diff --git a/src/machinelearningservices/HISTORY.rst b/src/machinelearningservices/HISTORY.rst new file mode 100644 index 00000000000..1c139576ba0 --- /dev/null +++ b/src/machinelearningservices/HISTORY.rst @@ -0,0 +1,8 @@ +.. :changelog: + +Release History +=============== + +0.1.0 +++++++ +* Initial release. diff --git a/src/machinelearningservices/README.md b/src/machinelearningservices/README.md new file mode 100644 index 00000000000..76ca6b28328 --- /dev/null +++ b/src/machinelearningservices/README.md @@ -0,0 +1,416 @@ +# Azure CLI machinelearningservices Extension # +This is the extension for machinelearningservices + +### How to use ### +Install this extension using the below CLI command +``` +az extension add --name machinelearningservices +``` + +### Included Features ### +#### machinelearningservices workspace #### +##### Create ##### +``` +az machinelearningservices workspace create --type "SystemAssigned" --location "eastus2euap" \ + --description "test description" \ + --application-insights "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/microsoft.insights/components/testinsights" \ + --container-registry "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/Microsoft.ContainerRegistry/registries/testRegistry" \ + --key-vault-properties identity-client-id="" key-identifier="https://testkv.vault.azure.net/keys/testkey/aabbccddee112233445566778899aabb" key-vault-arm-id="/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/Microsoft.KeyVault/vaults/testkv" \ + --status "Enabled" --friendly-name "HelloName" --hbi-workspace false \ + --key-vault "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/Microsoft.KeyVault/vaults/testkv" \ + --shared-private-link-resources name="testdbresource" private-link-resource-id="/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/Microsoft.DocumentDB/databaseAccounts/testdbresource/privateLinkResources/Sql" group-id="Sql" request-message="Please approve" status="Approved" \ + --storage-account "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/accountcrud-1234/providers/Microsoft.Storage/storageAccounts/testStorageAccount" \ + --sku name="Basic" tier="Basic" --resource-group "workspace-1234" --name "testworkspace" + +az machinelearningservices workspace wait --created --resource-group "{rg}" --name "{myWorkspace}" +``` +##### Show ##### +``` +az machinelearningservices workspace show --resource-group "workspace-1234" --name "testworkspace" +``` +##### List ##### +``` +az machinelearningservices workspace list --resource-group "workspace-1234" +``` +##### Update ##### +``` +az machinelearningservices workspace update --description "new description" --friendly-name "New friendly name" \ + --sku name="Enterprise" tier="Enterprise" --resource-group "workspace-1234" --name "testworkspace" +``` +##### List-key ##### +``` +az machinelearningservices workspace list-key --resource-group "testrg123" --name "workspaces123" +``` +##### Resync-key ##### +``` +az machinelearningservices workspace resync-key --resource-group "testrg123" --name "workspaces123" +``` +##### Delete ##### +``` +az machinelearningservices workspace delete --resource-group "workspace-1234" --name "testworkspace" +``` +#### machinelearningservices workspace-feature #### +##### List ##### +``` +az machinelearningservices workspace-feature list --resource-group "myResourceGroup" --workspace-name "testworkspace" +``` +#### machinelearningservices notebook #### +##### Prepare ##### +``` +az machinelearningservices notebook prepare --resource-group "testrg123" --workspace-name "workspaces123" +``` +#### machinelearningservices usage #### +##### List ##### +``` +az machinelearningservices usage list --location "eastus" +``` +#### machinelearningservices virtual-machine-size #### +##### List ##### +``` +az machinelearningservices virtual-machine-size list --location "eastus" --recommended false +``` +#### machinelearningservices quota #### +##### List ##### +``` +az machinelearningservices quota list --location "eastus" +``` +##### Update ##### +``` +az machinelearningservices quota update --location "eastus" \ + --value type="Microsoft.MachineLearningServices/workspaces/dedicatedCores/quotas" id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/rg/providers/Microsoft.MachineLearningServices/workspaces/demo_workspace1/quotas/StandardDSv2Family" limit=100 unit="Count" \ + --value type="Microsoft.MachineLearningServices/workspaces/dedicatedCores/quotas" id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/rg/providers/Microsoft.MachineLearningServices/workspaces/demo_workspace2/quotas/StandardDSv2Family" limit=200 unit="Count" +``` +#### machinelearningservices workspace-connection #### +##### Create ##### +``` +az machinelearningservices workspace-connection create --connection-name "connection-1" --name "connection-1" \ + --auth-type "PAT" --category "ACR" --target "www.facebook.com" --value "secrets" \ + --resource-group "resourceGroup-1" --workspace-name "workspace-1" +``` +##### Show ##### +``` +az machinelearningservices workspace-connection show --connection-name "connection-1" \ + --resource-group "resourceGroup-1" --workspace-name "workspace-1" +``` +##### List ##### +``` +az machinelearningservices workspace-connection list --category "ACR" --resource-group "resourceGroup-1" \ + --target "www.facebook.com" --workspace-name "workspace-1" +``` +##### Delete ##### +``` +az machinelearningservices workspace-connection delete --connection-name "connection-1" \ + --resource-group "resourceGroup-1" --workspace-name "workspace-1" +``` +#### machinelearningservices machine-learning-compute #### +##### Aks create ##### +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Aks create ##### +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" \ + --type "SystemAssigned,UserAssigned" \ + --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ + --location "eastus" \ + --ak-s-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\":{\\"maxNodeCount\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedicated\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Aks create ##### +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location "eastus" \ + --ak-s-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\"sshPublicAccess\\":\\"Disabled\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Aks create ##### +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location "eastus" \ + --ak-s-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Aks create ##### +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Aml-compute create ##### +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Aml-compute create ##### +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" \ + --type "SystemAssigned,UserAssigned" \ + --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ + --location "eastus" \ + --aml-compute-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\":{\\"maxNodeCount\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedicated\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Aml-compute create ##### +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --location "eastus" \ + --aml-compute-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\"sshPublicAccess\\":\\"Disabled\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Aml-compute create ##### +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --location "eastus" \ + --aml-compute-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Aml-compute create ##### +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Compute-instance create ##### +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Compute-instance create ##### +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ + --type "SystemAssigned,UserAssigned" \ + --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ + --location "eastus" \ + --compute-instance-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\":{\\"maxNodeCount\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedicated\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Compute-instance create ##### +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ + --location "eastus" \ + --compute-instance-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\"sshPublicAccess\\":\\"Disabled\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Compute-instance create ##### +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ + --location "eastus" --compute-instance-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Compute-instance create ##### +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-factory create ##### +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-factory create ##### +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ + --type "SystemAssigned,UserAssigned" \ + --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-factory create ##### +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-factory create ##### +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-factory create ##### +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-lake-analytics create ##### +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-lake-analytics create ##### +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" \ + --type "SystemAssigned,UserAssigned" \ + --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-lake-analytics create ##### +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-lake-analytics create ##### +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Data-lake-analytics create ##### +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Databricks create ##### +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Databricks create ##### +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" \ + --type "SystemAssigned,UserAssigned" \ + --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Databricks create ##### +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Databricks create ##### +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Databricks create ##### +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Hd-insight create ##### +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Hd-insight create ##### +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" \ + --type "SystemAssigned,UserAssigned" \ + --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Hd-insight create ##### +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Hd-insight create ##### +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Hd-insight create ##### +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --location "eastus" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Virtual-machine create ##### +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Virtual-machine create ##### +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ + --type "SystemAssigned,UserAssigned" \ + --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Virtual-machine create ##### +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Virtual-machine create ##### +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Virtual-machine create ##### +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ + --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### List ##### +``` +az machinelearningservices machine-learning-compute list --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Show ##### +``` +az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Show ##### +``` +az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Show ##### +``` +az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Update ##### +``` +az machinelearningservices machine-learning-compute update --compute-name "compute123" \ + --scale-settings max-node-count=4 min-node-count=4 node-idle-time-before-scale-down="PT5M" \ + --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### List-key ##### +``` +az machinelearningservices machine-learning-compute list-key --compute-name "compute123" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### List-node ##### +``` +az machinelearningservices machine-learning-compute list-node --compute-name "compute123" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Restart ##### +``` +az machinelearningservices machine-learning-compute restart --compute-name "compute123" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Start ##### +``` +az machinelearningservices machine-learning-compute start --compute-name "compute123" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Stop ##### +``` +az machinelearningservices machine-learning-compute stop --compute-name "compute123" --resource-group "testrg123" \ + --workspace-name "workspaces123" +``` +##### Delete ##### +``` +az machinelearningservices machine-learning-compute delete --compute-name "compute123" --resource-group "testrg123" \ + --underlying-resource-action "Delete" --workspace-name "workspaces123" +``` +#### machinelearningservices #### +##### List-sku ##### +``` +az machinelearningservices list-sku +``` +#### machinelearningservices private-endpoint-connection #### +##### Put ##### +``` +az machinelearningservices private-endpoint-connection put --name "{privateEndpointConnectionName}" \ + --private-link-service-connection-state description="Auto-Approved" status="Approved" --resource-group "rg-1234" \ + --workspace-name "testworkspace" +``` +##### Show ##### +``` +az machinelearningservices private-endpoint-connection show --name "{privateEndpointConnectionName}" \ + --resource-group "rg-1234" --workspace-name "testworkspace" +``` +##### Delete ##### +``` +az machinelearningservices private-endpoint-connection delete --name "{privateEndpointConnectionName}" \ + --resource-group "rg-1234" --workspace-name "testworkspace" +``` +#### machinelearningservices private-link-resource #### +##### List ##### +``` +az machinelearningservices private-link-resource list --resource-group "rg-1234" --workspace-name "testworkspace" +``` \ No newline at end of file diff --git a/src/machinelearningservices/azext_machinelearningservices/__init__.py b/src/machinelearningservices/azext_machinelearningservices/__init__.py new file mode 100644 index 00000000000..b234b2a3aa6 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/__init__.py @@ -0,0 +1,50 @@ +# -------------------------------------------------------------------------- +# 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.cli.core import AzCommandsLoader +from azext_machinelearningservices.generated._help import helps # pylint: disable=unused-import +try: + from azext_machinelearningservices.manual._help import helps # pylint: disable=reimported +except ImportError: + pass + + +class AzureMachineLearningWorkspacesCommandsLoader(AzCommandsLoader): + + def __init__(self, cli_ctx=None): + from azure.cli.core.commands import CliCommandType + from azext_machinelearningservices.generated._client_factory import cf_machinelearningservices_cl + machinelearningservices_custom = CliCommandType( + operations_tmpl='azext_machinelearningservices.custom#{}', + client_factory=cf_machinelearningservices_cl) + parent = super(AzureMachineLearningWorkspacesCommandsLoader, self) + parent.