9 @@ def build_list_skus_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
"deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
}
@@ -411,9 +420,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.OnlineDeploymentTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -471,8 +478,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -503,9 +511,7 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -522,8 +528,9 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -580,9 +587,7 @@ def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -606,7 +611,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -657,9 +664,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.OnlineDeployment] = kwargs.pop("cls", None)
request = build_get_request(
@@ -676,8 +681,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -718,9 +724,7 @@ def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.OnlineDeployment]] = kwargs.pop("cls", None)
@@ -749,8 +753,9 @@ def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -894,8 +899,8 @@ def begin_update(
:type endpoint_name: str
:param deployment_name: Inference Endpoint Deployment name. Required.
:type deployment_name: str
- :param body: Online Endpoint entity to apply during operation. Is either a model type or a IO
- type. Required.
+ :param body: Online Endpoint entity to apply during operation. Is either a
+ PartialMinimalTrackedResourceWithSku type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.PartialMinimalTrackedResourceWithSku or
IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -918,9 +923,7 @@ def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineDeployment] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -987,9 +990,7 @@ def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineDeployment] = kwargs.pop("cls", None)
@@ -1018,8 +1019,9 @@ def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1165,8 +1167,8 @@ def begin_create_or_update(
:type endpoint_name: str
:param deployment_name: Inference Endpoint Deployment name. Required.
:type deployment_name: str
- :param body: Inference Endpoint entity to apply during operation. Is either a model type or a
- IO type. Required.
+ :param body: Inference Endpoint entity to apply during operation. Is either a OnlineDeployment
+ type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.OnlineDeployment or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1188,9 +1190,7 @@ def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineDeployment] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -1219,7 +1219,9 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -1332,8 +1334,8 @@ def get_logs(
:type endpoint_name: str
:param deployment_name: The name and identifier for the endpoint. Required.
:type deployment_name: str
- :param body: The request containing parameters for retrieving logs. Is either a model type or a
- IO type. Required.
+ :param body: The request containing parameters for retrieving logs. Is either a
+ DeploymentLogsRequest type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.DeploymentLogsRequest or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1354,9 +1356,7 @@ def get_logs(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.DeploymentLogs] = kwargs.pop("cls", None)
@@ -1385,8 +1385,9 @@ def get_logs(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1443,9 +1444,7 @@ def list_skus(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.SkuResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -1503,8 +1502,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_online_endpoints_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_online_endpoints_operations.py
index 9d9051dce1f7..2b7b939af7cc 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_online_endpoints_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_online_endpoints_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -32,10 +31,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -60,7 +55,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -73,7 +68,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -107,7 +104,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -120,7 +117,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -141,7 +140,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -154,7 +153,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -175,7 +176,7 @@ def build_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -189,7 +190,9 @@ def build_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -212,7 +215,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -226,7 +229,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url(
"endpoint_name", endpoint_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
),
@@ -251,7 +256,7 @@ def build_list_keys_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -264,7 +269,9 @@ def build_list_keys_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -285,7 +292,7 @@ def build_regenerate_keys_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -299,7 +306,9 @@ def build_regenerate_keys_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -322,7 +331,7 @@ def build_get_token_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -335,7 +344,9 @@ def build_get_token_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"endpointName": _SERIALIZER.url("endpoint_name", endpoint_name, "str"),
}
@@ -420,9 +431,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.OnlineEndpointTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -483,8 +492,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -515,9 +525,7 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -533,8 +541,9 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -589,9 +598,7 @@ def begin_delete(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -614,7 +621,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -663,9 +672,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.OnlineEndpoint] = kwargs.pop("cls", None)
request = build_get_request(
@@ -681,8 +688,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -722,9 +730,7 @@ def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.OnlineEndpoint]] = kwargs.pop("cls", None)
@@ -752,8 +758,9 @@ def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -889,8 +896,8 @@ def begin_update(
:type workspace_name: str
:param endpoint_name: Online Endpoint name. Required.
:type endpoint_name: str
- :param body: Online Endpoint entity to apply during operation. Is either a model type or a IO
- type. Required.
+ :param body: Online Endpoint entity to apply during operation. Is either a
+ PartialMinimalTrackedResourceWithIdentity type or a IO type. Required.
:type body:
~azure.mgmt.machinelearningservices.models.PartialMinimalTrackedResourceWithIdentity or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -913,9 +920,7 @@ def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineEndpoint] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -980,9 +985,7 @@ def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineEndpoint] = kwargs.pop("cls", None)
@@ -1010,8 +1013,9 @@ def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1148,8 +1152,8 @@ def begin_create_or_update(
:type workspace_name: str
:param endpoint_name: Online Endpoint name. Required.
:type endpoint_name: str
- :param body: Online Endpoint entity to apply during operation. Is either a model type or a IO
- type. Required.
+ :param body: Online Endpoint entity to apply during operation. Is either a OnlineEndpoint type
+ or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.OnlineEndpoint or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1171,9 +1175,7 @@ def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.OnlineEndpoint] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -1201,7 +1203,9 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -1250,9 +1254,7 @@ def list_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EndpointAuthKeys] = kwargs.pop("cls", None)
request = build_list_keys_request(
@@ -1268,8 +1270,9 @@ def list_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1309,9 +1312,7 @@ def _regenerate_keys_initial( # pylint: disable=inconsistent-return-statements
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[None] = kwargs.pop("cls", None)
@@ -1339,8 +1340,9 @@ def _regenerate_keys_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1462,7 +1464,8 @@ def begin_regenerate_keys(
:type workspace_name: str
:param endpoint_name: Online Endpoint name. Required.
:type endpoint_name: str
- :param body: RegenerateKeys request . Is either a model type or a IO type. Required.
+ :param body: RegenerateKeys request . Is either a RegenerateEndpointKeysRequest type or a IO
+ type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.RegenerateEndpointKeysRequest or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1482,9 +1485,7 @@ def begin_regenerate_keys(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -1534,9 +1535,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
def get_token(
self, resource_group_name: str, workspace_name: str, endpoint_name: str, **kwargs: Any
) -> _models.EndpointAuthToken:
- """Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.
+ """Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.
- Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.
+ Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.
:param resource_group_name: The name of the resource group. The name is case insensitive.
Required.
@@ -1561,9 +1562,7 @@ def get_token(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.EndpointAuthToken] = kwargs.pop("cls", None)
request = build_get_token_request(
@@ -1579,8 +1578,9 @@ def get_token(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_operations.py
index 369a4a8166c9..7dbac1fe15f1 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, Iterable, Optional, TypeVar
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -45,7 +40,7 @@ def build_list_request(**kwargs: Any) -> HttpRequest:
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -91,9 +86,7 @@ def list(self, **kwargs: Any) -> Iterable["_models.AmlOperation"]:
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.AmlOperationListResult] = kwargs.pop("cls", None)
error_map = {
@@ -144,8 +137,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_private_endpoint_connections_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_private_endpoint_connections_operations.py
index 6be9a15c5c60..1edbf2717ad3 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_private_endpoint_connections_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_private_endpoint_connections_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -47,7 +42,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -59,7 +54,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
}
@@ -84,7 +81,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -97,7 +94,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"privateEndpointConnectionName": _SERIALIZER.url(
"private_endpoint_connection_name", private_endpoint_connection_name, "str"
),
@@ -124,7 +123,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -138,7 +137,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"privateEndpointConnectionName": _SERIALIZER.url(
"private_endpoint_connection_name", private_endpoint_connection_name, "str"
),
@@ -167,7 +168,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -180,7 +181,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"privateEndpointConnectionName": _SERIALIZER.url(
"private_endpoint_connection_name", private_endpoint_connection_name, "str"
),
@@ -237,9 +240,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.PrivateEndpointConnectionListResult] = kwargs.pop("cls", None)
error_map = {
@@ -293,8 +294,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -341,9 +343,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.PrivateEndpointConnection] = kwargs.pop("cls", None)
request = build_get_request(
@@ -359,8 +359,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -464,8 +465,8 @@ def create_or_update(
:param private_endpoint_connection_name: The name of the private endpoint connection associated
with the workspace. Required.
:type private_endpoint_connection_name: str
- :param properties: The private endpoint connection properties. Is either a model type or a IO
- type. Required.
+ :param properties: The private endpoint connection properties. Is either a
+ PrivateEndpointConnection type or a IO type. Required.
:type properties: ~azure.mgmt.machinelearningservices.models.PrivateEndpointConnection or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -486,9 +487,7 @@ def create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.PrivateEndpointConnection] = kwargs.pop("cls", None)
@@ -516,8 +515,9 @@ def create_or_update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -568,9 +568,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -586,8 +584,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_private_link_resources_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_private_link_resources_operations.py
index 330afa1b8940..a262b6f295cc 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_private_link_resources_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_private_link_resources_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, Optional, TypeVar
from azure.core.exceptions import (
@@ -28,10 +27,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -45,7 +40,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -58,7 +53,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -118,9 +115,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.PrivateLinkResourceListResult] = kwargs.pop("cls", None)
request = build_list_request(
@@ -135,8 +130,9 @@ def list(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_quotas_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_quotas_operations.py
index 926e7f8d9baa..96c18d13b1ab 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_quotas_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_quotas_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -45,7 +40,7 @@ def build_update_request(location: str, subscription_id: str, **kwargs: Any) ->
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -76,7 +71,7 @@ def build_list_request(location: str, subscription_id: str, **kwargs: Any) -> Ht
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -170,7 +165,8 @@ def update(
:param location: The location for update quota is queried. Required.
:type location: str
- :param parameters: Quota update parameters. Is either a model type or a IO type. Required.