__init__(cli_ctx=cli_ctx, custom_command_type=machinelearningservices_custom) + + def load_command_table(self, args): + from azext_machinelearningservices.generated.commands import load_command_table + load_command_table(self, args) + try: + from azext_machinelearningservices.manual.commands import load_command_table as load_command_table_manual + load_command_table_manual(self, args) + except ImportError: + pass + return self.command_table + + def load_arguments(self, command): + from azext_machinelearningservices.generated._params import load_arguments + load_arguments(self, command) + try: + from azext_machinelearningservices.manual._params import load_arguments as load_arguments_manual + load_arguments_manual(self, command) + except ImportError: + pass + + +COMMAND_LOADER_CLS = AzureMachineLearningWorkspacesCommandsLoader diff --git a/src/machinelearningservices/azext_machinelearningservices/action.py b/src/machinelearningservices/azext_machinelearningservices/action.py new file mode 100644 index 00000000000..d95d53bf711 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/action.py @@ -0,0 +1,17 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=wildcard-import +# pylint: disable=unused-wildcard-import + +from .generated.action import * # noqa: F403 +try: + from .manual.action import * # noqa: F403 +except ImportError: + pass diff --git a/src/machinelearningservices/azext_machinelearningservices/azext_metadata.json b/src/machinelearningservices/azext_machinelearningservices/azext_metadata.json new file mode 100644 index 00000000000..cfc30c747c7 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/azext_metadata.json @@ -0,0 +1,4 @@ +{ + "azext.isExperimental": true, + "azext.minCliCoreVersion": "2.15.0" +} \ No newline at end of file diff --git a/src/machinelearningservices/azext_machinelearningservices/custom.py b/src/machinelearningservices/azext_machinelearningservices/custom.py new file mode 100644 index 00000000000..dbe9d5f9742 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/custom.py @@ -0,0 +1,17 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=wildcard-import +# pylint: disable=unused-wildcard-import + +from .generated.custom import * # noqa: F403 +try: + from .manual.custom import * # noqa: F403 +except ImportError: + pass diff --git a/src/machinelearningservices/azext_machinelearningservices/generated/__init__.py b/src/machinelearningservices/azext_machinelearningservices/generated/__init__.py new file mode 100644 index 00000000000..c9cfdc73e77 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/generated/__init__.py @@ -0,0 +1,12 @@ +# 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. +# -------------------------------------------------------------------------- + +__path__ = __import__('pkgutil').extend_path(__path__, __name__) diff --git a/src/machinelearningservices/azext_machinelearningservices/generated/_client_factory.py b/src/machinelearningservices/azext_machinelearningservices/generated/_client_factory.py new file mode 100644 index 00000000000..c00137220f9 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/generated/_client_factory.py @@ -0,0 +1,56 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- + + +def cf_machinelearningservices_cl(cli_ctx, *_): + from azure.cli.core.commands.client_factory import get_mgmt_service_client + from azext_machinelearningservices.vendored_sdks.machinelearningservices import AzureMachineLearningWorkspaces + return get_mgmt_service_client(cli_ctx, + AzureMachineLearningWorkspaces) + + +def cf_workspace(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).workspaces + + +def cf_workspace_feature(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).workspace_features + + +def cf_notebook(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).notebooks + + +def cf_usage(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).usages + + +def cf_virtual_machine_size(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).virtual_machine_sizes + + +def cf_quota(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).quotas + + +def cf_workspace_connection(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).workspace_connections + + +def cf_machine_learning_compute(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).machine_learning_compute + + +def cf_private_endpoint_connection(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).private_endpoint_connections + + +def cf_private_link_resource(cli_ctx, *_): + return cf_machinelearningservices_cl(cli_ctx).private_link_resources diff --git a/src/machinelearningservices/azext_machinelearningservices/generated/_help.py b/src/machinelearningservices/azext_machinelearningservices/generated/_help.py new file mode 100644 index 00000000000..d0626c61b97 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/generated/_help.py @@ -0,0 +1,894 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=too-many-lines + +from knack.help_files import helps + + +helps['machinelearningservices workspace'] = """ + type: group + short-summary: Manage workspace with machinelearningservices +""" + +helps['machinelearningservices workspace list'] = """ + type: command + short-summary: "Lists all the available machine learning workspaces under the specified resource group. And Lists \ +all the available machine learning workspaces under the specified subscription." + examples: + - name: Get Workspaces by Resource Group + text: |- + az machinelearningservices workspace list --resource-group "workspace-1234" + - name: Get Workspaces by subscription + text: |- + az machinelearningservices workspace list +""" + +helps['machinelearningservices workspace show'] = """ + type: command + short-summary: "Gets the properties of the specified machine learning workspace." + examples: + - name: Get Workspace + text: |- + az machinelearningservices workspace show --resource-group "workspace-1234" --name "testworkspace" +""" + +helps['machinelearningservices workspace create'] = """ + type: command + short-summary: "Create a workspace with the specified parameters." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + - name: --shared-private-link-resources + short-summary: "The list of shared private link resources in this workspace." + long-summary: | + Usage: --shared-private-link-resources name=XX private-link-resource-id=XX group-id=XX request-message=XX \ +status=XX + + name: Unique name of the private link. + private-link-resource-id: The resource id that private link links to. + group-id: The private link resource group id. + request-message: Request message. + status: Indicates whether the connection has been Approved/Rejected/Removed by the owner of the service. + + Multiple actions can be specified by using more than one --shared-private-link-resources argument. + - name: --key-vault-properties + short-summary: "Customer Key vault properties." + long-summary: | + Usage: --key-vault-properties key-vault-arm-id=XX key-identifier=XX identity-client-id=XX + + key-vault-arm-id: Required. The ArmId of the keyVault where the customer owned encryption key is present. + key-identifier: Required. Key vault uri to access the encryption key. + identity-client-id: For future use - The client id of the identity which will be used to access key vault. + examples: + - name: Create Workspace + text: |- + az machinelearningservices workspace create --type "SystemAssigned" --location "eastus2euap" \ +--description "test description" --application-insights "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGr\ +oups/workspace-1234/providers/microsoft.insights/components/testinsights" --container-registry \ +"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/Microsoft.ContainerRegistr\ +y/registries/testRegistry" --key-vault-properties identity-client-id="" key-identifier="https://testkv.vault.azure.net/\ +keys/testkey/aabbccddee112233445566778899aabb" key-vault-arm-id="/subscriptions/00000000-1111-2222-3333-444444444444/re\ +sourceGroups/workspace-1234/providers/Microsoft.KeyVault/vaults/testkv" --status "Enabled" --friendly-name "HelloName" \ +--hbi-workspace false --key-vault "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/pr\ +oviders/Microsoft.KeyVault/vaults/testkv" --shared-private-link-resources name="testdbresource" \ +private-link-resource-id="/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/M\ +icrosoft.DocumentDB/databaseAccounts/testdbresource/privateLinkResources/Sql" group-id="Sql" request-message="Please \ +approve" status="Approved" --storage-account "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/accoun\ +tcrud-1234/providers/Microsoft.Storage/storageAccounts/testStorageAccount" --sku name="Basic" tier="Basic" \ +--resource-group "workspace-1234" --name "testworkspace" +""" + +helps['machinelearningservices workspace update'] = """ + type: command + short-summary: "Updates a machine learning workspace with the specified parameters." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + examples: + - name: Update Workspace + text: |- + az machinelearningservices workspace update --description "new description" --friendly-name "New \ +friendly name" --sku name="Enterprise" tier="Enterprise" --resource-group "workspace-1234" --name "testworkspace" +""" + +helps['machinelearningservices workspace delete'] = """ + type: command + short-summary: "Deletes a machine learning workspace." + examples: + - name: Delete Workspace + text: |- + az machinelearningservices workspace delete --resource-group "workspace-1234" --name "testworkspace" +""" + +helps['machinelearningservices workspace list-key'] = """ + type: command + short-summary: "Lists all the keys associated with this workspace. This includes keys for the storage account, app \ +insights and password for container registry." + examples: + - name: List Workspace Keys + text: |- + az machinelearningservices workspace list-key --resource-group "testrg123" --name "workspaces123" +""" + +helps['machinelearningservices workspace resync-key'] = """ + type: command + short-summary: "Resync all the keys associated with this workspace. This includes keys for the storage account, \ +app insights and password for container registry." + examples: + - name: Resync Workspace Keys + text: |- + az machinelearningservices workspace resync-key --resource-group "testrg123" --name "workspaces123" +""" + +helps['machinelearningservices workspace wait'] = """ + type: command + short-summary: Place the CLI in a waiting state until a condition of the machinelearningservices workspace is met. + examples: + - name: Pause executing next line of CLI script until the machinelearningservices workspace is successfully \ +created. + text: |- + az machinelearningservices workspace wait --resource-group "workspace-1234" --name "testworkspace" \ +--created + - name: Pause executing next line of CLI script until the machinelearningservices workspace is successfully \ +deleted. + text: |- + az machinelearningservices workspace wait --resource-group "workspace-1234" --name "testworkspace" \ +--deleted +""" + +helps['machinelearningservices workspace-feature'] = """ + type: group + short-summary: Manage workspace feature with machinelearningservices +""" + +helps['machinelearningservices workspace-feature list'] = """ + type: command + short-summary: "Lists all enabled features for a workspace." + examples: + - name: List Workspace features + text: |- + az machinelearningservices workspace-feature list --resource-group "myResourceGroup" --workspace-name \ +"testworkspace" +""" + +helps['machinelearningservices notebook'] = """ + type: group + short-summary: Manage notebook with machinelearningservices +""" + +helps['machinelearningservices notebook prepare'] = """ + type: command + short-summary: "." + examples: + - name: Prepare Notebook + text: |- + az machinelearningservices notebook prepare --resource-group "testrg123" --workspace-name \ +"workspaces123" +""" + +helps['machinelearningservices usage'] = """ + type: group + short-summary: Manage usage with machinelearningservices +""" + +helps['machinelearningservices usage list'] = """ + type: command + short-summary: "Gets the current usage information as well as limits for AML resources for given subscription and \ +location." + examples: + - name: List Usages + text: |- + az machinelearningservices usage list --location "eastus" +""" + +helps['machinelearningservices virtual-machine-size'] = """ + type: group + short-summary: Manage virtual machine size with machinelearningservices +""" + +helps['machinelearningservices virtual-machine-size list'] = """ + type: command + short-summary: "Returns supported VM Sizes in a location." + examples: + - name: List VM Sizes + text: |- + az machinelearningservices virtual-machine-size list --location "eastus" --recommended false +""" + +helps['machinelearningservices quota'] = """ + type: group + short-summary: Manage quota with machinelearningservices +""" + +helps['machinelearningservices quota list'] = """ + type: command + short-summary: "Gets the currently assigned Workspace Quotas based on VMFamily." + examples: + - name: List workspace quotas by VMFamily + text: |- + az machinelearningservices quota list --location "eastus" +""" + +helps['machinelearningservices quota update'] = """ + type: command + short-summary: "Update quota for each VM family in workspace." + parameters: + - name: --value + short-summary: "The list for update quota." + long-summary: | + Usage: --value id=XX type=XX limit=XX unit=XX + + id: Specifies the resource ID. + type: Specifies the resource type. + limit: The maximum permitted quota of the resource. + unit: An enum describing the unit of quota measurement. + + Multiple actions can be specified by using more than one --value argument. + examples: + - name: update quotas + text: |- + az machinelearningservices quota update --location "eastus" --value type="Microsoft.MachineLearningServi\ +ces/workspaces/dedicatedCores/quotas" id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/rg/provide\ +rs/Microsoft.MachineLearningServices/workspaces/demo_workspace1/quotas/StandardDSv2Family" limit=100 unit="Count" \ +--value type="Microsoft.MachineLearningServices/workspaces/dedicatedCores/quotas" id="/subscriptions/00000000-0000-0000\ +-0000-000000000000/resourceGroups/rg/providers/Microsoft.MachineLearningServices/workspaces/demo_workspace2/quotas/Stan\ +dardDSv2Family" limit=200 unit="Count" +""" + +helps['machinelearningservices workspace-connection'] = """ + type: group + short-summary: Manage workspace connection with machinelearningservices +""" + +helps['machinelearningservices workspace-connection list'] = """ + type: command + short-summary: "List all connections under a AML workspace." + examples: + - name: ListWorkspaceConnections + text: |- + az machinelearningservices workspace-connection list --category "ACR" --resource-group \ +"resourceGroup-1" --target "www.facebook.com" --workspace-name "workspace-1" +""" + +helps['machinelearningservices workspace-connection show'] = """ + type: command + short-summary: "Get the detail of a workspace connection." + examples: + - name: GetWorkspaceConnection + text: |- + az machinelearningservices workspace-connection show --connection-name "connection-1" --resource-group \ +"resourceGroup-1" --workspace-name "workspace-1" +""" + +helps['machinelearningservices workspace-connection create'] = """ + type: command + short-summary: "Add a new workspace connection." + examples: + - name: CreateWorkspaceConnection + text: |- + az machinelearningservices workspace-connection create --connection-name "connection-1" --name \ +"connection-1" --auth-type "PAT" --category "ACR" --target "www.facebook.com" --value "secrets" --resource-group \ +"resourceGroup-1" --workspace-name "workspace-1" +""" + +helps['machinelearningservices workspace-connection delete'] = """ + type: command + short-summary: "Delete a workspace connection." + examples: + - name: DeleteWorkspaceConnection + text: |- + az machinelearningservices workspace-connection delete --connection-name "connection-1" \ +--resource-group "resourceGroup-1" --workspace-name "workspace-1" +""" + +helps['machinelearningservices machine-learning-compute'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices +""" + +helps['machinelearningservices machine-learning-compute list'] = """ + type: command + short-summary: "Gets computes in specified workspace." + examples: + - name: Get Computes + text: |- + az machinelearningservices machine-learning-compute list --resource-group "testrg123" --workspace-name \ +"workspaces123" +""" + +helps['machinelearningservices machine-learning-compute show'] = """ + type: command + short-summary: "Gets compute definition by its name. Any secrets (storage keys, service credentials, etc) are not \ +returned - use 'keys' nested resource to get them." + examples: + - name: Get a AKS Compute + text: |- + az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group \ +"testrg123" --workspace-name "workspaces123" + - name: Get a AML Compute + text: |- + az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group \ +"testrg123" --workspace-name "workspaces123" + - name: Get a ComputeInstance + text: |- + az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group \ +"testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute aks'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices sub group aks +""" + +helps['machinelearningservices machine-learning-compute aks create'] = """ + type: command + short-summary: "Create compute. This call will overwrite a compute if it exists. This is a nonrecoverable \ +operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + examples: + - name: Create AKS Compute + text: |- + az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a AML Compute + text: |- + az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --ak-s-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\":{\\"maxNodeCount\ +\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedicated\\",\\"vmSize\\":\ +\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location \ +"eastus" --ak-s-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\"sshPublicAccess\\":\\"\ +Disabled\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ +--workspace-name "workspaces123" + - name: Create a ComputeInstance Compute with minimal inputs + text: |- + az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location \ +"eastus" --ak-s-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name \ +"workspaces123" + - name: Create a DataFactory Compute + text: |- + az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute aml-compute'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices sub group aml-compute +""" + +helps['machinelearningservices machine-learning-compute aml-compute create'] = """ + type: command + short-summary: "Create compute. This call will overwrite a compute if it exists. This is a nonrecoverable \ +operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + examples: + - name: Create AKS Compute + text: |- + az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a AML Compute + text: |- + az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" \ +--type "SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-00000000000\ +0/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ +--location "eastus" --aml-compute-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\"\ +:{\\"maxNodeCount\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedicated\ +\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" \ +--location "eastus" --aml-compute-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\"sshP\ +ublicAccess\\":\\"Disabled\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" \ +--resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute with minimal inputs + text: |- + az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" \ +--location "eastus" --aml-compute-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ +--workspace-name "workspaces123" + - name: Create a DataFactory Compute + text: |- + az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute compute-instance'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices sub group compute-instance +""" + +helps['machinelearningservices machine-learning-compute compute-instance create'] = """ + type: command + short-summary: "Create compute. This call will overwrite a compute if it exists. This is a nonrecoverable \ +operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + examples: + - name: Create AKS Compute + text: |- + az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a AML Compute + text: |- + az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ +--type "SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-00000000000\ +0/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ +--location "eastus" --compute-instance-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettin\ +gs\\":{\\"maxNodeCount\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedi\ +cated\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ +--location "eastus" --compute-instance-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\\ +"sshPublicAccess\\":\\"Disabled\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" \ +--resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute with minimal inputs + text: |- + az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ +--location "eastus" --compute-instance-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ +--workspace-name "workspaces123" + - name: Create a DataFactory Compute + text: |- + az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute data-factory'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices sub group data-factory +""" + +helps['machinelearningservices machine-learning-compute data-factory create'] = """ + type: command + short-summary: "Create compute. This call will overwrite a compute if it exists. This is a nonrecoverable \ +operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + examples: + - name: Create AKS Compute + text: |- + az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a AML Compute + text: |- + az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ +--type "SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-00000000000\ +0/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute with minimal inputs + text: |- + az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a DataFactory Compute + text: |- + az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute data-lake-analytics'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices sub group data-lake-analytics +""" + +helps['machinelearningservices machine-learning-compute data-lake-analytics create'] = """ + type: command + short-summary: "Create compute. This call will overwrite a compute if it exists. This is a nonrecoverable \ +operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + examples: + - name: Create AKS Compute + text: |- + az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name \ +"compute123" --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a AML Compute + text: |- + az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name \ +"compute123" --type "SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-000\ +0-000000000000/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\ +\\":{}}" --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name \ +"compute123" --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute with minimal inputs + text: |- + az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name \ +"compute123" --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a DataFactory Compute + text: |- + az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name \ +"compute123" --location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute databricks'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices sub group databricks +""" + +helps['machinelearningservices machine-learning-compute databricks create'] = """ + type: command + short-summary: "Create compute. This call will overwrite a compute if it exists. This is a nonrecoverable \ +operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + examples: + - name: Create AKS Compute + text: |- + az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a AML Compute + text: |- + az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" \ +--type "SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-00000000000\ +0/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute with minimal inputs + text: |- + az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a DataFactory Compute + text: |- + az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute hd-insight'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices sub group hd-insight +""" + +helps['machinelearningservices machine-learning-compute hd-insight create'] = """ + type: command + short-summary: "Create compute. This call will overwrite a compute if it exists. This is a nonrecoverable \ +operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + - name: --administrator-account + short-summary: "Admin credentials for master node of the cluster" + long-summary: | + Usage: --administrator-account username=XX password=XX public-key-data=XX private-key-data=XX + + username: Username of admin account + password: Password of admin account + public-key-data: Public key data + private-key-data: Private key data + examples: + - name: Create AKS Compute + text: |- + az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a AML Compute + text: |- + az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" \ +--type "SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-00000000000\ +0/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute with minimal inputs + text: |- + az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a DataFactory Compute + text: |- + az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute virtual-machine'] = """ + type: group + short-summary: Manage machine learning compute with machinelearningservices sub group virtual-machine +""" + +helps['machinelearningservices machine-learning-compute virtual-machine create'] = """ + type: command + short-summary: "Create compute. This call will overwrite a compute if it exists. This is a nonrecoverable \ +operation. If your intent is to create a new compute, do a GET first to verify that it does not exist yet." + parameters: + - name: --sku + short-summary: "The sku of the workspace." + long-summary: | + Usage: --sku name=XX tier=XX + + name: Name of the sku + tier: Tier of the sku like Basic or Enterprise + - name: --administrator-account + short-summary: "Admin credentials for virtual machine" + long-summary: | + Usage: --administrator-account username=XX password=XX public-key-data=XX private-key-data=XX + + username: Username of admin account + password: Password of admin account + public-key-data: Public key data + private-key-data: Private key data + examples: + - name: Create AKS Compute + text: |- + az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a AML Compute + text: |- + az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ +--type "SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-00000000000\ +0/resourceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a ComputeInstance Compute with minimal inputs + text: |- + az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" + - name: Create a DataFactory Compute + text: |- + az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" \ +--location "eastus" --resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute update'] = """ + type: command + short-summary: "Updates properties of a compute. This call will overwrite a compute if it exists. This is a \ +nonrecoverable operation." + parameters: + - name: --scale-settings + short-summary: "Desired scale settings for the amlCompute." + long-summary: | + Usage: --scale-settings max-node-count=XX min-node-count=XX node-idle-time-before-scale-down=XX + + max-node-count: Required. Max number of nodes to use + min-node-count: Min number of nodes to use + node-idle-time-before-scale-down: Node Idle Time before scaling down amlCompute. This string needs to be \ +in the RFC Format. + examples: + - name: Update a AmlCompute Compute + text: |- + az machinelearningservices machine-learning-compute update --compute-name "compute123" --scale-settings \ +max-node-count=4 min-node-count=4 node-idle-time-before-scale-down="PT5M" --resource-group "testrg123" \ +--workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute delete'] = """ + type: command + short-summary: "Deletes specified Machine Learning compute." + examples: + - name: Delete Compute + text: |- + az machinelearningservices machine-learning-compute delete --compute-name "compute123" --resource-group \ +"testrg123" --underlying-resource-action "Delete" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute list-key'] = """ + type: command + short-summary: "Gets secrets related to Machine Learning compute (storage keys, service credentials, etc)." + examples: + - name: List AKS Compute Keys + text: |- + az machinelearningservices machine-learning-compute list-key --compute-name "compute123" \ +--resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute list-node'] = """ + type: command + short-summary: "Get the details (e.g IP address, port etc) of all the compute nodes in the compute." + examples: + - name: Get compute nodes information for a compute + text: |- + az machinelearningservices machine-learning-compute list-node --compute-name "compute123" \ +--resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute restart'] = """ + type: command + short-summary: "Posts a restart action to a compute instance." + examples: + - name: Restart ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute restart --compute-name "compute123" \ +--resource-group "testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute start'] = """ + type: command + short-summary: "Posts a start action to a compute instance." + examples: + - name: Start ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute start --compute-name "compute123" --resource-group \ +"testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute stop'] = """ + type: command + short-summary: "Posts a stop action to a compute instance." + examples: + - name: Stop ComputeInstance Compute + text: |- + az machinelearningservices machine-learning-compute stop --compute-name "compute123" --resource-group \ +"testrg123" --workspace-name "workspaces123" +""" + +helps['machinelearningservices machine-learning-compute wait'] = """ + type: command + short-summary: Place the CLI in a waiting state until a condition of the machinelearningservices \ +machine-learning-compute is met. + examples: + - name: Pause executing next line of CLI script until the machinelearningservices machine-learning-compute is \ +successfully created. + text: |- + az machinelearningservices machine-learning-compute wait --compute-name "compute123" --resource-group \ +"testrg123" --workspace-name "workspaces123" --created + - name: Pause executing next line of CLI script until the machinelearningservices machine-learning-compute is \ +successfully updated. + text: |- + az machinelearningservices machine-learning-compute wait --compute-name "compute123" --resource-group \ +"testrg123" --workspace-name "workspaces123" --updated + - name: Pause executing next line of CLI script until the machinelearningservices machine-learning-compute is \ +successfully deleted. + text: |- + az machinelearningservices machine-learning-compute wait --compute-name "compute123" --resource-group \ +"testrg123" --workspace-name "workspaces123" --deleted +""" + +helps['machinelearningservices'] = """ + type: group + short-summary: Manage with machinelearningservices +""" + +helps['machinelearningservices list-sku'] = """ + type: command + short-summary: "Lists all skus with associated features." + examples: + - name: List Skus + text: |- + az machinelearningservices list-sku +""" + +helps['machinelearningservices private-endpoint-connection'] = """ + type: group + short-summary: Manage private endpoint connection with machinelearningservices +""" + +helps['machinelearningservices private-endpoint-connection show'] = """ + type: command + short-summary: "Gets the specified private endpoint connection associated with the workspace." + examples: + - name: WorkspaceGetPrivateEndpointConnection + text: |- + az machinelearningservices private-endpoint-connection show --name "{privateEndpointConnectionName}" \ +--resource-group "rg-1234" --workspace-name "testworkspace" +""" + +helps['machinelearningservices private-endpoint-connection delete'] = """ + type: command + short-summary: "Deletes the specified private endpoint connection associated with the workspace." + examples: + - name: WorkspaceDeletePrivateEndpointConnection + text: |- + az machinelearningservices private-endpoint-connection delete --name "{privateEndpointConnectionName}" \ +--resource-group "rg-1234" --workspace-name "testworkspace" +""" + +helps['machinelearningservices private-endpoint-connection put'] = """ + type: command + short-summary: "Update the state of specified private endpoint connection associated with the workspace." + parameters: + - name: --private-link-service-connection-state + short-summary: "A collection of information about the state of the connection between service consumer and \ +provider." + long-summary: | + Usage: --private-link-service-connection-state status=XX description=XX actions-required=XX + + status: Indicates whether the connection has been Approved/Rejected/Removed by the owner of the service. + description: The reason for approval/rejection of the connection. + actions-required: A message indicating