+ :param parameters: Quota update parameters. Is either a QuotaUpdateParameters type or a IO
+ type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.QuotaUpdateParameters or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -191,9 +187,7 @@ def update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.UpdateWorkspaceQuotasResult] = kwargs.pop("cls", None)
@@ -219,8 +213,9 @@ def update(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -255,9 +250,7 @@ def list(self, location: str, **kwargs: Any) -> Iterable["_models.ResourceQuota"
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListWorkspaceQuotas] = kwargs.pop("cls", None)
error_map = {
@@ -310,8 +303,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registries_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registries_operations.py
new file mode 100644
index 000000000000..ed667ca65b08
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registries_operations.py
@@ -0,0 +1,1272 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_by_subscription_request(subscription_id: str, **kwargs: Any) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url", "/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/registries"
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_list_request(resource_group_name: str, subscription_id: str, **kwargs: Any) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(resource_group_name: str, registry_name: str, subscription_id: str, **kwargs: Any) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_update_request(
+ resource_group_name: str, registry_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PATCH", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_remove_regions_request(
+ resource_group_name: str, registry_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/removeRegions",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistriesOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registries` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list_by_subscription(self, **kwargs: Any) -> Iterable["_models.Registry"]:
+ """List registries by subscription.
+
+ List registries by subscription.
+
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either Registry or the result of cls(response)
+ :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.RegistryTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_by_subscription_request(
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.list_by_subscription.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("RegistryTrackedResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list_by_subscription.metadata = {
+ "url": "/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/registries"
+ }
+
+ @distributed_trace
+ def list(self, resource_group_name: str, **kwargs: Any) -> Iterable["_models.Registry"]:
+ """List registries.
+
+ List registries.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either Registry or the result of cls(response)
+ :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.RegistryTrackedResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("RegistryTrackedResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ @distributed_trace
+ def begin_delete(self, resource_group_name: str, registry_name: str, **kwargs: Any) -> LROPoller[None]:
+ """Delete registry.
+
+ Delete registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ @distributed_trace
+ def get(self, resource_group_name: str, registry_name: str, **kwargs: Any) -> _models.Registry:
+ """Get registry.
+
+ Get registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: Registry or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.Registry
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ @overload
+ def update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: _models.PartialRegistryPartialTrackedResource,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.Registry:
+ """Update tags.
+
+ Update tags.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PartialRegistryPartialTrackedResource
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: Registry or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.Registry
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.Registry:
+ """Update tags.
+
+ Update tags.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: Registry or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.Registry
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: Union[_models.PartialRegistryPartialTrackedResource, IO],
+ **kwargs: Any
+ ) -> _models.Registry:
+ """Update tags.
+
+ Update tags.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Is either a
+ PartialRegistryPartialTrackedResource type or a IO type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PartialRegistryPartialTrackedResource or
+ IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: Registry or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.Registry
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PartialRegistryPartialTrackedResource")
+
+ request = build_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.update.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ def _create_or_update_initial(
+ self, resource_group_name: str, registry_name: str, body: Union[_models.Registry, IO], **kwargs: Any
+ ) -> _models.Registry:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "Registry")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ if response.status_code == 200:
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if response.status_code == 201:
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: _models.Registry,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.Registry]:
+ """Create or update registry.
+
+ Create or update registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.Registry
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either Registry or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.Registry]:
+ """Create or update registry.
+
+ Create or update registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either Registry or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self, resource_group_name: str, registry_name: str, body: Union[_models.Registry, IO], **kwargs: Any
+ ) -> LROPoller[_models.Registry]:
+ """Create or update registry.
+
+ Create or update registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Is either a Registry type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.Registry or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either Registry or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("Registry", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "azure-async-operation"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}"
+ }
+
+ def _remove_regions_initial(
+ self, resource_group_name: str, registry_name: str, body: Union[_models.Registry, IO], **kwargs: Any
+ ) -> Optional[_models.Registry]:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[Optional[_models.Registry]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "Registry")
+
+ request = build_remove_regions_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._remove_regions_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = None
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("Registry", pipeline_response)
+
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers)
+
+ return deserialized
+
+ _remove_regions_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/removeRegions"
+ }
+
+ @overload
+ def begin_remove_regions(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: _models.Registry,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.Registry]:
+ """Remove regions from registry.
+
+ Remove regions from registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.Registry
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either Registry or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_remove_regions(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.Registry]:
+ """Remove regions from registry.
+
+ Remove regions from registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either Registry or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_remove_regions(
+ self, resource_group_name: str, registry_name: str, body: Union[_models.Registry, IO], **kwargs: Any
+ ) -> LROPoller[_models.Registry]:
+ """Remove regions from registry.
+
+ Remove regions from registry.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param body: Details required to create the registry. Is either a Registry type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.Registry or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either Registry or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.Registry]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.Registry] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._remove_regions_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("Registry", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_remove_regions.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/removeRegions"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_code_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_code_containers_operations.py
new file mode 100644
index 000000000000..5aa24deb5353
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_code_containers_operations.py
@@ -0,0 +1,761 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str, registry_name: str, subscription_id: str, *, skip: Optional[str] = None, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, code_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "codeName": _SERIALIZER.url("code_name", code_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, code_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "codeName": _SERIALIZER.url("code_name", code_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, code_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "codeName": _SERIALIZER.url("code_name", code_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryCodeContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_code_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self, resource_group_name: str, registry_name: str, skip: Optional[str] = None, **kwargs: Any
+ ) -> Iterable["_models.CodeContainer"]:
+ """List containers.
+
+ List containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either CodeContainer or the result of cls(response)
+ :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.CodeContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.CodeContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("CodeContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, code_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, code_name: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete Code container.
+
+ Delete Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
+
+ @distributed_trace
+ def get(self, resource_group_name: str, registry_name: str, code_name: str, **kwargs: Any) -> _models.CodeContainer:
+ """Get Code container.
+
+ Get Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: CodeContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.CodeContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("CodeContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ body: Union[_models.CodeContainer, IO],
+ **kwargs: Any
+ ) -> _models.CodeContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "CodeContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("CodeContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("CodeContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ body: _models.CodeContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.CodeContainer]:
+ """Create or update Code container.
+
+ Create or update Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.CodeContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either CodeContainer or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.CodeContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.CodeContainer]:
+ """Create or update Code container.
+
+ Create or update Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either CodeContainer or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.CodeContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ body: Union[_models.CodeContainer, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.CodeContainer]:
+ """Create or update Code container.
+
+ Create or update Code container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param body: Container entity to create or update. Is either a CodeContainer type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.CodeContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either CodeContainer or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.CodeContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.CodeContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("CodeContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_code_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_code_versions_operations.py
new file mode 100644
index 000000000000..715f14bdb5bc
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_code_versions_operations.py
@@ -0,0 +1,1026 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ subscription_id: str,
+ *,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "codeName": _SERIALIZER.url("code_name", code_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if order_by is not None:
+ _params["$orderBy"] = _SERIALIZER.query("order_by", order_by, "str")
+ if top is not None:
+ _params["$top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, code_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "codeName": _SERIALIZER.url("code_name", code_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, code_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "codeName": _SERIALIZER.url("code_name", code_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, code_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "codeName": _SERIALIZER.url("code_name", code_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_get_start_pending_upload_request( # pylint: disable=name-too-long
+ resource_group_name: str, registry_name: str, code_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}/startPendingUpload",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "codeName": _SERIALIZER.url("code_name", code_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryCodeVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_code_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.CodeVersion"]:
+ """List versions.
+
+ List versions.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param order_by: Ordering of list. Default value is None.
+ :type order_by: str
+ :param top: Maximum number of records to return. Default value is None.
+ :type top: int
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either CodeVersion or the result of cls(response)
+ :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.CodeVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.CodeVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ subscription_id=self._config.subscription_id,
+ order_by=order_by,
+ top=top,
+ skip=skip,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("CodeVersionResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, code_name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, code_name: str, version: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ @distributed_trace
+ def get(
+ self, resource_group_name: str, registry_name: str, code_name: str, version: str, **kwargs: Any
+ ) -> _models.CodeVersion:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: CodeVersion or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.CodeVersion
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("CodeVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: Union[_models.CodeVersion, IO],
+ **kwargs: Any
+ ) -> _models.CodeVersion:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "CodeVersion")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("CodeVersion", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("CodeVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: _models.CodeVersion,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.CodeVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.CodeVersion
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either CodeVersion or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.CodeVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.CodeVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either CodeVersion or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.CodeVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: Union[_models.CodeVersion, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.CodeVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Container name. Required.
+ :type code_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a CodeVersion type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.CodeVersion or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either CodeVersion or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.CodeVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.CodeVersion] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("CodeVersion", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"
+ }
+
+ @overload
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: _models.PendingUploadRequestDto,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Pending upload name. This is case-sensitive. Required.
+ :type code_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Pending upload name. This is case-sensitive. Required.
+ :type code_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: Union[_models.PendingUploadRequestDto, IO],
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param code_name: Pending upload name. This is case-sensitive. Required.
+ :type code_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Is either a PendingUploadRequestDto type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.PendingUploadResponseDto] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PendingUploadRequestDto")
+
+ request = build_create_or_get_start_pending_upload_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.create_or_get_start_pending_upload.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("PendingUploadResponseDto", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_start_pending_upload.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}/startPendingUpload"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_component_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_component_containers_operations.py
new file mode 100644
index 000000000000..ad5c7506387c
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_component_containers_operations.py
@@ -0,0 +1,773 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str, registry_name: str, subscription_id: str, *, skip: Optional[str] = None, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, component_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "componentName": _SERIALIZER.url(
+ "component_name", component_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, component_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "componentName": _SERIALIZER.url(
+ "component_name", component_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, component_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "componentName": _SERIALIZER.url(
+ "component_name", component_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryComponentContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_component_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self, resource_group_name: str, registry_name: str, skip: Optional[str] = None, **kwargs: Any
+ ) -> Iterable["_models.ComponentContainer"]:
+ """List containers.