if changes on the service provider require any updates on the \ +consumer. + examples: + - name: WorkspacePutPrivateEndpointConnection + text: |- + az machinelearningservices private-endpoint-connection put --name "{privateEndpointConnectionName}" \ +--private-link-service-connection-state description="Auto-Approved" status="Approved" --resource-group "rg-1234" \ +--workspace-name "testworkspace" +""" + +helps['machinelearningservices private-endpoint-connection wait'] = """ + type: command + short-summary: Place the CLI in a waiting state until a condition of the machinelearningservices \ +private-endpoint-connection is met. + examples: + - name: Pause executing next line of CLI script until the machinelearningservices private-endpoint-connection is \ +successfully deleted. + text: |- + az machinelearningservices private-endpoint-connection wait --name "{privateEndpointConnectionName}" \ +--resource-group "rg-1234" --workspace-name "testworkspace" --deleted +""" + +helps['machinelearningservices private-link-resource'] = """ + type: group + short-summary: Manage private link resource with machinelearningservices +""" + +helps['machinelearningservices private-link-resource list'] = """ + type: command + short-summary: "Gets the private link resources that need to be created for a workspace." + examples: + - name: WorkspaceListPrivateLinkResources + text: |- + az machinelearningservices private-link-resource list --resource-group "rg-1234" --workspace-name \ +"testworkspace" +""" diff --git a/src/machinelearningservices/azext_machinelearningservices/generated/_params.py b/src/machinelearningservices/azext_machinelearningservices/generated/_params.py new file mode 100644 index 00000000000..a437eb0417f --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/generated/_params.py @@ -0,0 +1,447 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=too-many-lines +# pylint: disable=too-many-statements + +from azure.cli.core.commands.parameters import ( + tags_type, + get_three_state_flag, + get_enum_type, + resource_group_name_type, + get_location_type +) +from azure.cli.core.commands.validators import ( + get_default_location_from_resource_group, + validate_file_or_dict +) +from azext_machinelearningservices.action import ( + AddSku, + AddSharedPrivateLinkResources, + AddKeyVaultProperties, + AddValue, + AddAdministratorAccount, + AddScaleSettings, + AddPrivateLinkServiceConnectionState +) + + +def load_arguments(self, _): + + with self.argument_context('machinelearningservices workspace list') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('skiptoken', type=str, help='Continuation token for pagination.') + + with self.argument_context('machinelearningservices workspace show') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', options_list=['--name', '-n', '--workspace-name'], type=str, help='Name of Azure ' + 'Machine Learning workspace.', id_part='name') + + with self.argument_context('machinelearningservices workspace create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', options_list=['--name', '-n', '--workspace-name'], type=str, help='Name of Azure ' + 'Machine Learning workspace.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('description', type=str, help='The description of this workspace.') + c.argument('friendly_name', type=str, help='The friendly name for this workspace. This name in mutable') + c.argument('key_vault', type=str, help='ARM id of the key vault associated with this workspace. This cannot be ' + 'changed once the workspace has been created') + c.argument('application_insights', type=str, help='ARM id of the application insights associated with this ' + 'workspace. This cannot be changed once the workspace has been created') + c.argument('container_registry', type=str, help='ARM id of the container registry associated with this ' + 'workspace. This cannot be changed once the workspace has been created') + c.argument('storage_account', type=str, help='ARM id of the storage account associated with this workspace. ' + 'This cannot be changed once the workspace has been created') + c.argument('discovery_url', type=str, help='Url for the discovery service to identify regional endpoints for ' + 'machine learning experimentation services') + c.argument('hbi_workspace', arg_type=get_three_state_flag(), help='The flag to signal HBI data in the ' + 'workspace and reduce diagnostic data collected by the service') + c.argument('image_build_compute', type=str, help='The compute name for image build') + c.argument('allow_public_access_when_behind_vnet', arg_type=get_three_state_flag(), help='The flag to indicate ' + 'whether to allow public access when behind VNet.') + c.argument('shared_private_link_resources', action=AddSharedPrivateLinkResources, nargs='+', help='The list of ' + 'shared private link resources in this workspace.') + c.argument('status', arg_type=get_enum_type(['Enabled', 'Disabled']), help='Indicates whether or not the ' + 'encryption is enabled for the workspace.', arg_group='Encryption') + c.argument('key_vault_properties', action=AddKeyVaultProperties, nargs='+', help='Customer Key vault ' + 'properties.', arg_group='Encryption') + + with self.argument_context('machinelearningservices workspace update') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', options_list=['--name', '-n', '--workspace-name'], type=str, help='Name of Azure ' + 'Machine Learning workspace.', id_part='name') + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('description', type=str, help='The description of this workspace.') + c.argument('friendly_name', type=str, help='The friendly name for this workspace.') + + with self.argument_context('machinelearningservices workspace delete') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', options_list=['--name', '-n', '--workspace-name'], type=str, help='Name of Azure ' + 'Machine Learning workspace.', id_part='name') + + with self.argument_context('machinelearningservices workspace list-key') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', options_list=['--name', '-n', '--workspace-name'], type=str, help='Name of Azure ' + 'Machine Learning workspace.') + + with self.argument_context('machinelearningservices workspace resync-key') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', options_list=['--name', '-n', '--workspace-name'], type=str, help='Name of Azure ' + 'Machine Learning workspace.', id_part='name') + + with self.argument_context('machinelearningservices workspace wait') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', options_list=['--name', '-n', '--workspace-name'], type=str, help='Name of Azure ' + 'Machine Learning workspace.', id_part='name') + + with self.argument_context('machinelearningservices workspace-feature list') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + + with self.argument_context('machinelearningservices notebook prepare') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + + with self.argument_context('machinelearningservices usage list') as c: + c.argument('location', arg_type=get_location_type(self.cli_ctx)) + + with self.argument_context('machinelearningservices virtual-machine-size list') as c: + c.argument('location', arg_type=get_location_type(self.cli_ctx)) + c.argument('compute_type', type=str, help='Type of compute to filter by.') + c.argument('recommended', arg_type=get_three_state_flag(), help='Specifies whether to return recommended vm ' + 'sizes or all vm sizes') + + with self.argument_context('machinelearningservices quota list') as c: + c.argument('location', arg_type=get_location_type(self.cli_ctx)) + + with self.argument_context('machinelearningservices quota update') as c: + c.argument('location', arg_type=get_location_type(self.cli_ctx), id_part='name') + c.argument('value', action=AddValue, nargs='+', help='The list for update quota.') + + with self.argument_context('machinelearningservices workspace-connection list') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('target', type=str, help='Target of the workspace connection.') + c.argument('category', type=str, help='Category of the workspace connection.') + + with self.argument_context('machinelearningservices workspace-connection show') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('connection_name', type=str, help='Friendly name of the workspace connection', + id_part='child_name_1') + + with self.argument_context('machinelearningservices workspace-connection create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('connection_name', type=str, help='Friendly name of the workspace connection') + c.argument('name', type=str, help='Friendly name of the workspace connection') + c.argument('category', type=str, help='Category of the workspace connection.') + c.argument('target', type=str, help='Target of the workspace connection.') + c.argument('auth_type', type=str, help='Authorization type of the workspace connection.') + c.argument('value', type=str, help='Value details of the workspace connection.') + + with self.argument_context('machinelearningservices workspace-connection delete') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('connection_name', type=str, help='Friendly name of the workspace connection', + id_part='child_name_1') + + with self.argument_context('machinelearningservices machine-learning-compute list') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('skiptoken', type=str, help='Continuation token for pagination.') + + with self.argument_context('machinelearningservices machine-learning-compute show') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.', + id_part='child_name_1') + + with self.argument_context('machinelearningservices machine-learning-compute aks create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('ak_s_compute_location', type=str, help='Location for the underlying compute') + c.argument('ak_s_description', type=str, help='The description of the Machine Learning compute.') + c.argument('ak_s_resource_id', type=str, help='ARM resource id of the underlying compute') + c.argument('ak_s_properties', type=validate_file_or_dict, help='AKS properties Expected value: ' + 'json-string/@json-file.') + + with self.argument_context('machinelearningservices machine-learning-compute aml-compute create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('compute_location', type=str, help='Location for the underlying compute') + c.argument('description', type=str, help='The description of the Machine Learning compute.') + c.argument('resource_id', type=str, help='ARM resource id of the underlying compute') + c.argument('aml_compute_properties', type=validate_file_or_dict, help='AML Compute properties Expected value: ' + 'json-string/@json-file.') + + with self.argument_context('machinelearningservices machine-learning-compute compute-instance create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('compute_location', type=str, help='Location for the underlying compute') + c.argument('description', type=str, help='The description of the Machine Learning compute.') + c.argument('resource_id', type=str, help='ARM resource id of the underlying compute') + c.argument('compute_instance_properties', type=validate_file_or_dict, help='Compute Instance properties ' + 'Expected value: json-string/@json-file.') + + with self.argument_context('machinelearningservices machine-learning-compute data-factory create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('compute_location', type=str, help='Location for the underlying compute') + c.argument('description', type=str, help='The description of the Machine Learning compute.') + c.argument('resource_id', type=str, help='ARM resource id of the underlying compute') + + with self.argument_context('machinelearningservices machine-learning-compute data-lake-analytics create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('compute_location', type=str, help='Location for the underlying compute') + c.argument('description', type=str, help='The description of the Machine Learning compute.') + c.argument('resource_id', type=str, help='ARM resource id of the underlying compute') + c.argument('data_lake_store_account_name', type=str, help='DataLake Store Account Name') + + with self.argument_context('machinelearningservices machine-learning-compute databricks create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('compute_location', type=str, help='Location for the underlying compute') + c.argument('description', type=str, help='The description of the Machine Learning compute.') + c.argument('resource_id', type=str, help='ARM resource id of the underlying compute') + c.argument('databricks_access_token', type=str, help='Databricks access token') + + with self.argument_context('machinelearningservices machine-learning-compute hd-insight create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('compute_location', type=str, help='Location for the underlying compute') + c.argument('description', type=str, help='The description of the Machine Learning compute.') + c.argument('resource_id', type=str, help='ARM resource id of the underlying compute') + c.argument('ssh_port', type=int, help='Port open for ssh connections on the master node of the cluster.') + c.argument('address', type=str, help='Public IP address of the master node of the cluster.') + c.argument('administrator_account', action=AddAdministratorAccount, nargs='+', help='Admin credentials for ' + 'master node of the cluster') + + with self.argument_context('machinelearningservices machine-learning-compute virtual-machine create') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False, + validator=get_default_location_from_resource_group) + c.argument('tags', tags_type) + c.argument('sku', action=AddSku, nargs='+', help='The sku of the workspace.') + c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['SystemAssigned', + 'SystemAssigned,UserAssigned', + 'UserAssigned', 'None']), help='The ' + 'identity type.', arg_group='Identity') + c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities ' + 'associated with resource. The user identity dictionary key references will be ARM resource ids in ' + 'the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.' + 'ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: json-string/@json-file.', + arg_group='Identity') + c.argument('compute_location', type=str, help='Location for the underlying compute') + c.argument('description', type=str, help='The description of the Machine Learning compute.') + c.argument('resource_id', type=str, help='ARM resource id of the underlying compute') + c.argument('virtual_machine_size', type=str, help='Virtual Machine size') + c.argument('ssh_port', type=int, help='Port open for ssh connections.') + c.argument('address', type=str, help='Public IP address of the virtual machine.') + c.argument('administrator_account', action=AddAdministratorAccount, nargs='+', help='Admin credentials for ' + 'virtual machine') + + with self.argument_context('machinelearningservices machine-learning-compute update') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.', + id_part='child_name_1') + c.argument('scale_settings', action=AddScaleSettings, nargs='+', help='Desired scale settings for the ' + 'amlCompute.') + + with self.argument_context('machinelearningservices machine-learning-compute delete') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.', + id_part='child_name_1') + c.argument('underlying_resource_action', arg_type=get_enum_type(['Delete', 'Detach']), help='Delete the ' + 'underlying compute if \'Delete\', or detach the underlying compute from workspace if \'Detach\'.') + + with self.argument_context('machinelearningservices machine-learning-compute list-key') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + + with self.argument_context('machinelearningservices machine-learning-compute list-node') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.') + + with self.argument_context('machinelearningservices machine-learning-compute restart') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.', + id_part='child_name_1') + + with self.argument_context('machinelearningservices machine-learning-compute start') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.', + id_part='child_name_1') + + with self.argument_context('machinelearningservices