+
+ List containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either ComponentContainer or the result of cls(response)
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.ComponentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ComponentContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("ComponentContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, component_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, component_name: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete container.
+
+ Delete container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
+
+ @distributed_trace
+ def get(
+ self, resource_group_name: str, registry_name: str, component_name: str, **kwargs: Any
+ ) -> _models.ComponentContainer:
+ """Get container.
+
+ Get container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: ComponentContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.ComponentContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("ComponentContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ body: Union[_models.ComponentContainer, IO],
+ **kwargs: Any
+ ) -> _models.ComponentContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "ComponentContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("ComponentContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("ComponentContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ body: _models.ComponentContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ComponentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ComponentContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ComponentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ComponentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ComponentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ComponentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ComponentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ body: Union[_models.ComponentContainer, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.ComponentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param body: Container entity to create or update. Is either a ComponentContainer type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ComponentContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ComponentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ComponentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ComponentContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("ComponentContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_component_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_component_versions_operations.py
new file mode 100644
index 000000000000..fcdba5c9f2d6
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_component_versions_operations.py
@@ -0,0 +1,826 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ subscription_id: str,
+ *,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "componentName": _SERIALIZER.url(
+ "component_name", component_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if order_by is not None:
+ _params["$orderBy"] = _SERIALIZER.query("order_by", order_by, "str")
+ if top is not None:
+ _params["$top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, component_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "componentName": _SERIALIZER.url(
+ "component_name", component_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, component_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "componentName": _SERIALIZER.url(
+ "component_name", component_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, component_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "componentName": _SERIALIZER.url(
+ "component_name", component_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryComponentVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_component_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.ComponentVersion"]:
+ """List versions.
+
+ List versions.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param order_by: Ordering of list. Default value is None.
+ :type order_by: str
+ :param top: Maximum number of records to return. Default value is None.
+ :type top: int
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either ComponentVersion or the result of cls(response)
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.ComponentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ComponentVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ subscription_id=self._config.subscription_id,
+ order_by=order_by,
+ top=top,
+ skip=skip,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("ComponentVersionResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, component_name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, component_name: str, version: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
+
+ @distributed_trace
+ def get(
+ self, resource_group_name: str, registry_name: str, component_name: str, version: str, **kwargs: Any
+ ) -> _models.ComponentVersion:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: ComponentVersion or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.ComponentVersion
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("ComponentVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ version: str,
+ body: Union[_models.ComponentVersion, IO],
+ **kwargs: Any
+ ) -> _models.ComponentVersion:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "ComponentVersion")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("ComponentVersion", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("ComponentVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ version: str,
+ body: _models.ComponentVersion,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ComponentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ComponentVersion
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ComponentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ComponentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ComponentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ComponentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ComponentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ component_name: str,
+ version: str,
+ body: Union[_models.ComponentVersion, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.ComponentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param component_name: Container name. Required.
+ :type component_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a ComponentVersion type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ComponentVersion or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ComponentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ComponentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ComponentVersion] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ component_name=component_name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("ComponentVersion", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_data_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_data_containers_operations.py
new file mode 100644
index 000000000000..fd5226d5d10f
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_data_containers_operations.py
@@ -0,0 +1,776 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str,
+ registry_name: str,
+ subscription_id: str,
+ *,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+ if list_view_type is not None:
+ _params["listViewType"] = _SERIALIZER.query("list_view_type", list_view_type, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryDataContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_data_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.DataContainer"]:
+ """List Data containers.
+
+ List Data containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either DataContainer or the result of cls(response)
+ :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.DataContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.DataContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("DataContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
+
+ @distributed_trace
+ def begin_delete(self, resource_group_name: str, registry_name: str, name: str, **kwargs: Any) -> LROPoller[None]:
+ """Delete container.
+
+ Delete container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
+
+ @distributed_trace
+ def get(self, resource_group_name: str, registry_name: str, name: str, **kwargs: Any) -> _models.DataContainer:
+ """Get container.
+
+ Get container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: DataContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.DataContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("DataContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ body: Union[_models.DataContainer, IO],
+ **kwargs: Any
+ ) -> _models.DataContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "DataContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("DataContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("DataContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ body: _models.DataContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.DataContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.DataContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either DataContainer or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.DataContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.DataContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either DataContainer or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.DataContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ body: Union[_models.DataContainer, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.DataContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param body: Container entity to create or update. Is either a DataContainer type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.DataContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either DataContainer or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.DataContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.DataContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("DataContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_data_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_data_versions_operations.py
new file mode 100644
index 000000000000..26519d8c88a9
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_data_versions_operations.py
@@ -0,0 +1,1050 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ subscription_id: str,
+ *,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ tags: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if order_by is not None:
+ _params["$orderBy"] = _SERIALIZER.query("order_by", order_by, "str")
+ if top is not None:
+ _params["$top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+ if tags is not None:
+ _params["$tags"] = _SERIALIZER.query("tags", tags, "str")
+ if list_view_type is not None:
+ _params["listViewType"] = _SERIALIZER.query("list_view_type", list_view_type, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_get_start_pending_upload_request( # pylint: disable=name-too-long
+ resource_group_name: str, registry_name: str, name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}/startPendingUpload",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "name": _SERIALIZER.url("name", name, "str"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryDataVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_data_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ tags: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.DataVersionBase"]:
+ """List data versions in the data container.
+
+ List data versions in the data container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Data container's name. Required.
+ :type name: str
+ :param order_by: Please choose OrderBy value from ['createdtime', 'modifiedtime']. Default
+ value is None.
+ :type order_by: str
+ :param top: Top count of results, top count cannot be greater than the page size.
+ If topCount > page size, results with be default page size count
+ will be returned. Default value is None.
+ :type top: int
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param tags: Comma-separated list of tag names (and optionally values). Example:
+ tag1,tag2=value2. Default value is None.
+ :type tags: str
+ :param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
+ ListViewType.All]View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either DataVersionBase or the result of cls(response)
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.DataVersionBase]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.DataVersionBaseResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ subscription_id=self._config.subscription_id,
+ order_by=order_by,
+ top=top,
+ skip=skip,
+ tags=tags,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("DataVersionBaseResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, name: str, version: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ @distributed_trace
+ def get(
+ self, resource_group_name: str, registry_name: str, name: str, version: str, **kwargs: Any
+ ) -> _models.DataVersionBase:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: DataVersionBase or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.DataVersionBase
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("DataVersionBase", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: Union[_models.DataVersionBase, IO],
+ **kwargs: Any
+ ) -> _models.DataVersionBase:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "DataVersionBase")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("DataVersionBase", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("DataVersionBase", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: _models.DataVersionBase,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.DataVersionBase]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.DataVersionBase
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either DataVersionBase or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.DataVersionBase]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.DataVersionBase]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either DataVersionBase or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.DataVersionBase]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: Union[_models.DataVersionBase, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.DataVersionBase]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Container name. Required.
+ :type name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a DataVersionBase type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.DataVersionBase or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either DataVersionBase or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.DataVersionBase]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.DataVersionBase] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("DataVersionBase", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"
+ }
+
+ @overload
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: _models.PendingUploadRequestDto,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a data asset to.
+
+ Generate a storage location and credential for the client to upload a data asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Data asset name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a data asset to.
+
+ Generate a storage location and credential for the client to upload a data asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Data asset name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ name: str,
+ version: str,
+ body: Union[_models.PendingUploadRequestDto, IO],
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a data asset to.
+
+ Generate a storage location and credential for the client to upload a data asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param name: Data asset name. This is case-sensitive. Required.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Is either a PendingUploadRequestDto type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.PendingUploadResponseDto] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PendingUploadRequestDto")
+
+ request = build_create_or_get_start_pending_upload_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ name=name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.create_or_get_start_pending_upload.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("PendingUploadResponseDto", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_start_pending_upload.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}/startPendingUpload"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_environment_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_environment_containers_operations.py
new file mode 100644
index 000000000000..2a06796b076d
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_environment_containers_operations.py
@@ -0,0 +1,791 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str,
+ registry_name: str,
+ subscription_id: str,
+ *,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+ if list_view_type is not None:
+ _params["listViewType"] = _SERIALIZER.query("list_view_type", list_view_type, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, environment_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "environmentName": _SERIALIZER.url(
+ "environment_name", environment_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, environment_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "environmentName": _SERIALIZER.url(
+ "environment_name", environment_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, environment_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "environmentName": _SERIALIZER.url(
+ "environment_name", environment_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryEnvironmentContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_environment_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.EnvironmentContainer"]:
+ """List environment containers.
+
+ List environment containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either EnvironmentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.EnvironmentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.EnvironmentContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("EnvironmentContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, environment_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, environment_name: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete container.
+
+ Delete container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
+
+ @distributed_trace
+ def get(
+ self, resource_group_name: str, registry_name: str, environment_name: str, **kwargs: Any
+ ) -> _models.EnvironmentContainer:
+ """Get container.
+
+ Get container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. This is case-sensitive. Required.
+ :type environment_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: EnvironmentContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.EnvironmentContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("EnvironmentContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ body: Union[_models.EnvironmentContainer, IO],
+ **kwargs: Any
+ ) -> _models.EnvironmentContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "EnvironmentContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("EnvironmentContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("EnvironmentContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ body: _models.EnvironmentContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.EnvironmentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.EnvironmentContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either EnvironmentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.EnvironmentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either EnvironmentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ body: Union[_models.EnvironmentContainer, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.EnvironmentContainer]:
+ """Create or update container.
+
+ Create or update container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param body: Container entity to create or update. Is either a EnvironmentContainer type or a
+ IO type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.EnvironmentContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either EnvironmentContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.EnvironmentContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("EnvironmentContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_environment_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_environment_versions_operations.py
new file mode 100644
index 000000000000..b8b75e0ca8b2
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_environment_versions_operations.py
@@ -0,0 +1,849 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ subscription_id: str,
+ *,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "environmentName": _SERIALIZER.url(
+ "environment_name", environment_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if order_by is not None:
+ _params["$orderBy"] = _SERIALIZER.query("order_by", order_by, "str")
+ if top is not None:
+ _params["$top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+ if list_view_type is not None:
+ _params["listViewType"] = _SERIALIZER.query("list_view_type", list_view_type, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ subscription_id: str,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "environmentName": _SERIALIZER.url(
+ "environment_name", environment_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ subscription_id: str,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "environmentName": _SERIALIZER.url(
+ "environment_name", environment_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ subscription_id: str,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "environmentName": _SERIALIZER.url(
+ "environment_name", environment_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"
+ ),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryEnvironmentVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_environment_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.EnvironmentVersion"]:
+ """List versions.
+
+ List versions.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. This is case-sensitive. Required.
+ :type environment_name: str
+ :param order_by: Ordering of list. Default value is None.
+ :type order_by: str
+ :param top: Maximum number of records to return. Default value is None.
+ :type top: int
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either EnvironmentVersion or the result of cls(response)
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.EnvironmentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.EnvironmentVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ subscription_id=self._config.subscription_id,
+ order_by=order_by,
+ top=top,
+ skip=skip,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("EnvironmentVersionResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, environment_name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, environment_name: str, version: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
+
+ @distributed_trace
+ def get(
+ self, resource_group_name: str, registry_name: str, environment_name: str, version: str, **kwargs: Any
+ ) -> _models.EnvironmentVersion:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. This is case-sensitive. Required.
+ :type environment_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: EnvironmentVersion or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.EnvironmentVersion
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("EnvironmentVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ body: Union[_models.EnvironmentVersion, IO],
+ **kwargs: Any
+ ) -> _models.EnvironmentVersion:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "EnvironmentVersion")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("EnvironmentVersion", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("EnvironmentVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ body: _models.EnvironmentVersion,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.EnvironmentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.EnvironmentVersion
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either EnvironmentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.EnvironmentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either EnvironmentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ environment_name: str,
+ version: str,
+ body: Union[_models.EnvironmentVersion, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.EnvironmentVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param environment_name: Container name. Required.
+ :type environment_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a EnvironmentVersion type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.EnvironmentVersion or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either EnvironmentVersion or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.EnvironmentVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.EnvironmentVersion] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ environment_name=environment_name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("EnvironmentVersion", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_model_containers_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_model_containers_operations.py
new file mode 100644
index 000000000000..2b08ce523a08
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_model_containers_operations.py
@@ -0,0 +1,783 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str,
+ registry_name: str,
+ subscription_id: str,
+ *,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+ if list_view_type is not None:
+ _params["listViewType"] = _SERIALIZER.query("list_view_type", list_view_type, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, model_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "modelName": _SERIALIZER.url("model_name", model_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, model_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "modelName": _SERIALIZER.url("model_name", model_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, model_name: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "modelName": _SERIALIZER.url("model_name", model_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryModelContainersOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_model_containers` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ skip: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.ModelContainer"]:
+ """List model containers.
+
+ List model containers.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either ModelContainer or the result of cls(response)
+ :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.ModelContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ModelContainerResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("ModelContainerResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, model_name: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, model_name: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete container.
+
+ Delete container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
+
+ @distributed_trace
+ def get(
+ self, resource_group_name: str, registry_name: str, model_name: str, **kwargs: Any
+ ) -> _models.ModelContainer:
+ """Get container.
+
+ Get container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. This is case-sensitive. Required.
+ :type model_name: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: ModelContainer or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.ModelContainer
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("ModelContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ body: Union[_models.ModelContainer, IO],
+ **kwargs: Any
+ ) -> _models.ModelContainer:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "ModelContainer")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("ModelContainer", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("ModelContainer", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ body: _models.ModelContainer,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ModelContainer]:
+ """Create or update model container.
+
+ Create or update model container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ModelContainer
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ModelContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ModelContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ModelContainer]:
+ """Create or update model container.
+
+ Create or update model container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param body: Container entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ModelContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ModelContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ body: Union[_models.ModelContainer, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.ModelContainer]:
+ """Create or update model container.
+
+ Create or update model container.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param body: Container entity to create or update. Is either a ModelContainer type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ModelContainer or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ModelContainer or the result of
+ cls(response)
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ModelContainer]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ModelContainer] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("ModelContainer", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_model_versions_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_model_versions_operations.py
new file mode 100644
index 000000000000..2c3e9922f220
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_registry_model_versions_operations.py
@@ -0,0 +1,1064 @@
+# pylint: disable=too-many-lines
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+from azure.core.pipeline import PipelineResponse
+from azure.core.pipeline.transport import HttpResponse
+from azure.core.polling import LROPoller, NoPolling, PollingMethod
+from azure.core.rest import HttpRequest
+from azure.core.tracing.decorator import distributed_trace
+from azure.core.utils import case_insensitive_dict
+from azure.mgmt.core.exceptions import ARMErrorFormat
+from azure.mgmt.core.polling.arm_polling import ARMPolling
+
+from .. import models as _models
+from .._serialization import Serializer
+from .._vendor import _convert_request, _format_url_section
+
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_list_request(
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ subscription_id: str,
+ *,
+ skip: Optional[str] = None,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ version: Optional[str] = None,
+ description: Optional[str] = None,
+ tags: Optional[str] = None,
+ properties: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "modelName": _SERIALIZER.url("model_name", model_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if skip is not None:
+ _params["$skip"] = _SERIALIZER.query("skip", skip, "str")
+ if order_by is not None:
+ _params["$orderBy"] = _SERIALIZER.query("order_by", order_by, "str")
+ if top is not None:
+ _params["$top"] = _SERIALIZER.query("top", top, "int")
+ if version is not None:
+ _params["version"] = _SERIALIZER.query("version", version, "str")
+ if description is not None:
+ _params["description"] = _SERIALIZER.query("description", description, "str")
+ if tags is not None:
+ _params["tags"] = _SERIALIZER.query("tags", tags, "str")
+ if properties is not None:
+ _params["properties"] = _SERIALIZER.query("properties", properties, "str")
+ if list_view_type is not None:
+ _params["listViewType"] = _SERIALIZER.query("list_view_type", list_view_type, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_delete_request(
+ resource_group_name: str, registry_name: str, model_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "modelName": _SERIALIZER.url("model_name", model_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_get_request(
+ resource_group_name: str, registry_name: str, model_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "modelName": _SERIALIZER.url("model_name", model_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_update_request(
+ resource_group_name: str, registry_name: str, model_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "modelName": _SERIALIZER.url("model_name", model_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_create_or_get_start_pending_upload_request( # pylint: disable=name-too-long
+ resource_group_name: str, registry_name: str, model_name: str, version: str, subscription_id: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = kwargs.pop(
+ "template_url",
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}/startPendingUpload",
+ ) # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, "str", min_length=1),
+ "resourceGroupName": _SERIALIZER.url(
+ "resource_group_name", resource_group_name, "str", max_length=90, min_length=1
+ ),
+ "registryName": _SERIALIZER.url(
+ "registry_name", registry_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{2,32}$"
+ ),
+ "modelName": _SERIALIZER.url("model_name", model_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
+ "version": _SERIALIZER.url("version", version, "str"),
+ }
+
+ _url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class RegistryModelVersionsOperations:
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.mgmt.machinelearningservices.MachineLearningServicesMgmtClient`'s
+ :attr:`registry_model_versions` attribute.
+ """
+
+ models = _models
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ skip: Optional[str] = None,
+ order_by: Optional[str] = None,
+ top: Optional[int] = None,
+ version: Optional[str] = None,
+ description: Optional[str] = None,
+ tags: Optional[str] = None,
+ properties: Optional[str] = None,
+ list_view_type: Optional[Union[str, _models.ListViewType]] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.ModelVersion"]:
+ """List versions.
+
+ List versions.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. This is case-sensitive. Required.
+ :type model_name: str
+ :param skip: Continuation token for pagination. Default value is None.
+ :type skip: str
+ :param order_by: Ordering of list. Default value is None.
+ :type order_by: str
+ :param top: Maximum number of records to return. Default value is None.
+ :type top: int
+ :param version: Version identifier. Default value is None.
+ :type version: str
+ :param description: Model description. Default value is None.
+ :type description: str
+ :param tags: Comma-separated list of tag names (and optionally values). Example:
+ tag1,tag2=value2. Default value is None.
+ :type tags: str
+ :param properties: Comma-separated list of property names (and optionally values). Example:
+ prop1,prop2=value2. Default value is None.
+ :type properties: str
+ :param list_view_type: View type for including/excluding (for example) archived entities. Known
+ values are: "ActiveOnly", "ArchivedOnly", and "All". Default value is None.