machine-learning-compute stop') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.', + id_part='child_name_1') + + with self.argument_context('machinelearningservices machine-learning-compute wait') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('compute_name', type=str, help='Name of the Azure Machine Learning compute.', + id_part='child_name_1') + + with self.argument_context('machinelearningservices private-endpoint-connection show') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('private_endpoint_connection_name', options_list=['--name', '-n', '--private-endpoint-connection-nam' + 'e'], type=str, help='The name of the private ' + 'endpoint connection associated with the workspace', id_part='child_name_1') + + with self.argument_context('machinelearningservices private-endpoint-connection delete') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('private_endpoint_connection_name', options_list=['--name', '-n', '--private-endpoint-connection-nam' + 'e'], type=str, help='The name of the private ' + 'endpoint connection associated with the workspace', id_part='child_name_1') + + with self.argument_context('machinelearningservices private-endpoint-connection put') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('private_endpoint_connection_name', options_list=['--name', '-n', '--private-endpoint-connection-nam' + 'e'], type=str, help='The name of the private ' + 'endpoint connection associated with the workspace', id_part='child_name_1') + c.argument('private_link_service_connection_state', action=AddPrivateLinkServiceConnectionState, nargs='+', + help='A collection of information about the state of the connection between service consumer and ' + 'provider.') + + with self.argument_context('machinelearningservices private-endpoint-connection wait') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.', id_part='name') + c.argument('private_endpoint_connection_name', options_list=['--name', '-n', '--private-endpoint-connection-nam' + 'e'], type=str, help='The name of the private ' + 'endpoint connection associated with the workspace', id_part='child_name_1') + + with self.argument_context('machinelearningservices private-link-resource list') as c: + c.argument('resource_group_name', resource_group_name_type) + c.argument('workspace_name', type=str, help='Name of Azure Machine Learning workspace.') diff --git a/src/machinelearningservices/azext_machinelearningservices/generated/_validators.py b/src/machinelearningservices/azext_machinelearningservices/generated/_validators.py new file mode 100644 index 00000000000..b33a44c1ebf --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/generated/_validators.py @@ -0,0 +1,9 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- diff --git a/src/machinelearningservices/azext_machinelearningservices/generated/action.py b/src/machinelearningservices/azext_machinelearningservices/generated/action.py new file mode 100644 index 00000000000..a185440b78b --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/generated/action.py @@ -0,0 +1,225 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=protected-access + +import argparse +from collections import defaultdict +from knack.util import CLIError + + +class AddSku(argparse.Action): + def __call__(self, parser, namespace, values, option_string=None): + action = self.get_action(values, option_string) + namespace.sku = action + + def get_action(self, values, option_string): # pylint: disable=no-self-use + try: + properties = defaultdict(list) + for (k, v) in (x.split('=', 1) for x in values): + properties[k].append(v) + properties = dict(properties) + except ValueError: + raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) + d = {} + for k in properties: + kl = k.lower() + v = properties[k] + if kl == 'name': + d['name'] = v[0] + elif kl == 'tier': + d['tier'] = v[0] + else: + raise CLIError('Unsupported Key {} is provided for parameter sku. All possible keys are: name, tier'. + format(k)) + return d + + +class AddSharedPrivateLinkResources(argparse._AppendAction): + def __call__(self, parser, namespace, values, option_string=None): + action = self.get_action(values, option_string) + super(AddSharedPrivateLinkResources, self).__call__(parser, namespace, action, option_string) + + def get_action(self, values, option_string): # pylint: disable=no-self-use + try: + properties = defaultdict(list) + for (k, v) in (x.split('=', 1) for x in values): + properties[k].append(v) + properties = dict(properties) + except ValueError: + raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) + d = {} + for k in properties: + kl = k.lower() + v = properties[k] + if kl == 'name': + d['name'] = v[0] + elif kl == 'private-link-resource-id': + d['private_link_resource_id'] = v[0] + elif kl == 'group-id': + d['group_id'] = v[0] + elif kl == 'request-message': + d['request_message'] = v[0] + elif kl == 'status': + d['status'] = v[0] + else: + raise CLIError('Unsupported Key {} is provided for parameter shared_private_link_resources. All ' + 'possible keys are: name, private-link-resource-id, group-id, request-message, status'. + format(k)) + return d + + +class AddKeyVaultProperties(argparse.Action): + def __call__(self, parser, namespace, values, option_string=None): + action = self.get_action(values, option_string) + namespace.key_vault_properties = action + + def get_action(self, values, option_string): # pylint: disable=no-self-use + try: + properties = defaultdict(list) + for (k, v) in (x.split('=', 1) for x in values): + properties[k].append(v) + properties = dict(properties) + except ValueError: + raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) + d = {} + for k in properties: + kl = k.lower() + v = properties[k] + if kl == 'key-vault-arm-id': + d['key_vault_arm_id'] = v[0] + elif kl == 'key-identifier': + d['key_identifier'] = v[0] + elif kl == 'identity-client-id': + d['identity_client_id'] = v[0] + else: + raise CLIError('Unsupported Key {} is provided for parameter key_vault_properties. All possible keys ' + 'are: key-vault-arm-id, key-identifier, identity-client-id'.format(k)) + return d + + +class AddValue(argparse._AppendAction): + def __call__(self, parser, namespace, values, option_string=None): + action = self.get_action(values, option_string) + super(AddValue, self).__call__(parser, namespace, action, option_string) + + def get_action(self, values, option_string): # pylint: disable=no-self-use + try: + properties = defaultdict(list) + for (k, v) in (x.split('=', 1) for x in values): + properties[k].append(v) + properties = dict(properties) + except ValueError: + raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) + d = {} + for k in properties: + kl = k.lower() + v = properties[k] + if kl == 'id': + d['id'] = v[0] + elif kl == 'type': + d['type'] = v[0] + elif kl == 'limit': + d['limit'] = v[0] + elif kl == 'unit': + d['unit'] = v[0] + else: + raise CLIError('Unsupported Key {} is provided for parameter value. All possible keys are: id, type, ' + 'limit, unit'.format(k)) + return d + + +class AddAdministratorAccount(argparse.Action): + def __call__(self, parser, namespace, values, option_string=None): + action = self.get_action(values, option_string) + namespace.administrator_account = action + + def get_action(self, values, option_string): # pylint: disable=no-self-use + try: + properties = defaultdict(list) + for (k, v) in (x.split('=', 1) for x in values): + properties[k].append(v) + properties = dict(properties) + except ValueError: + raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) + d = {} + for k in properties: + kl = k.lower() + v = properties[k] + if kl == 'username': + d['username'] = v[0] + elif kl == 'password': + d['password'] = v[0] + elif kl == 'public-key-data': + d['public_key_data'] = v[0] + elif kl == 'private-key-data': + d['private_key_data'] = v[0] + else: + raise CLIError('Unsupported Key {} is provided for parameter administrator_account. All possible keys ' + 'are: username, password, public-key-data, private-key-data'.format(k)) + return d + + +class AddScaleSettings(argparse.Action): + def __call__(self, parser, namespace, values, option_string=None): + action = self.get_action(values, option_string) + namespace.scale_settings = action + + def get_action(self, values, option_string): # pylint: disable=no-self-use + try: + properties = defaultdict(list) + for (k, v) in (x.split('=', 1) for x in values): + properties[k].append(v) + properties = dict(properties) + except ValueError: + raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) + d = {} + d['min_node_count'] = 0 + for k in properties: + kl = k.lower() + v = properties[k] + if kl == 'max-node-count': + d['max_node_count'] = v[0] + elif kl == 'min-node-count': + d['min_node_count'] = v[0] + elif kl == 'node-idle-time-before-scale-down': + d['node_idle_time_before_scale_down'] = v[0] + else: + raise CLIError('Unsupported Key {} is provided for parameter scale_settings. All possible keys are: ' + 'max-node-count, min-node-count, node-idle-time-before-scale-down'.format(k)) + return d + + +class AddPrivateLinkServiceConnectionState(argparse.Action): + def __call__(self, parser, namespace, values, option_string=None): + action = self.get_action(values, option_string) + namespace.private_link_service_connection_state = action + + def get_action(self, values, option_string): # pylint: disable=no-self-use + try: + properties = defaultdict(list) + for (k, v) in (x.split('=', 1) for x in values): + properties[k].append(v) + properties = dict(properties) + except ValueError: + raise CLIError('usage error: {} [KEY=VALUE ...]'.format(option_string)) + d = {} + for k in properties: + kl = k.lower() + v = properties[k] + if kl == 'status': + d['status'] = v[0] + elif kl == 'description': + d['description'] = v[0] + elif kl == 'actions-required': + d['actions_required'] = v[0] + else: + raise CLIError('Unsupported Key {} is provided for parameter private_link_service_connection_state. ' + 'All possible keys are: status, description, actions-required'.format(k)) + return d diff --git a/src/machinelearningservices/azext_machinelearningservices/generated/commands.py b/src/machinelearningservices/azext_machinelearningservices/generated/commands.py new file mode 100644 index 00000000000..712b906364f --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/generated/commands.py @@ -0,0 +1,162 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=too-many-statements +# pylint: disable=too-many-locals + +from azure.cli.core.commands import CliCommandType + + +def load_command_table(self, _): + + from azext_machinelearningservices.generated._client_factory import cf_workspace + machinelearningservices_workspace = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._workspaces_ope' + 'rations#WorkspacesOperations.{}', + client_factory=cf_workspace) + with self.command_group('machinelearningservices workspace', machinelearningservices_workspace, + client_factory=cf_workspace) as g: + g.custom_command('list', 'machinelearningservices_workspace_list') + g.custom_show_command('show', 'machinelearningservices_workspace_show') + g.custom_command('create', 'machinelearningservices_workspace_create', supports_no_wait=True) + g.custom_command('update', 'machinelearningservices_workspace_update') + g.custom_command('delete', 'machinelearningservices_workspace_delete', supports_no_wait=True, + confirmation=True) + g.custom_command('list-key', 'machinelearningservices_workspace_list_key') + g.custom_command('resync-key', 'machinelearningservices_workspace_resync_key') + g.custom_wait_command('wait', 'machinelearningservices_workspace_show') + + from azext_machinelearningservices.generated._client_factory import cf_workspace_feature + machinelearningservices_workspace_feature = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._workspace_feat' + 'ures_operations#WorkspaceFeaturesOperations.{}', + client_factory=cf_workspace_feature) + with self.command_group('machinelearningservices workspace-feature', machinelearningservices_workspace_feature, + client_factory=cf_workspace_feature) as g: + g.custom_command('list', 'machinelearningservices_workspace_feature_list') + + from azext_machinelearningservices.generated._client_factory import cf_notebook + machinelearningservices_notebook = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._notebooks_oper' + 'ations#NotebooksOperations.{}', + client_factory=cf_notebook) + with self.command_group('machinelearningservices notebook', machinelearningservices_notebook, + client_factory=cf_notebook) as g: + g.custom_command('prepare', 'machinelearningservices_notebook_prepare') + + from azext_machinelearningservices.generated._client_factory import cf_usage + machinelearningservices_usage = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._usages_operati' + 'ons#UsagesOperations.{}', + client_factory=cf_usage) + with self.command_group('machinelearningservices usage', machinelearningservices_usage, + client_factory=cf_usage) as g: + g.custom_command('list', 'machinelearningservices_usage_list') + + from azext_machinelearningservices.generated._client_factory import cf_virtual_machine_size + machinelearningservices_virtual_machine_size = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._virtual_machin' + 'e_sizes_operations#VirtualMachineSizesOperations.{}', + client_factory=cf_virtual_machine_size) + with self.command_group('machinelearningservices virtual-machine-size', + machinelearningservices_virtual_machine_size, + client_factory=cf_virtual_machine_size) as g: + g.custom_command('list', 'machinelearningservices_virtual_machine_size_list') + + from azext_machinelearningservices.generated._client_factory import cf_quota + machinelearningservices_quota = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._quotas_operati' + 'ons#QuotasOperations.{}', + client_factory=cf_quota) + with self.command_group('machinelearningservices quota', machinelearningservices_quota, + client_factory=cf_quota) as g: + g.custom_command('list', 'machinelearningservices_quota_list') + g.custom_command('update', 'machinelearningservices_quota_update') + + from azext_machinelearningservices.generated._client_factory import cf_workspace_connection + machinelearningservices_workspace_connection = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._workspace_conn' + 'ections_operations#WorkspaceConnectionsOperations.{}', + client_factory=cf_workspace_connection) + with self.command_group('machinelearningservices workspace-connection', + machinelearningservices_workspace_connection, + client_factory=cf_workspace_connection) as g: + g.custom_command('list', 'machinelearningservices_workspace_connection_list') + g.custom_show_command('show', 'machinelearningservices_workspace_connection_show') + g.custom_command('create', 'machinelearningservices_workspace_connection_create') + g.custom_command('delete', 'machinelearningservices_workspace_connection_delete', confirmation=True) + + from azext_machinelearningservices.generated._client_factory import cf_machine_learning_compute + machinelearningservices_machine_learning_compute = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._machine_learni' + 'ng_compute_operations#MachineLearningComputeOperations.