+ :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: An iterator like instance of either ModelVersion or the result of cls(response)
+ :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ModelVersionResourceArmPaginatedResult] = kwargs.pop("cls", None)
+
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ def prepare_request(next_link=None):
+ if not next_link:
+
+ request = build_list_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ subscription_id=self._config.subscription_id,
+ skip=skip,
+ order_by=order_by,
+ top=top,
+ version=version,
+ description=description,
+ tags=tags,
+ properties=properties,
+ list_view_type=list_view_type,
+ api_version=api_version,
+ template_url=self.list.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ else:
+ # make call to next link with the client's api-version
+ _parsed_next_link = urllib.parse.urlparse(next_link)
+ _next_request_params = case_insensitive_dict(
+ {
+ key: [urllib.parse.quote(v) for v in value]
+ for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+ }
+ )
+ _next_request_params["api-version"] = self._config.api_version
+ request = HttpRequest(
+ "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+ request.method = "GET"
+ return request
+
+ def extract_data(pipeline_response):
+ deserialized = self._deserialize("ModelVersionResourceArmPaginatedResult", pipeline_response)
+ list_of_elem = deserialized.value
+ if cls:
+ list_of_elem = cls(list_of_elem) # type: ignore
+ return deserialized.next_link or None, iter(list_of_elem)
+
+ def get_next(next_link=None):
+ request = prepare_request(next_link)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ list.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions"
+ }
+
+ def _delete_initial( # pylint: disable=inconsistent-return-statements
+ self, resource_group_name: str, registry_name: str, model_name: str, version: str, **kwargs: Any
+ ) -> None:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+
+ request = build_delete_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self._delete_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 202, 204]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 202:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Location"] = self._deserialize("str", response.headers.get("Location"))
+ response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
+
+ if cls:
+ return cls(pipeline_response, None, response_headers)
+
+ _delete_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ @distributed_trace
+ def begin_delete(
+ self, resource_group_name: str, registry_name: str, model_name: str, version: str, **kwargs: Any
+ ) -> LROPoller[None]:
+ """Delete version.
+
+ Delete version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either None or the result of cls(response)
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[None] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._delete_initial( # type: ignore
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ api_version=api_version,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {})
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_delete.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ @distributed_trace
+ def get(
+ self, resource_group_name: str, registry_name: str, model_name: str, version: str, **kwargs: Any
+ ) -> _models.ModelVersion:
+ """Get version.
+
+ Get version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. This is case-sensitive. Required.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: ModelVersion or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.ModelVersion
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
+
+ request = build_get_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ template_url=self.get.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("ModelVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ get.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ def _create_or_update_initial(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: Union[_models.ModelVersion, IO],
+ **kwargs: Any
+ ) -> _models.ModelVersion:
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "ModelVersion")
+
+ request = build_create_or_update_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self._create_or_update_initial.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ response_headers = {}
+ if response.status_code == 200:
+ deserialized = self._deserialize("ModelVersion", pipeline_response)
+
+ if response.status_code == 201:
+ response_headers["x-ms-async-operation-timeout"] = self._deserialize(
+ "duration", response.headers.get("x-ms-async-operation-timeout")
+ )
+ response_headers["Azure-AsyncOperation"] = self._deserialize(
+ "str", response.headers.get("Azure-AsyncOperation")
+ )
+
+ deserialized = self._deserialize("ModelVersion", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ _create_or_update_initial.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: _models.ModelVersion,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ModelVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ModelVersion
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ModelVersion or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ModelVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ModelVersion or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_create_or_update(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: Union[_models.ModelVersion, IO],
+ **kwargs: Any
+ ) -> LROPoller[_models.ModelVersion]:
+ """Create or update version.
+
+ Create or update version.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Container name. Required.
+ :type model_name: str
+ :param version: Version identifier. Required.
+ :type version: str
+ :param body: Version entity to create or update. Is either a ModelVersion type or a IO type.
+ Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.ModelVersion or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :keyword str continuation_token: A continuation token to restart a poller from a saved state.
+ :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
+ operation to not poll, or pass in your own initialized polling object for a personal polling
+ strategy.
+ :paramtype polling: bool or ~azure.core.polling.PollingMethod
+ :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
+ Retry-After header is present.
+ :return: An instance of LROPoller that returns either ModelVersion or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.ModelVersion] = kwargs.pop("cls", None)
+ polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
+ lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
+ cont_token: Optional[str] = kwargs.pop("continuation_token", None)
+ if cont_token is None:
+ raw_result = self._create_or_update_initial(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ body=body,
+ api_version=api_version,
+ content_type=content_type,
+ cls=lambda x, y, z: x,
+ headers=_headers,
+ params=_params,
+ **kwargs
+ )
+ kwargs.pop("error_map", None)
+
+ def get_long_running_output(pipeline_response):
+ deserialized = self._deserialize("ModelVersion", pipeline_response)
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+ return deserialized
+
+ if polling is True:
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
+ elif polling is False:
+ polling_method = cast(PollingMethod, NoPolling())
+ else:
+ polling_method = polling
+ if cont_token:
+ return LROPoller.from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller(self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ begin_create_or_update.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"
+ }
+
+ @overload
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: _models.PendingUploadRequestDto,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a model asset to.
+
+ Generate a storage location and credential for the client to upload a model asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Model name. This is case-sensitive. Required.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: IO,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a model asset to.
+
+ Generate a storage location and credential for the client to upload a model asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Model name. This is case-sensitive. Required.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Required.
+ :type body: IO
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def create_or_get_start_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: Union[_models.PendingUploadRequestDto, IO],
+ **kwargs: Any
+ ) -> _models.PendingUploadResponseDto:
+ """Generate a storage location and credential for the client to upload a model asset to.
+
+ Generate a storage location and credential for the client to upload a model asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ Required.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry. This is case-insensitive.
+ Required.
+ :type registry_name: str
+ :param model_name: Model name. This is case-sensitive. Required.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive. Required.
+ :type version: str
+ :param body: Pending upload request object. Is either a PendingUploadRequestDto type or a IO
+ type. Required.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto or IO
+ :keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
+ Default value is None.
+ :paramtype content_type: str
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ error_map = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
+ content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
+ cls: ClsType[_models.PendingUploadResponseDto] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _json = None
+ _content = None
+ if isinstance(body, (IO, bytes)):
+ _content = body
+ else:
+ _json = self._serialize.body(body, "PendingUploadRequestDto")
+
+ request = build_create_or_get_start_pending_upload_request(
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ subscription_id=self._config.subscription_id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ content=_content,
+ template_url=self.create_or_get_start_pending_upload.metadata["url"],
+ headers=_headers,
+ params=_params,
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ _stream = False
+ pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
+ request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize("PendingUploadResponseDto", pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_start_pending_upload.metadata = {
+ "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}/startPendingUpload"
+ }
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_schedules_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_schedules_operations.py
index ccf22fb3aed1..42f8f32d4fc7 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_schedules_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_schedules_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -32,10 +31,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -55,7 +50,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -68,7 +63,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -92,7 +89,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -105,7 +102,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -126,7 +125,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -139,7 +138,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str"),
}
@@ -160,7 +161,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -174,7 +175,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"name": _SERIALIZER.url("name", name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$"),
}
@@ -241,9 +244,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ScheduleResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -299,8 +300,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -331,9 +333,7 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -349,8 +349,9 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -403,9 +404,7 @@ def begin_delete(self, resource_group_name: str, workspace_name: str, name: str,
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -428,7 +427,9 @@ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-
return cls(pipeline_response, None, {})
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "location"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
@@ -475,9 +476,7 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.Schedule] = kwargs.pop("cls", None)
request = build_get_request(
@@ -493,8 +492,9 @@ def get(self, resource_group_name: str, workspace_name: str, name: str, **kwargs
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -529,9 +529,7 @@ def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Schedule] = kwargs.pop("cls", None)
@@ -559,8 +557,9 @@ def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -688,7 +687,7 @@ def begin_create_or_update(
:type workspace_name: str
:param name: Schedule name. Required.
:type name: str
- :param body: Schedule definition. Is either a model type or a IO type. Required.
+ :param body: Schedule definition. Is either a Schedule type or a IO type. Required.
:type body: ~azure.mgmt.machinelearningservices.models.Schedule or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -708,9 +707,7 @@ def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Schedule] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -738,7 +735,9 @@ def get_long_running_output(pipeline_response):
return deserialized
if polling is True:
- polling_method: PollingMethod = cast(PollingMethod, ARMPolling(lro_delay, **kwargs))
+ polling_method: PollingMethod = cast(
+ PollingMethod, ARMPolling(lro_delay, lro_options={"final-state-via": "original-uri"}, **kwargs)
+ )
elif polling is False:
polling_method = cast(PollingMethod, NoPolling())
else:
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_usages_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_usages_operations.py
index 87b60742ab08..3dc29c049f1d 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_usages_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_usages_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, Iterable, Optional, TypeVar
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -45,7 +40,7 @@ def build_list_request(location: str, subscription_id: str, **kwargs: Any) -> Ht
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -103,9 +98,7 @@ def list(self, location: str, **kwargs: Any) -> Iterable["_models.Usage"]:
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListUsagesResult] = kwargs.pop("cls", None)
error_map = {
@@ -158,8 +151,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_virtual_machine_sizes_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_virtual_machine_sizes_operations.py
index 4928f81dcedf..27bb7d3b448a 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_virtual_machine_sizes_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_virtual_machine_sizes_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, Optional, TypeVar
from azure.core.exceptions import (
@@ -28,10 +27,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -43,7 +38,7 @@ def build_list_request(location: str, subscription_id: str, **kwargs: Any) -> Ht
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -108,9 +103,7 @@ def list(self, location: str, **kwargs: Any) -> _models.VirtualMachineSizeListRe
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.VirtualMachineSizeListResult] = kwargs.pop("cls", None)
request = build_list_request(
@@ -124,8 +117,9 @@ def list(self, location: str, **kwargs: Any) -> _models.VirtualMachineSizeListRe
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspace_connections_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspace_connections_operations.py
index c85caf24b6e8..393540fb8e49 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspace_connections_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspace_connections_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, overload
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -47,7 +42,7 @@ def build_create_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -61,7 +56,9 @@ def build_create_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"connectionName": _SERIALIZER.url("connection_name", connection_name, "str"),
}
@@ -84,7 +81,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -97,7 +94,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"connectionName": _SERIALIZER.url("connection_name", connection_name, "str"),
}
@@ -118,7 +117,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -131,7 +130,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
"connectionName": _SERIALIZER.url("connection_name", connection_name, "str"),
}
@@ -158,7 +159,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -171,7 +172,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -290,7 +293,7 @@ def create(
:param connection_name: Friendly name of the workspace connection. Required.