{}', + client_factory=cf_machine_learning_compute) + with self.command_group('machinelearningservices machine-learning-compute', + machinelearningservices_machine_learning_compute, + client_factory=cf_machine_learning_compute) as g: + g.custom_command('list', 'machinelearningservices_machine_learning_compute_list') + g.custom_show_command('show', 'machinelearningservices_machine_learning_compute_show') + g.custom_command('aks create', 'machinelearningservices_machine_learning_compute_aks_create', + supports_no_wait=True) + g.custom_command('aml-compute create', 'machinelearningservices_machine_learning_compute_aml_compute_create', + supports_no_wait=True) + g.custom_command('compute-instance create', 'machinelearningservices_machine_learning_compute_compute_instance_' + 'create', supports_no_wait=True) + g.custom_command('data-factory create', 'machinelearningservices_machine_learning_compute_data_factory_create', + supports_no_wait=True) + g.custom_command('data-lake-analytics create', 'machinelearningservices_machine_learning_compute_data_lake_anal' + 'ytics_create', supports_no_wait=True) + g.custom_command('databricks create', 'machinelearningservices_machine_learning_compute_databricks_create', + supports_no_wait=True) + g.custom_command('hd-insight create', 'machinelearningservices_machine_learning_compute_hd_insight_create', + supports_no_wait=True) + g.custom_command('virtual-machine create', 'machinelearningservices_machine_learning_compute_virtual_machine_cr' + 'eate', supports_no_wait=True) + g.custom_command('update', 'machinelearningservices_machine_learning_compute_update', supports_no_wait=True) + g.custom_command('delete', 'machinelearningservices_machine_learning_compute_delete', supports_no_wait=True, + confirmation=True) + g.custom_command('list-key', 'machinelearningservices_machine_learning_compute_list_key') + g.custom_command('list-node', 'machinelearningservices_machine_learning_compute_list_node') + g.custom_command('restart', 'machinelearningservices_machine_learning_compute_restart') + g.custom_command('start', 'machinelearningservices_machine_learning_compute_start') + g.custom_command('stop', 'machinelearningservices_machine_learning_compute_stop') + g.custom_wait_command('wait', 'machinelearningservices_machine_learning_compute_show') + + from azext_machinelearningservices.generated._client_factory import cf_machinelearningservices + machinelearningservices_ = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._model_operatio' + 'ns#AzureMachineLearningWorkspacesOperationsMixin.{}', + client_factory=cf_machinelearningservices) + with self.command_group('machinelearningservices', machinelearningservices_, + client_factory=cf_machinelearningservices, is_experimental=True) as g: + g.custom_command('list-sku', 'machinelearningservices_list_sku') + + from azext_machinelearningservices.generated._client_factory import cf_private_endpoint_connection + machinelearningservices_private_endpoint_connection = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._private_endpoi' + 'nt_connections_operations#PrivateEndpointConnectionsOperations.{}', + client_factory=cf_private_endpoint_connection) + with self.command_group('machinelearningservices private-endpoint-connection', + machinelearningservices_private_endpoint_connection, + client_factory=cf_private_endpoint_connection) as g: + g.custom_show_command('show', 'machinelearningservices_private_endpoint_connection_show') + g.custom_command('delete', 'machinelearningservices_private_endpoint_connection_delete', supports_no_wait=True, + confirmation=True) + g.custom_command('put', 'machinelearningservices_private_endpoint_connection_put') + g.custom_wait_command('wait', 'machinelearningservices_private_endpoint_connection_show') + + from azext_machinelearningservices.generated._client_factory import cf_private_link_resource + machinelearningservices_private_link_resource = CliCommandType( + operations_tmpl='azext_machinelearningservices.vendored_sdks.machinelearningservices.operations._private_link_r' + 'esources_operations#PrivateLinkResourcesOperations.{}', + client_factory=cf_private_link_resource) + with self.command_group('machinelearningservices private-link-resource', + machinelearningservices_private_link_resource, + client_factory=cf_private_link_resource) as g: + g.custom_command('list', 'machinelearningservices_private_link_resource_list') diff --git a/src/machinelearningservices/azext_machinelearningservices/generated/custom.py b/src/machinelearningservices/azext_machinelearningservices/generated/custom.py new file mode 100644 index 00000000000..c9239de04d6 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/generated/custom.py @@ -0,0 +1,645 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=line-too-long +# pylint: disable=too-many-lines + +from azure.cli.core.util import sdk_no_wait + + +def machinelearningservices_workspace_list(client, + resource_group_name=None, + skiptoken=None): + if resource_group_name: + return client.list_by_resource_group(resource_group_name=resource_group_name, + skiptoken=skiptoken) + return client.list_by_subscription(skiptoken=skiptoken) + + +def machinelearningservices_workspace_show(client, + resource_group_name, + workspace_name): + return client.get(resource_group_name=resource_group_name, + workspace_name=workspace_name) + + +def machinelearningservices_workspace_create(client, + resource_group_name, + workspace_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + description=None, + friendly_name=None, + key_vault=None, + application_insights=None, + container_registry=None, + storage_account=None, + discovery_url=None, + hbi_workspace=None, + image_build_compute=None, + allow_public_access_when_behind_vnet=None, + shared_private_link_resources=None, + status=None, + key_vault_properties=None, + no_wait=False): + if hbi_workspace is None: + hbi_workspace = False + if allow_public_access_when_behind_vnet is None: + allow_public_access_when_behind_vnet = False + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['friendly_name'] = friendly_name + parameters['key_vault'] = key_vault + parameters['application_insights'] = application_insights + parameters['container_registry'] = container_registry + parameters['storage_account'] = storage_account + parameters['discovery_url'] = discovery_url + parameters['hbi_workspace'] = False if hbi_workspace is None else hbi_workspace + parameters['image_build_compute'] = image_build_compute + parameters['allow_public_access_when_behind_vnet'] = False if allow_public_access_when_behind_vnet is None else allow_public_access_when_behind_vnet + parameters['shared_private_link_resources'] = shared_private_link_resources + parameters['encryption'] = {} + parameters['encryption']['status'] = status + parameters['encryption']['key_vault_properties'] = key_vault_properties + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + parameters=parameters) + + +def machinelearningservices_workspace_update(client, + resource_group_name, + workspace_name, + tags=None, + sku=None, + description=None, + friendly_name=None): + parameters = {} + parameters['tags'] = tags + parameters['sku'] = sku + parameters['description'] = description + parameters['friendly_name'] = friendly_name + return client.update(resource_group_name=resource_group_name, + workspace_name=workspace_name, + parameters=parameters) + + +def machinelearningservices_workspace_delete(client, + resource_group_name, + workspace_name, + no_wait=False): + return sdk_no_wait(no_wait, + client.begin_delete, + resource_group_name=resource_group_name, + workspace_name=workspace_name) + + +def machinelearningservices_workspace_list_key(client, + resource_group_name, + workspace_name): + return client.list_keys(resource_group_name=resource_group_name, + workspace_name=workspace_name) + + +def machinelearningservices_workspace_resync_key(client, + resource_group_name, + workspace_name): + return client.resync_keys(resource_group_name=resource_group_name, + workspace_name=workspace_name) + + +def machinelearningservices_workspace_feature_list(client, + resource_group_name, + workspace_name): + return client.list(resource_group_name=resource_group_name, + workspace_name=workspace_name) + + +def machinelearningservices_notebook_prepare(client, + resource_group_name, + workspace_name): + return client.begin_prepare(resource_group_name=resource_group_name, + workspace_name=workspace_name) + + +def machinelearningservices_usage_list(client, + location): + return client.list(location=location) + + +def machinelearningservices_virtual_machine_size_list(client, + location, + compute_type=None, + recommended=None): + return client.list(location=location, + compute_type=compute_type, + recommended=recommended) + + +def machinelearningservices_quota_list(client, + location): + return client.list(location=location) + + +def machinelearningservices_quota_update(client, + location, + value=None): + parameters = {} + parameters['value'] = value + return client.update(location=location, + parameters=parameters) + + +def machinelearningservices_workspace_connection_list(client, + resource_group_name, + workspace_name, + target=None, + category=None): + return client.list(resource_group_name=resource_group_name, + workspace_name=workspace_name, + target=target, + category=category) + + +def machinelearningservices_workspace_connection_show(client, + resource_group_name, + workspace_name, + connection_name): + return client.get(resource_group_name=resource_group_name, + workspace_name=workspace_name, + connection_name=connection_name) + + +def machinelearningservices_workspace_connection_create(client, + resource_group_name, + workspace_name, + connection_name, + name=None, + category=None, + target=None, + auth_type=None, + value=None): + parameters = {} + parameters['name'] = name + parameters['category'] = category + parameters['target'] = target + parameters['auth_type'] = auth_type + parameters['value'] = value + return client.create(resource_group_name=resource_group_name, + workspace_name=workspace_name, + connection_name=connection_name, + parameters=parameters) + + +def machinelearningservices_workspace_connection_delete(client, + resource_group_name, + workspace_name, + connection_name): + return client.delete(resource_group_name=resource_group_name, + workspace_name=workspace_name, + connection_name=connection_name) + + +def machinelearningservices_machine_learning_compute_list(client, + resource_group_name, + workspace_name, + skiptoken=None): + return client.list_by_workspace(resource_group_name=resource_group_name, + workspace_name=workspace_name, + skiptoken=skiptoken) + + +def machinelearningservices_machine_learning_compute_show(client, + resource_group_name, + workspace_name, + compute_name): + return client.get(resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name) + + +def machinelearningservices_machine_learning_compute_aks_create(client, + resource_group_name, + workspace_name, + compute_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + ak_s_compute_location=None, + ak_s_description=None, + ak_s_resource_id=None, + ak_s_properties=None, + no_wait=False): + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['properties'] = {} + parameters['properties']['compute_type'] = 'Aks' + parameters['properties']['compute_location'] = ak_s_compute_location + parameters['properties']['description'] = ak_s_description + parameters['properties']['resource_id'] = ak_s_resource_id + parameters['properties']['properties'] = ak_s_properties + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_aml_compute_create(client, + resource_group_name, + workspace_name, + compute_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + compute_location=None, + description=None, + resource_id=None, + aml_compute_properties=None, + no_wait=False): + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['properties'] = {} + parameters['properties']['compute_type'] = 'AmlCompute' + parameters['properties']['compute_location'] = compute_location + parameters['properties']['description'] = description + parameters['properties']['resource_id'] = resource_id + parameters['properties']['properties'] = aml_compute_properties + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_compute_instance_create(client, + resource_group_name, + workspace_name, + compute_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + compute_location=None, + description=None, + resource_id=None, + compute_instance_properties=None, + no_wait=False): + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['properties'] = {} + parameters['properties']['compute_type'] = 'ComputeInstance' + parameters['properties']['compute_location'] = compute_location + parameters['properties']['description'] = description + parameters['properties']['resource_id'] = resource_id + parameters['properties']['properties'] = compute_instance_properties + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_data_factory_create(client, + resource_group_name, + workspace_name, + compute_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + compute_location=None, + description=None, + resource_id=None, + no_wait=False): + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['properties'] = {} + parameters['properties']['compute_type'] = 'DataFactory' + parameters['properties']['compute_location'] = compute_location + parameters['properties']['description'] = description + parameters['properties']['resource_id'] = resource_id + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_data_lake_analytics_create(client, + resource_group_name, + workspace_name, + compute_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + compute_location=None, + description=None, + resource_id=None, + data_lake_store_account_name=None, + no_wait=False): + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['properties'] = {} + parameters['properties']['compute_type'] = 'DataLakeAnalytics' + parameters['properties']['compute_location'] = compute_location + parameters['properties']['description'] = description + parameters['properties']['resource_id'] = resource_id + parameters['properties']['properties'] = {} + parameters['properties']['properties']['data_lake_store_account_name'] = data_lake_store_account_name + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_databricks_create(client, + resource_group_name, + workspace_name, + compute_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + compute_location=None, + description=None, + resource_id=None, + databricks_access_token=None, + no_wait=False): + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['properties'] = {} + parameters['properties']['compute_type'] = 'Databricks' + parameters['properties']['compute_location'] = compute_location + parameters['properties']['description'] = description + parameters['properties']['resource_id'] = resource_id + parameters['properties']['properties'] = {} + parameters['properties']['properties']['databricks_access_token'] = databricks_access_token + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_hd_insight_create(client, + resource_group_name, + workspace_name, + compute_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + compute_location=None, + description=None, + resource_id=None, + ssh_port=None, + address=None, + administrator_account=None, + no_wait=False): + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['properties'] = {} + parameters['properties']['compute_type'] = 'HdInsight' + parameters['properties']['compute_location'] = compute_location + parameters['properties']['description'] = description + parameters['properties']['resource_id'] = resource_id + parameters['properties']['properties'] = {} + parameters['properties']['properties']['ssh_port'] = ssh_port + parameters['properties']['properties']['address'] = address + parameters['properties']['properties']['administrator_account'] = administrator_account + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_virtual_machine_create(client, + resource_group_name, + workspace_name, + compute_name, + location=None, + tags=None, + sku=None, + type_=None, + user_assigned_identities=None, + compute_location=None, + description=None, + resource_id=None, + virtual_machine_size=None, + ssh_port=None, + address=None, + administrator_account=None, + no_wait=False): + parameters = {} + parameters['location'] = location + parameters['tags'] = tags + parameters['sku'] = sku + parameters['identity'] = {} + parameters['identity']['type'] = type_ + parameters['identity']['user_assigned_identities'] = user_assigned_identities + parameters['properties'] = {} + parameters['properties']['compute_type'] = 'VirtualMachine' + parameters['properties']['compute_location'] = compute_location + parameters['properties']['description'] = description + parameters['properties']['resource_id'] = resource_id + parameters['properties']['properties'] = {} + parameters['properties']['properties']['virtual_machine_size'] = virtual_machine_size + parameters['properties']['properties']['ssh_port'] = ssh_port + parameters['properties']['properties']['address'] = address + parameters['properties']['properties']['administrator_account'] = administrator_account + return sdk_no_wait(no_wait, + client.begin_create_or_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_update(client, + resource_group_name, + workspace_name, + compute_name, + scale_settings=None, + no_wait=False): + parameters = {} + parameters['scale_settings'] = scale_settings + return sdk_no_wait(no_wait, + client.begin_update, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters) + + +def machinelearningservices_machine_learning_compute_delete(client, + resource_group_name, + workspace_name, + compute_name, + underlying_resource_action, + no_wait=False): + return sdk_no_wait(no_wait, + client.begin_delete, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + underlying_resource_action=underlying_resource_action) + + +def machinelearningservices_machine_learning_compute_list_key(client, + resource_group_name, + workspace_name, + compute_name): + return client.list_keys(resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name) + + +def machinelearningservices_machine_learning_compute_list_node(client, + resource_group_name, + workspace_name, + compute_name): + return client.list_nodes(resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name) + + +def machinelearningservices_machine_learning_compute_restart(client, + resource_group_name, + workspace_name, + compute_name): + return client.restart(resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name) + + +def machinelearningservices_machine_learning_compute_start(client, + resource_group_name, + workspace_name, + compute_name): + return client.start(resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name) + + +def machinelearningservices_machine_learning_compute_stop(client, + resource_group_name, + workspace_name, + compute_name): + return client.stop(resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name) + + +def machinelearningservices_list_sku(client): + return client.list_skus() + + +def machinelearningservices_private_endpoint_connection_show(client, + resource_group_name, + workspace_name, + private_endpoint_connection_name): + return client.get(resource_group_name=resource_group_name, + workspace_name=workspace_name, + private_endpoint_connection_name=private_endpoint_connection_name) + + +def machinelearningservices_private_endpoint_connection_delete(client, + resource_group_name, + workspace_name, + private_endpoint_connection_name, + no_wait=False): + return sdk_no_wait(no_wait, + client.begin_delete, + resource_group_name=resource_group_name, + workspace_name=workspace_name, + private_endpoint_connection_name=private_endpoint_connection_name) + + +def machinelearningservices_private_endpoint_connection_put(client, + resource_group_name, + workspace_name, + private_endpoint_connection_name, + private_link_service_connection_state=None): + properties = {} + properties['private_link_service_connection_state'] = private_link_service_connection_state + return client.put(resource_group_name=resource_group_name, + workspace_name=workspace_name, + private_endpoint_connection_name=private_endpoint_connection_name, + properties=properties) + + +def machinelearningservices_private_link_resource_list(client, + resource_group_name, + workspace_name): + return client.list_by_workspace(resource_group_name=resource_group_name, + workspace_name=workspace_name) diff --git a/src/machinelearningservices/azext_machinelearningservices/manual/__init__.py b/src/machinelearningservices/azext_machinelearningservices/manual/__init__.py new file mode 100644 index 00000000000..c9cfdc73e77 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/manual/__init__.py @@ -0,0 +1,12 @@ +# 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. +# -------------------------------------------------------------------------- + +__path__ = __import__('pkgutil').extend_path(__path__, __name__) diff --git a/src/machinelearningservices/azext_machinelearningservices/tests/__init__.py b/src/machinelearningservices/azext_machinelearningservices/tests/__init__.py new file mode 100644 index 00000000000..70488e93851 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/tests/__init__.py @@ -0,0 +1,116 @@ +# 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. +# -------------------------------------------------------------------------- +import inspect +import logging +import os +import sys +import traceback +import datetime as dt + +from azure.core.exceptions import AzureError +from azure.cli.testsdk.exceptions import CliTestError, CliExecutionError, JMESPathCheckAssertionError + + +logger = logging.getLogger('azure.cli.testsdk') +logger.addHandler(logging.StreamHandler()) +__path__ = __import__('pkgutil').extend_path(__path__, __name__) +exceptions = [] +test_map = dict() +SUCCESSED = "successed" +FAILED = "failed" + + +def try_manual(func): + def import_manual_function(origin_func): + from importlib import import_module + decorated_path = inspect.getfile(origin_func).lower() + module_path = __path__[0].lower() + if not decorated_path.startswith(module_path): + raise Exception("Decorator can only be used in submodules!") + manual_path = os.path.join( + decorated_path[module_path.rfind(os.path.sep) + 1:]) + manual_file_path, manual_file_name = os.path.split(manual_path) + module_name, _ = os.path.splitext(manual_file_name) + manual_module = "..manual." + \ + ".".join(manual_file_path.split(os.path.sep) + [module_name, ]) + return getattr(import_module(manual_module, package=__name__), origin_func.__name__) + + def get_func_to_call(): + func_to_call = func + try: + func_to_call = import_manual_function(func) + logger.info("Found manual override for %s(...)", func.__name__) + except (ImportError, AttributeError): + pass + return func_to_call + + def wrapper(*args, **kwargs): + func_to_call = get_func_to_call() + logger.info("running %s()...", func.__name__) + try: + test_map[func.__name__] = dict() + test_map[func.__name__]["result"] = SUCCESSED + test_map[func.__name__]["error_message"] = "" + test_map[func.__name__]["error_stack"] = "" + test_map[func.__name__]["error_normalized"] = "" + test_map[func.__name__]["start_dt"] = dt.datetime.utcnow() + ret = func_to_call(*args, **kwargs) + except (AssertionError, AzureError, CliTestError, CliExecutionError, SystemExit, + JMESPathCheckAssertionError) as e: + use_exception_cache = os.getenv("TEST_EXCEPTION_CACHE") + if use_exception_cache is None or use_exception_cache.lower() != "true": + raise + test_map[func.__name__]["end_dt"] = dt.datetime.utcnow() + test_map[func.__name__]["result"] = FAILED + test_map[func.__name__]["error_message"] = str(e).replace("\r\n", " ").replace("\n", " ")[:500] + test_map[func.__name__]["error_stack"] = traceback.format_exc().replace( + "\r\n", " ").replace("\n", " ")[:500] + logger.info("--------------------------------------") + logger.info("step exception: %s", e) + logger.error("--------------------------------------") + logger.error("step exception in %s: %s", func.__name__, e) + logger.info(traceback.format_exc()) + exceptions.append((func.__name__, sys.exc_info())) + else: + test_map[func.__name__]["end_dt"] = dt.datetime.utcnow() + return ret + + if inspect.isclass(func): + return get_func_to_call() + return wrapper + + +def calc_coverage(filename): + filename = filename.split(".")[0] + coverage_name = filename + "_coverage.md" + with open(coverage_name, "w") as f: + f.write("|Scenario|Result|ErrorMessage|ErrorStack|ErrorNormalized|StartDt|EndDt|\n") + total = len(test_map) + covered = 0 + for k, v in test_map.items(): + if not k.startswith("step_"): + total -= 1 + continue + if v["result"] == SUCCESSED: + covered += 1 + f.write("|{step_name}|{result}|{error_message}|{error_stack}|{error_normalized}|{start_dt}|" + "{end_dt}|\n".format(step_name=k, **v)) + f.write("Coverage: {}/{}\n".format(covered, total)) + print("Create coverage\n", file=sys.stderr) + + +def raise_if(): + if exceptions: + if len(exceptions) <= 1: + raise exceptions[0][1][1] + message = "{}\nFollowed with exceptions in other steps:\n".format(str(exceptions[0][1][1])) + message += "\n".join(["{}: {}".format(h[0], h[1][1]) for h in exceptions[1:]]) + raise exceptions[0][1][0](message).with_traceback(exceptions[0][1][2]) diff --git a/src/machinelearningservices/azext_machinelearningservices/tests/latest/__init__.py b/src/machinelearningservices/azext_machinelearningservices/tests/latest/__init__.py new file mode 100644 index 00000000000..c9cfdc73e77 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/tests/latest/__init__.py @@ -0,0 +1,12 @@ +# 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. +# -------------------------------------------------------------------------- + +__path__ = __import__('pkgutil').extend_path(__path__, __name__) diff --git a/src/machinelearningservices/azext_machinelearningservices/tests/latest/example_steps.py b/src/machinelearningservices/azext_machinelearningservices/tests/latest/example_steps.py new file mode 100644 index 00000000000..90952047249 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/tests/latest/example_steps.py @@ -0,0 +1,496 @@ +# -------------------------------------------------------------------------- +# 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 .. import try_manual + + +# EXAMPLE: /Workspaces/put/Create Workspace +@try_manual +def step_workspace_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace create ' + '--type "SystemAssigned" ' + '--location "eastus2euap" ' + '--description "test description" ' + '--application-insights "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/microsoft.insights' + '/components/testinsights" ' + '--container-registry "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/Microsoft.ContainerR' + 'egistry/registries/testRegistry" ' + '--key-vault-properties identity-client-id="" key-identifier="https://testkv.vault.azure.net/keys/testkey/' + 'aabbccddee112233445566778899aabb" key-vault-arm-id="/subscriptions/{subscription_id}/resourceGroups/{rg}/' + 'providers/Microsoft.KeyVault/vaults/testkv" ' + '--status "Enabled" ' + '--friendly-name "HelloName" ' + '--hbi-workspace false ' + '--key-vault "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/Microsoft.KeyVault/vaults/tes' + 'tkv" ' + '--shared-private-link-resources name="testdbresource" private-link-resource-id="/subscriptions/{subscript' + 'ion_id}/resourceGroups/{rg}/providers/Microsoft.DocumentDB/databaseAccounts/testdbresource/privateLinkRes' + 'ources/{myPrivateLinkResource}" group-id="{myPrivateLinkResource}" request-message="Please approve" ' + 'status="Approved" ' + '--storage-account "/subscriptions/{subscription_id}/resourceGroups/{rg_2}/providers/Microsoft.Storage/sto' + 'rageAccounts/{sa}" ' + '--sku name="Basic" tier="Basic" ' + '--resource-group "{rg}" ' + '--name "{myWorkspace}"', + checks=[]) + test.cmd('az machinelearningservices workspace wait --created ' + '--resource-group "{rg}" ' + '--name "{myWorkspace}"', + checks=checks) + + +# EXAMPLE: /Workspaces/get/Get Workspace +@try_manual +def step_workspace_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace show ' + '--resource-group "{rg}" ' + '--name "{myWorkspace}"', + checks=checks) + + +# EXAMPLE: /Workspaces/get/Get Workspaces by Resource Group +@try_manual +def step_workspace_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace list ' + '--resource-group "{rg}"', + checks=checks) + + +# EXAMPLE: /Workspaces/get/Get Workspaces by subscription +@try_manual +def step_workspace_list2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace list ' + '-g ""', + checks=checks) + + +# EXAMPLE: /Workspaces/patch/Update Workspace +@try_manual +def step_workspace_update(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace update ' + '--description "new description" ' + '--friendly-name "New friendly name" ' + '--sku name="Enterprise" tier="Enterprise" ' + '--resource-group "{rg}" ' + '--name "{myWorkspace}"', + checks=checks) + + +# EXAMPLE: /Workspaces/post/List Workspace Keys +@try_manual +def step_workspace_list_key(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace list-key ' + '--resource-group "{rg_3}" ' + '--name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /Workspaces/post/Resync Workspace Keys +@try_manual +def step_workspace_resync_key(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace resync-key ' + '--resource-group "{rg_3}" ' + '--name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/put/Create a AML Compute +@try_manual +def step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute aks create ' + '--compute-name "compute123" ' + '--type "SystemAssigned,UserAssigned" ' + '--user-assigned-identities "{{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myRes' + 'ourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{{}}}}" ' + '--location "eastus" ' + '--ak-s-properties "{{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\":{{\\"maxNod' + 'eCount\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"}},\\"vmPriority\\":\\"Dedic' + 'ated\\",\\"vmSize\\":\\"STANDARD_NC6\\"}}" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/put/Create a ComputeInstance Compute +@try_manual +def step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute aks create ' + '--compute-name "compute123" ' + '--location "eastus" ' + '--ak-s-properties "{{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{{\\"sshPublicAccess' + '\\":\\"Disabled\\"}},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}}" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/put/Create a ComputeInstance Compute with minimal inputs +@try_manual +def step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute aks create ' + '--compute-name "compute123" ' + '--location "eastus" ' + '--ak-s-properties "{{\\"vmSize\\":\\"STANDARD_NC6\\"}}" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/put/Create a DataFactory Compute +@try_manual +def step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute aks create ' + '--compute-name "compute123" ' + '--location "eastus" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/put/Create AKS Compute +@try_manual +def step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + return step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks) + + +# EXAMPLE: /MachineLearningCompute/get/Get a AKS Compute +@try_manual +def step_machine_learning_compute_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute show ' + '--compute-name "compute123" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/get/Get a AML Compute +@try_manual +def step_machine_learning_compute_show2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + return step_machine_learning_compute_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks) + + +# EXAMPLE: /MachineLearningCompute/get/Get a ComputeInstance +@try_manual +def step_machine_learning_compute_show3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + return step_machine_learning_compute_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks) + + +# EXAMPLE: /MachineLearningCompute/get/Get Computes +@try_manual +def step_machine_learning_compute_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute list ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/patch/Update a AmlCompute Compute +@try_manual +def step_machine_learning_compute_update(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute update ' + '--compute-name "compute123" ' + '--scale-settings max-node-count=4 min-node-count=4 node-idle-time-before-scale-down="PT5M" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/post/Get compute nodes information for a compute +@try_manual +def step_machine_learning_compute_list_node(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute list-node ' + '--compute-name "compute123" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/post/List AKS Compute Keys +@try_manual +def step_machine_learning_compute_list_key(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute list-key ' + '--compute-name "compute123" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/post/Restart ComputeInstance Compute +@try_manual +def step_machine_learning_compute_restart(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute restart ' + '--compute-name "compute123" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/post/Start ComputeInstance Compute +@try_manual +def step_machine_learning_compute_start(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute start ' + '--compute-name "compute123" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/post/Stop