:type connection_name: str
:param parameters: The object for creating or updating a new workspace connection. Is either a
- model type or a IO type. Required.
+ WorkspaceConnectionPropertiesV2BasicResource type or a IO type. Required.
:type parameters:
~azure.mgmt.machinelearningservices.models.WorkspaceConnectionPropertiesV2BasicResource or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
@@ -312,9 +315,7 @@ def create(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.WorkspaceConnectionPropertiesV2BasicResource] = kwargs.pop("cls", None)
@@ -342,8 +343,9 @@ def create(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -393,9 +395,7 @@ def get(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.WorkspaceConnectionPropertiesV2BasicResource] = kwargs.pop("cls", None)
request = build_get_request(
@@ -411,8 +411,9 @@ def get(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -462,9 +463,7 @@ def delete( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -480,8 +479,9 @@ def delete( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -528,9 +528,7 @@ def list(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.WorkspaceConnectionPropertiesV2BasicResourceArmPaginatedResult] = kwargs.pop("cls", None)
error_map = {
@@ -588,8 +586,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspace_features_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspace_features_operations.py
index 00c72c0a8b82..a8b05127e633 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspace_features_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspace_features_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, Iterable, Optional, TypeVar
import urllib.parse
@@ -30,10 +29,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -47,7 +42,7 @@ def build_list_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -60,7 +55,9 @@ def build_list_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -110,9 +107,7 @@ def list(self, resource_group_name: str, workspace_name: str, **kwargs: Any) ->
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListAmlUserFeatureResult] = kwargs.pop("cls", None)
error_map = {
@@ -166,8 +161,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspaces_operations.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspaces_operations.py
index 3d8220b5fefa..d85546a56fa8 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspaces_operations.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/operations/_workspaces_operations.py
@@ -6,7 +6,6 @@
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
-import sys
from typing import Any, Callable, Dict, IO, Iterable, Optional, TypeVar, Union, cast, overload
import urllib.parse
@@ -32,10 +31,6 @@
from .._serialization import Serializer
from .._vendor import _convert_request, _format_url_section
-if sys.version_info >= (3, 8):
- from typing import Literal # pylint: disable=no-name-in-module, ungrouped-imports
-else:
- from typing_extensions import Literal # type: ignore # pylint: disable=ungrouped-imports
T = TypeVar("T")
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
@@ -49,7 +44,7 @@ def build_get_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -62,7 +57,9 @@ def build_get_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -82,7 +79,7 @@ def build_create_or_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -96,7 +93,9 @@ def build_create_or_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -118,7 +117,7 @@ def build_delete_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -131,7 +130,9 @@ def build_delete_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -151,7 +152,7 @@ def build_update_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -165,7 +166,9 @@ def build_update_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -187,7 +190,7 @@ def build_list_by_resource_group_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -221,7 +224,7 @@ def build_diagnose_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
accept = _headers.pop("Accept", "application/json")
@@ -235,7 +238,9 @@ def build_diagnose_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -257,7 +262,7 @@ def build_list_keys_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -270,7 +275,9 @@ def build_list_keys_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -290,7 +297,7 @@ def build_resync_keys_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -303,7 +310,9 @@ def build_resync_keys_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -323,7 +332,7 @@ def build_list_by_subscription_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -353,7 +362,7 @@ def build_list_notebook_access_token_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -366,7 +375,9 @@ def build_list_notebook_access_token_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -386,7 +397,7 @@ def build_prepare_notebook_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -399,7 +410,9 @@ def build_prepare_notebook_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -419,7 +432,7 @@ def build_list_storage_account_keys_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -432,7 +445,9 @@ def build_list_storage_account_keys_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -452,7 +467,7 @@ def build_list_notebook_keys_request(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -465,7 +480,9 @@ def build_list_notebook_keys_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -479,13 +496,13 @@ def build_list_notebook_keys_request(
return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
-def build_list_outbound_network_dependencies_endpoints_request(
+def build_list_outbound_network_dependencies_endpoints_request( # pylint: disable=name-too-long
resource_group_name: str, workspace_name: str, subscription_id: str, **kwargs: Any
) -> HttpRequest:
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop("api_version", _params.pop("api-version", "2022-10-01"))
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2023-04-01"))
accept = _headers.pop("Accept", "application/json")
# Construct URL
@@ -498,7 +515,9 @@ def build_list_outbound_network_dependencies_endpoints_request(
"resourceGroupName": _SERIALIZER.url(
"resource_group_name", resource_group_name, "str", max_length=90, min_length=1
),
- "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, "str"),
+ "workspaceName": _SERIALIZER.url(
+ "workspace_name", workspace_name, "str", pattern=r"^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
+ ),
}
_url: str = _format_url_section(_url, **path_format_arguments) # type: ignore
@@ -556,9 +575,7 @@ def get(self, resource_group_name: str, workspace_name: str, **kwargs: Any) -> _
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.Workspace] = kwargs.pop("cls", None)
request = build_get_request(
@@ -573,8 +590,9 @@ def get(self, resource_group_name: str, workspace_name: str, **kwargs: Any) -> _
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -609,9 +627,7 @@ def _create_or_update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.Workspace]] = kwargs.pop("cls", None)
@@ -638,8 +654,9 @@ def _create_or_update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -746,7 +763,7 @@ def begin_create_or_update(
:param workspace_name: Name of Azure Machine Learning workspace. Required.
:type workspace_name: str
:param parameters: The parameters for creating or updating a machine learning workspace. Is
- either a model type or a IO type. Required.
+ either a Workspace type or a IO type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.Workspace or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -766,9 +783,7 @@ def begin_create_or_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Workspace] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -827,9 +842,7 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_delete_request(
@@ -844,8 +857,9 @@ def _delete_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -886,9 +900,7 @@ def begin_delete(self, resource_group_name: str, workspace_name: str, **kwargs:
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -946,9 +958,7 @@ def _update_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.Workspace]] = kwargs.pop("cls", None)
@@ -975,8 +985,9 @@ def _update_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1084,8 +1095,8 @@ def begin_update(
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace. Required.
:type workspace_name: str
- :param parameters: The parameters for updating a machine learning workspace. Is either a model
- type or a IO type. Required.
+ :param parameters: The parameters for updating a machine learning workspace. Is either a
+ WorkspaceUpdateParameters type or a IO type. Required.
:type parameters: ~azure.mgmt.machinelearningservices.models.WorkspaceUpdateParameters or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1105,9 +1116,7 @@ def begin_update(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.Workspace] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -1171,9 +1180,7 @@ def list_by_resource_group(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.WorkspaceListResult] = kwargs.pop("cls", None)
error_map = {
@@ -1227,8 +1234,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1263,9 +1271,7 @@ def _diagnose_initial(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[Optional[_models.DiagnoseResponseResult]] = kwargs.pop("cls", None)
@@ -1295,8 +1301,9 @@ def _diagnose_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1419,8 +1426,8 @@ def begin_diagnose(
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace. Required.
:type workspace_name: str
- :param parameters: The parameter of diagnosing workspace health. Is either a model type or a IO
- type. Default value is None.
+ :param parameters: The parameter of diagnosing workspace health. Is either a
+ DiagnoseWorkspaceParameters type or a IO type. Default value is None.
:type parameters: ~azure.mgmt.machinelearningservices.models.DiagnoseWorkspaceParameters or IO
:keyword content_type: Body Parameter content-type. Known values are: 'application/json'.
Default value is None.
@@ -1442,9 +1449,7 @@ def begin_diagnose(
_headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
cls: ClsType[_models.DiagnoseResponseResult] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
@@ -1519,9 +1524,7 @@ def list_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListWorkspaceKeysResult] = kwargs.pop("cls", None)
request = build_list_keys_request(
@@ -1536,8 +1539,9 @@ def list_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1572,9 +1576,7 @@ def _resync_keys_initial( # pylint: disable=inconsistent-return-statements
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
request = build_resync_keys_request(
@@ -1589,8 +1591,9 @@ def _resync_keys_initial( # pylint: disable=inconsistent-return-statements
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1632,9 +1635,7 @@ def begin_resync_keys(self, resource_group_name: str, workspace_name: str, **kwa
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[None] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1688,9 +1689,7 @@ def list_by_subscription(self, skip: Optional[str] = None, **kwargs: Any) -> Ite
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.WorkspaceListResult] = kwargs.pop("cls", None)
error_map = {
@@ -1743,8 +1742,9 @@ def extract_data(pipeline_response):
def get_next(next_link=None):
request = prepare_request(next_link)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1788,9 +1788,7 @@ def list_notebook_access_token(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.NotebookAccessTokenResult] = kwargs.pop("cls", None)
request = build_list_notebook_access_token_request(
@@ -1805,8 +1803,9 @@ def list_notebook_access_token(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1841,9 +1840,7 @@ def _prepare_notebook_initial(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[Optional[_models.NotebookResourceInfo]] = kwargs.pop("cls", None)
request = build_prepare_notebook_request(
@@ -1858,8 +1855,9 @@ def _prepare_notebook_initial(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -1910,9 +1908,7 @@ def begin_prepare_notebook(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.NotebookResourceInfo] = kwargs.pop("cls", None)
polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
@@ -1983,9 +1979,7 @@ def list_storage_account_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListStorageAccountKeysResult] = kwargs.pop("cls", None)
request = build_list_storage_account_keys_request(
@@ -2000,8 +1994,9 @@ def list_storage_account_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -2049,9 +2044,7 @@ def list_notebook_keys(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ListNotebookKeysResult] = kwargs.pop("cls", None)
request = build_list_notebook_keys_request(
@@ -2066,8 +2059,9 @@ def list_notebook_keys(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
@@ -2089,7 +2083,7 @@ def list_notebook_keys(
}
@distributed_trace
- def list_outbound_network_dependencies_endpoints(
+ def list_outbound_network_dependencies_endpoints( # pylint: disable=name-too-long
self, resource_group_name: str, workspace_name: str, **kwargs: Any
) -> _models.ExternalFQDNResponse:
"""Called by Client (Portal, CLI, etc) to get a list of all external outbound dependencies (FQDNs)
@@ -2119,9 +2113,7 @@ def list_outbound_network_dependencies_endpoints(
_headers = kwargs.pop("headers", {}) or {}
_params = case_insensitive_dict(kwargs.pop("params", {}) or {})
- api_version: Literal["2022-10-01"] = kwargs.pop(
- "api_version", _params.pop("api-version", self._config.api_version)
- )
+ api_version: str = kwargs.pop("api_version", _params.pop("api-version", self._config.api_version))
cls: ClsType[_models.ExternalFQDNResponse] = kwargs.pop("cls", None)
request = build_list_outbound_network_dependencies_endpoints_request(
@@ -2136,8 +2128,9 @@ def list_outbound_network_dependencies_endpoints(
request = _convert_request(request)
request.url = self._client.format_url(request.url)
+ _stream = False
pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access
- request, stream=False, **kwargs
+ request, stream=_stream, **kwargs
)
response = pipeline_response.http_response
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/aks_compute.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/aks_compute.py
index 4154ad04114e..4692f63ff9d7 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/aks_compute.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/aks_compute.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/get/AKSCompute.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/get/AKSCompute.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/aml_compute.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/aml_compute.py
index 9b60010544b5..59ea7d05e296 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/aml_compute.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/aml_compute.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/get/AmlCompute.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/get/AmlCompute.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_aks_compute.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_aks_compute.py
index 7bf0144d06dc..c4f5100e5166 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_aks_compute.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_aks_compute.py
@@ -38,6 +38,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/createOrUpdate/BasicAKSCompute.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/createOrUpdate/BasicAKSCompute.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_aml_compute.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_aml_compute.py
index d6cfcd909034..4e8789e3ef24 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_aml_compute.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_aml_compute.py
@@ -55,6 +55,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/createOrUpdate/BasicAmlCompute.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/createOrUpdate/BasicAmlCompute.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_data_factory_compute.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_data_factory_compute.py
index c7256aaa7266..322dec99f0ea 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_data_factory_compute.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/basic_data_factory_compute.py
@@ -38,6 +38,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/createOrUpdate/BasicDataFactoryCompute.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/createOrUpdate/BasicDataFactoryCompute.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/cancel.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/cancel.py
index 14832bc92a6c..be40485be034 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/cancel.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/cancel.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Job/cancel.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Job/cancel.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance.py
index 8be35ceb91e4..fe66677f7193 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/get/ComputeInstance.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/get/ComputeInstance.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance_minimal.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance_minimal.py
index f67029c8ca3c..575439d32563 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance_minimal.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance_minimal.py
@@ -41,6 +41,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/createOrUpdate/ComputeInstanceMinimal.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/createOrUpdate/ComputeInstanceMinimal.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance_with_schedules.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance_with_schedules.py
index c5ef7c03d6b9..4134df53117f 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance_with_schedules.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/compute_instance_with_schedules.py
@@ -69,6 +69,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/createOrUpdate/ComputeInstanceWithSchedules.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/createOrUpdate/ComputeInstanceWithSchedules.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create.py
index 0d7e657dba30..cd04a676e0e1 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create.py
@@ -76,6 +76,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/create.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/create.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_get_start_pending_upload.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_get_start_pending_upload.py
new file mode 100644
index 000000000000..e3e974c61eb9
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_get_start_pending_upload.py
@@ -0,0 +1,44 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python create_or_get_start_pending_upload.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registry_code_versions.create_or_get_start_pending_upload(
+ resource_group_name="test-rg",
+ registry_name="registryName",
+ code_name="string",
+ version="string",
+ body={"pendingUploadId": "string", "pendingUploadType": "TemporaryBlobReference"},
+ )
+ print(response)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registry/CodeVersion/createOrGetStartPendingUpload.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update.py
index d69a53bd684c..4f95d6a5bdef 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update.py
@@ -40,6 +40,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/PrivateEndpointConnection/createOrUpdate.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/PrivateEndpointConnection/createOrUpdate.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update_system_created.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update_system_created.py
new file mode 100644
index 000000000000..577787fee2b8
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update_system_created.py
@@ -0,0 +1,96 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python create_or_update_system_created.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.begin_create_or_update(
+ resource_group_name="test-rg",
+ registry_name="string",
+ body={
+ "identity": {"type": "None", "userAssignedIdentities": {"string": {}}},
+ "kind": "string",
+ "location": "string",
+ "properties": {
+ "discoveryUrl": "string",
+ "intellectualPropertyPublisher": "string",
+ "managedResourceGroup": {"resourceId": "string"},
+ "mlFlowRegistryUri": "string",
+ "publicNetworkAccess": "string",
+ "regionDetails": [
+ {
+ "acrDetails": [
+ {
+ "systemCreatedAcrAccount": {
+ "acrAccountName": "string",
+ "acrAccountSku": "string",
+ "armResourceId": {"resourceId": "string"},
+ }
+ }
+ ],
+ "location": "string",
+ "storageAccountDetails": [
+ {
+ "systemCreatedStorageAccount": {
+ "allowBlobPublicAccess": False,
+ "armResourceId": {"resourceId": "string"},
+ "storageAccountHnsEnabled": False,
+ "storageAccountName": "string",
+ "storageAccountType": "string",
+ }
+ }
+ ],
+ }
+ ],
+ "registryPrivateEndpointConnections": [
+ {
+ "id": "string",
+ "location": "string",
+ "properties": {
+ "groupIds": ["string"],
+ "privateEndpoint": {"subnetArmId": "string"},
+ "provisioningState": "string",
+ "registryPrivateLinkServiceConnectionState": {
+ "actionsRequired": "string",
+ "description": "string",
+ "status": "Approved",
+ },
+ },
+ }
+ ],
+ },
+ "sku": {"capacity": 1, "family": "string", "name": "string", "size": "string", "tier": "Free"},
+ "tags": {},
+ },
+ ).result()
+ print(response)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/createOrUpdate-SystemCreated.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update_user_created.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update_user_created.py
new file mode 100644
index 000000000000..4fb0f626522f
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/create_or_update_user_created.py
@@ -0,0 +1,80 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python create_or_update_user_created.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.begin_create_or_update(
+ resource_group_name="test-rg",
+ registry_name="string",
+ body={
+ "identity": {"type": "None", "userAssignedIdentities": {"string": {}}},
+ "kind": "string",
+ "location": "string",
+ "properties": {
+ "discoveryUrl": "string",
+ "intellectualPropertyPublisher": "string",
+ "managedResourceGroup": {"resourceId": "string"},
+ "mlFlowRegistryUri": "string",
+ "publicNetworkAccess": "string",
+ "regionDetails": [
+ {
+ "acrDetails": [{"userCreatedAcrAccount": {"armResourceId": {"resourceId": "string"}}}],
+ "location": "string",
+ "storageAccountDetails": [
+ {"userCreatedStorageAccount": {"armResourceId": {"resourceId": "string"}}}
+ ],
+ }
+ ],
+ "registryPrivateEndpointConnections": [
+ {
+ "id": "string",
+ "location": "string",
+ "properties": {
+ "groupIds": ["string"],
+ "privateEndpoint": {"subnetArmId": "string"},
+ "provisioningState": "string",
+ "registryPrivateLinkServiceConnectionState": {
+ "actionsRequired": "string",
+ "description": "string",
+ "status": "Approved",
+ },
+ },
+ }
+ ],
+ },
+ "sku": {"capacity": 1, "family": "string", "name": "string", "size": "string", "tier": "Free"},
+ "tags": {},
+ },
+ ).result()
+ print(response)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/createOrUpdate-UserCreated.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/delete.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/delete.py
index 1ab7cceee3e0..6332bd1c2462 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/delete.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/delete.py
@@ -36,6 +36,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/delete.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/delete.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/diagnose.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/diagnose.py
index e7d53be6b011..3077375cd454 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/diagnose.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/diagnose.py
@@ -36,6 +36,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/diagnose.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/diagnose.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get.py
index ae2325915702..4c2f399080e3 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get.py
@@ -36,6 +36,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/get.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/get.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_logs.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_logs.py
index 08ca1c985e42..2bae655720a4 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_logs.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_logs.py
@@ -39,6 +39,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/OnlineDeployment/getLogs.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/OnlineDeployment/getLogs.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_system_created.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_system_created.py
new file mode 100644
index 000000000000..fd5b114248b7
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_system_created.py
@@ -0,0 +1,41 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python get_system_created.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.get(
+ resource_group_name="test-rg",
+ registry_name="string",
+ )
+ print(response)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/get-SystemCreated.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_token.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_token.py
index ce3165223bbc..f721177eb41c 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_token.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_token.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/OnlineEndpoint/getToken.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/OnlineEndpoint/getToken.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_user_created.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_user_created.py
new file mode 100644
index 000000000000..bd86983df7e3
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/get_user_created.py
@@ -0,0 +1,41 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python get_user_created.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.get(
+ resource_group_name="test-rg",
+ registry_name="string",
+ )
+ print(response)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/get-UserCreated.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/kubernetes_compute.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/kubernetes_compute.py
index 1c4abcb9c998..b09cac4f3f62 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/kubernetes_compute.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/kubernetes_compute.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/get/KubernetesCompute.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/get/KubernetesCompute.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list.py
index 803939df104d..ccff07e2fa36 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list.py
@@ -36,6 +36,6 @@ def main():
print(item)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Usage/list.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Usage/list.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_by_resource_group.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_by_resource_group.py
index ab77ccf41bcb..48ad1779487f 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_by_resource_group.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_by_resource_group.py
@@ -36,6 +36,6 @@ def main():
print(item)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/listByResourceGroup.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/listByResourceGroup.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_by_subscription.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_by_subscription.py
index 021a94dc65b3..921bfb2b59f6 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_by_subscription.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_by_subscription.py
@@ -34,6 +34,6 @@ def main():
print(item)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/listBySubscription.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/listBySubscription.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_keys.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_keys.py
index 4329788bf08c..9e0e183e60ef 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_keys.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_keys.py
@@ -36,6 +36,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/listKeys.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/listKeys.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_nodes.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_nodes.py
index 08a92686eed7..66ee6a0f4bee 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_nodes.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_nodes.py
@@ -38,6 +38,6 @@ def main():
print(item)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/listNodes.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/listNodes.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_notebook_access_token.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_notebook_access_token.py
index 2231f08361b1..d180f3ee30c2 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_notebook_access_token.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_notebook_access_token.py
@@ -36,6 +36,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/listNotebookAccessToken.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/listNotebookAccessToken.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_secrets.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_secrets.py
index 6c9f9145642c..74fe51d50b35 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_secrets.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_secrets.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Datastore/listSecrets.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Datastore/listSecrets.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_skus.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_skus.py
index a1cd89f08c22..532af7db70b6 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_skus.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_skus.py
@@ -39,6 +39,6 @@ def main():
print(item)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/OnlineDeployment/KubernetesOnlineDeployment/listSkus.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/OnlineDeployment/KubernetesOnlineDeployment/listSkus.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_storage_account_keys.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_storage_account_keys.py
index 84b7f19567c0..dbc963513d84 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_storage_account_keys.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_storage_account_keys.py
@@ -36,6 +36,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/listStorageAccountKeys.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/listStorageAccountKeys.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_system_created.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_system_created.py
new file mode 100644
index 000000000000..d9ef5482f599
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_system_created.py
@@ -0,0 +1,41 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python list_system_created.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.list(
+ resource_group_name="test-rg",
+ )
+ for item in response:
+ print(item)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/list-SystemCreated.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_user_created.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_user_created.py
new file mode 100644
index 000000000000..193089df5170
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/list_user_created.py
@@ -0,0 +1,41 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python list_user_created.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.list(
+ resource_group_name="test-rg",
+ )
+ for item in response:
+ print(item)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/list-UserCreated.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/operations_list.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/operations_list.py
index 1ed3dd9d1da4..91510c53d5b5 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/operations_list.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/operations_list.py
@@ -34,6 +34,6 @@ def main():
print(item)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/operationsList.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/operationsList.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/patch.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/patch.py
index 88d3d61b0099..344934f7929b 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/patch.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/patch.py
@@ -44,6 +44,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/patch.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/patch.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/prepare.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/prepare.py
index c6038615acb6..009f750c227c 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/prepare.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/prepare.py
@@ -36,6 +36,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Notebook/prepare.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Notebook/prepare.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/regenerate_keys.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/regenerate_keys.py
index 7e4eb60a2634..d7898c413ab2 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/regenerate_keys.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/regenerate_keys.py
@@ -38,6 +38,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/OnlineEndpoint/regenerateKeys.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/OnlineEndpoint/regenerateKeys.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/registry_list.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/registry_list.py
new file mode 100644
index 000000000000..1b5917eb34e7
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/registry_list.py
@@ -0,0 +1,42 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python registry_list.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registry_data_containers.list(
+ resource_group_name="test-rg",
+ registry_name="registryName",
+ )
+ for item in response:
+ print(item)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registry/DataContainer/registryList.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/remove_regions.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/remove_regions.py
new file mode 100644
index 000000000000..75dd8c55aac0
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/remove_regions.py
@@ -0,0 +1,98 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python remove_regions.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.begin_remove_regions(
+ resource_group_name="test-rg",
+ registry_name="string",
+ body={
+ "identity": {"type": "None", "userAssignedIdentities": {"string": {}}},
+ "kind": "string",
+ "location": "string",
+ "properties": {
+ "discoveryUrl": "string",
+ "intellectualPropertyPublisher": "string",
+ "managedResourceGroup": {"resourceId": "string"},
+ "mlFlowRegistryUri": "string",
+ "publicNetworkAccess": "string",
+ "regionDetails": [
+ {
+ "acrDetails": [
+ {
+ "systemCreatedAcrAccount": {
+ "acrAccountName": "string",
+ "acrAccountSku": "string",
+ "armResourceId": {"resourceId": "string"},
+ },
+ "userCreatedAcrAccount": {"armResourceId": {"resourceId": "string"}},
+ }
+ ],
+ "location": "string",
+ "storageAccountDetails": [
+ {
+ "systemCreatedStorageAccount": {
+ "allowBlobPublicAccess": False,
+ "armResourceId": {"resourceId": "string"},
+ "storageAccountHnsEnabled": False,
+ "storageAccountName": "string",
+ "storageAccountType": "string",
+ },
+ "userCreatedStorageAccount": {"armResourceId": {"resourceId": "string"}},
+ }
+ ],
+ }
+ ],
+ "registryPrivateEndpointConnections": [
+ {
+ "id": "string",
+ "location": "string",
+ "properties": {
+ "groupIds": ["string"],
+ "privateEndpoint": {"subnetArmId": "string"},
+ "provisioningState": "string",
+ "registryPrivateLinkServiceConnectionState": {
+ "actionsRequired": "string",
+ "description": "string",
+ "status": "Approved",
+ },
+ },
+ }
+ ],
+ },
+ "sku": {"capacity": 1, "family": "string", "name": "string", "size": "string", "tier": "Free"},
+ "tags": {},
+ },
+ ).result()
+ print(response)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/removeRegions.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/restart.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/restart.py
index df42109f655d..3a911b9a6697 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/restart.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/restart.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/restart.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/restart.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/resync_keys.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/resync_keys.py
index 02b711c19636..2e671e8eab13 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/resync_keys.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/resync_keys.py
@@ -36,6 +36,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/resyncKeys.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/resyncKeys.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/start.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/start.py
index b2754e281b74..ba8fe5e94d0c 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/start.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/start.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/start.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/start.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/stop.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/stop.py
index 4337f64aa158..0015e7d4156d 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/stop.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/stop.py
@@ -37,6 +37,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Compute/stop.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Compute/stop.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update.py
index 482c71b07c8c..f8b3fae5c4cc 100644
--- a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update.py
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update.py
@@ -43,6 +43,6 @@ def main():
print(response)
-# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-10-01/examples/Workspace/update.json
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Workspace/update.json
if __name__ == "__main__":
main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update_system_created.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update_system_created.py
new file mode 100644
index 000000000000..bda97b4ad6d5
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update_system_created.py
@@ -0,0 +1,46 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python update_system_created.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.update(
+ resource_group_name="test-rg",
+ registry_name="string",
+ body={
+ "identity": {"type": "SystemAssigned", "userAssignedIdentities": {"string": {}}},
+ "sku": {"capacity": 1, "family": "string", "name": "string", "size": "string", "tier": "Basic"},
+ "tags": {},
+ },
+ )
+ print(response)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/update-SystemCreated.json
+if __name__ == "__main__":
+ main()
diff --git a/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update_user_created.py b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update_user_created.py
new file mode 100644
index 000000000000..d8ecdb855c20
--- /dev/null
+++ b/sdk/machinelearning/azure-mgmt-machinelearningservices/generated_samples/update_user_created.py
@@ -0,0 +1,46 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for license information.
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.identity import DefaultAzureCredential
+from azure.mgmt.machinelearningservices import MachineLearningServicesMgmtClient
+
+"""
+# PREREQUISITES
+ pip install azure-identity
+ pip install azure-mgmt-machinelearningservices
+# USAGE
+ python update_user_created.py
+
+ Before run the sample, please set the values of the client ID, tenant ID and client secret
+ of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID,
+ AZURE_CLIENT_SECRET. For more info about how to get the value, please see:
+ https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal
+"""
+
+
+def main():
+ client = MachineLearningServicesMgmtClient(
+ credential=DefaultAzureCredential(),
+ subscription_id="00000000-1111-2222-3333-444444444444",
+ )
+
+ response = client.registries.update(
+ resource_group_name="test-rg",
+ registry_name="string",
+ body={
+ "identity": {"type": "UserAssigned", "userAssignedIdentities": {"string": {}}},
+ "sku": {"capacity": 1, "family": "string", "name": "string", "size": "string", "tier": "Basic"},
+ "tags": {},
+ },
+ )
+ print(response)
+
+
+# x-ms-original-file: specification/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/examples/Registries/update-UserCreated.json
+if __name__ == "__main__":
+ main()