ComputeInstance Compute +@try_manual +def step_machine_learning_compute_stop(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute stop ' + '--compute-name "compute123" ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /MachineLearningCompute/delete/Delete Compute +@try_manual +def step_machine_learning_compute_delete(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices machine-learning-compute delete -y ' + '--compute-name "compute123" ' + '--resource-group "{rg_3}" ' + '--underlying-resource-action "Delete" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /machinelearningservices/get/List Skus +@try_manual +def step_list_sku(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices list-sku', + checks=checks) + + +# EXAMPLE: /Notebooks/post/Prepare Notebook +@try_manual +def step_notebook_prepare(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices notebook prepare ' + '--resource-group "{rg_3}" ' + '--workspace-name "{myWorkspace2}"', + checks=checks) + + +# EXAMPLE: /PrivateEndpointConnections/put/WorkspacePutPrivateEndpointConnection +@try_manual +def step_private_endpoint_connection_put(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices private-endpoint-connection put ' + '--name "{myPrivateEndpointConnection}" ' + '--private-link-service-connection-state description="Auto-Approved" status="Approved" ' + '--resource-group "{rg_7}" ' + '--workspace-name "{myWorkspace}"', + checks=checks) + + +# EXAMPLE: /PrivateEndpointConnections/get/WorkspaceGetPrivateEndpointConnection +@try_manual +def step_private_endpoint_connection_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices private-endpoint-connection show ' + '--name "{myPrivateEndpointConnection}" ' + '--resource-group "{rg_7}" ' + '--workspace-name "{myWorkspace}"', + checks=checks) + + +# EXAMPLE: /PrivateEndpointConnections/delete/WorkspaceDeletePrivateEndpointConnection +@try_manual +def step_private_endpoint_connection_delete(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices private-endpoint-connection delete -y ' + '--name "{myPrivateEndpointConnection}" ' + '--resource-group "{rg_7}" ' + '--workspace-name "{myWorkspace}"', + checks=checks) + + +# EXAMPLE: /PrivateLinkResources/get/WorkspaceListPrivateLinkResources +@try_manual +def step_private_link_resource_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices private-link-resource list ' + '--resource-group "{rg_7}" ' + '--workspace-name "{myWorkspace}"', + checks=checks) + + +# EXAMPLE: /Quotas/get/List workspace quotas by VMFamily +@try_manual +def step_quota_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices quota list ' + '--location "eastus"', + checks=checks) + + +# EXAMPLE: /Quotas/post/update quotas +@try_manual +def step_quota_update(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices quota update ' + '--location "eastus" ' + '--value type="Microsoft.MachineLearningServices/workspaces/dedicatedCores/quotas" ' + 'id="/subscriptions/{subscription_id}/resourceGroups/{rg_5}/providers/Microsoft.MachineLearningServices/wo' + 'rkspaces/{myWorkspace3}/quotas/{myQuota}" limit=100 unit="Count" ' + '--value type="Microsoft.MachineLearningServices/workspaces/dedicatedCores/quotas" ' + 'id="/subscriptions/{subscription_id}/resourceGroups/{rg_5}/providers/Microsoft.MachineLearningServices/wo' + 'rkspaces/{myWorkspace4}/quotas/{myQuota}" limit=200 unit="Count"', + checks=checks) + + +# EXAMPLE: /Usages/get/List Usages +@try_manual +def step_usage_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices usage list ' + '--location "eastus"', + checks=checks) + + +# EXAMPLE: /VirtualMachineSizes/get/List VM Sizes +@try_manual +def step_virtual_machine_size_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices virtual-machine-size list ' + '--location "eastus" ' + '--recommended false', + checks=checks) + + +# EXAMPLE: /WorkspaceConnections/put/CreateWorkspaceConnection +@try_manual +def step_workspace_connection_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace-connection create ' + '--connection-name "{myMachinelearningservice}" ' + '--name "{myMachinelearningservice}" ' + '--auth-type "PAT" ' + '--category "ACR" ' + '--target "www.facebook.com" ' + '--value "secrets" ' + '--resource-group "{rg_6}" ' + '--workspace-name "{myWorkspace5}"', + checks=checks) + + +# EXAMPLE: /WorkspaceConnections/get/GetWorkspaceConnection +@try_manual +def step_workspace_connection_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace-connection show ' + '--connection-name "{myMachinelearningservice}" ' + '--resource-group "{rg_6}" ' + '--workspace-name "{myWorkspace5}"', + checks=checks) + + +# EXAMPLE: /WorkspaceConnections/get/ListWorkspaceConnections +@try_manual +def step_workspace_connection_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace-connection list ' + '--category "ACR" ' + '--resource-group "{rg_6}" ' + '--target "www.facebook.com" ' + '--workspace-name "{myWorkspace5}"', + checks=checks) + + +# EXAMPLE: /WorkspaceConnections/delete/DeleteWorkspaceConnection +@try_manual +def step_workspace_connection_delete(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace-connection delete -y ' + '--connection-name "{myMachinelearningservice}" ' + '--resource-group "{rg_6}" ' + '--workspace-name "{myWorkspace5}"', + checks=checks) + + +# EXAMPLE: /WorkspaceFeatures/get/List Workspace features +@try_manual +def step_workspace_feature_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace-feature list ' + '--resource-group "{rg_4}" ' + '--workspace-name "{myWorkspace}"', + checks=checks) + + +# EXAMPLE: /Workspaces/delete/Delete Workspace +@try_manual +def step_workspace_delete(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=None): + if checks is None: + checks = [] + test.cmd('az machinelearningservices workspace delete -y ' + '--resource-group "{rg}" ' + '--name "{myWorkspace}"', + checks=checks) + diff --git a/src/machinelearningservices/azext_machinelearningservices/tests/latest/test_machinelearningservices_scenario.py b/src/machinelearningservices/azext_machinelearningservices/tests/latest/test_machinelearningservices_scenario.py new file mode 100644 index 00000000000..1d8a3563c01 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/tests/latest/test_machinelearningservices_scenario.py @@ -0,0 +1,264 @@ +# -------------------------------------------------------------------------- +# 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. +# -------------------------------------------------------------------------- + +import os +from azure.cli.testsdk import ScenarioTest +from azure.cli.testsdk import ResourceGroupPreparer +from azure.cli.testsdk import StorageAccountPreparer +from .example_steps import step_workspace_create +from .example_steps import step_workspace_show +from .example_steps import step_workspace_list +from .example_steps import step_workspace_list2 +from .example_steps import step_workspace_update +from .example_steps import step_workspace_list_key +from .example_steps import step_workspace_resync_key +from .example_steps import step_machine_learning_compute_aks_create +from .example_steps import step_machine_learning_compute_aks_create2 +from .example_steps import step_machine_learning_compute_aks_create3 +from .example_steps import step_machine_learning_compute_aks_create4 +from .example_steps import step_machine_learning_compute_aks_create5 +from .example_steps import step_machine_learning_compute_show +from .example_steps import step_machine_learning_compute_show2 +from .example_steps import step_machine_learning_compute_show3 +from .example_steps import step_machine_learning_compute_list +from .example_steps import step_machine_learning_compute_update +from .example_steps import step_machine_learning_compute_list_node +from .example_steps import step_machine_learning_compute_list_key +from .example_steps import step_machine_learning_compute_restart +from .example_steps import step_machine_learning_compute_start +from .example_steps import step_machine_learning_compute_stop +from .example_steps import step_machine_learning_compute_delete +from .example_steps import step_list_sku +from .example_steps import step_notebook_prepare +from .example_steps import step_private_endpoint_connection_put +from .example_steps import step_private_endpoint_connection_show +from .example_steps import step_private_endpoint_connection_delete +from .example_steps import step_private_link_resource_list +from .example_steps import step_quota_list +from .example_steps import step_quota_update +from .example_steps import step_usage_list +from .example_steps import step_virtual_machine_size_list +from .example_steps import step_workspace_connection_create +from .example_steps import step_workspace_connection_show +from .example_steps import step_workspace_connection_list +from .example_steps import step_workspace_connection_delete +from .example_steps import step_workspace_feature_list +from .example_steps import step_workspace_delete +from .. import ( + try_manual, + raise_if, + calc_coverage +) + + +TEST_DIR = os.path.abspath(os.path.join(os.path.abspath(__file__), '..')) + + +# Env setup_scenario +@try_manual +def setup_scenario(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7): + pass + + +# Env cleanup_scenario +@try_manual +def cleanup_scenario(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7): + pass + + +# Testcase: Scenario +@try_manual +def call_scenario(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7): + setup_scenario(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7) + step_workspace_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[ + test.check("location", "eastus2euap", case_sensitive=False), + test.check("description", "test description", case_sensitive=False), + test.check("applicationInsights", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/microsoft.ins" + "ights/components/testinsights", case_sensitive=False), + test.check("containerRegistry", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/Microsoft.Conta" + "inerRegistry/registries/testRegistry", case_sensitive=False), + test.check("encryption.keyVaultProperties.identityClientId", "", case_sensitive=False), + test.check("encryption.keyVaultProperties.keyIdentifier", "https://testkv.vault.azure.net/keys/testkey/aabbccdd" + "ee112233445566778899aabb", case_sensitive=False), + test.check("encryption.keyVaultProperties.keyVaultArmId", "/subscriptions/{subscription_id}/resourceGroups/{rg}" + "/providers/Microsoft.KeyVault/vaults/testkv", case_sensitive=False), + test.check("encryption.status", "Enabled", case_sensitive=False), + test.check("friendlyName", "HelloName", case_sensitive=False), + test.check("hbiWorkspace", False), + test.check("keyVault", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/Microsoft.KeyVault/vault" + "s/testkv", case_sensitive=False), + test.check("storageAccount", "/subscriptions/{subscription_id}/resourceGroups/{rg_2}/providers/Microsoft.Storag" + "e/storageAccounts/{sa}", case_sensitive=False), + test.check("sku.name", "Basic", case_sensitive=False), + test.check("sku.tier", "Basic", case_sensitive=False), + test.check("name", "{myWorkspace}", case_sensitive=False), + ]) + step_workspace_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[ + test.check("location", "eastus2euap", case_sensitive=False), + test.check("description", "test description", case_sensitive=False), + test.check("applicationInsights", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/microsoft.ins" + "ights/components/testinsights", case_sensitive=False), + test.check("containerRegistry", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/Microsoft.Conta" + "inerRegistry/registries/testRegistry", case_sensitive=False), + test.check("encryption.keyVaultProperties.identityClientId", "", case_sensitive=False), + test.check("encryption.keyVaultProperties.keyIdentifier", "https://testkv.vault.azure.net/keys/testkey/aabbccdd" + "ee112233445566778899aabb", case_sensitive=False), + test.check("encryption.keyVaultProperties.keyVaultArmId", "/subscriptions/{subscription_id}/resourceGroups/{rg}" + "/providers/Microsoft.KeyVault/vaults/testkv", case_sensitive=False), + test.check("encryption.status", "Enabled", case_sensitive=False), + test.check("friendlyName", "HelloName", case_sensitive=False), + test.check("hbiWorkspace", False), + test.check("keyVault", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/Microsoft.KeyVault/vault" + "s/testkv", case_sensitive=False), + test.check("storageAccount", "/subscriptions/{subscription_id}/resourceGroups/{rg_2}/providers/Microsoft.Storag" + "e/storageAccounts/{sa}", case_sensitive=False), + test.check("name", "{myWorkspace}", case_sensitive=False), + ]) + step_workspace_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[ + test.check('length(@)', 1), + ]) + step_workspace_list2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[ + test.check('length(@)', 2), + ]) + step_workspace_update(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[ + test.check("location", "eastus2euap", case_sensitive=False), + test.check("description", "new description", case_sensitive=False), + test.check("applicationInsights", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/microsoft.ins" + "ights/components/testinsights", case_sensitive=False), + test.check("containerRegistry", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/Microsoft.Conta" + "inerRegistry/registries/testRegistry", case_sensitive=False), + test.check("friendlyName", "New friendly name", case_sensitive=False), + test.check("keyVault", "/subscriptions/{subscription_id}/resourceGroups/{rg}/providers/Microsoft.KeyVault/vault" + "s/testkv", case_sensitive=False), + test.check("storageAccount", "/subscriptions/{subscription_id}/resourceGroups/{rg_2}/providers/Microsoft.Storag" + "e/storageAccounts/{sa}", case_sensitive=False), + test.check("sku.name", "Enterprise", case_sensitive=False), + test.check("sku.tier", "Enterprise", case_sensitive=False), + test.check("name", "{myWorkspace}", case_sensitive=False), + ]) + step_workspace_list_key(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_workspace_resync_key(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create4(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_aks_create5(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_show2(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_show3(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_update(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_list_node(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_list_key(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_restart(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_start(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_stop(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_machine_learning_compute_delete(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_list_sku(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_notebook_prepare(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_private_endpoint_connection_put(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_private_endpoint_connection_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[ + test.check("name", "{myPrivateEndpointConnection}", case_sensitive=False), + ]) + step_private_endpoint_connection_delete(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_private_link_resource_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_quota_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_quota_update(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_usage_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_virtual_machine_size_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_workspace_connection_create(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_workspace_connection_show(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_workspace_connection_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_workspace_connection_delete(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_workspace_feature_list(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + step_workspace_delete(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7, checks=[]) + cleanup_scenario(test, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7) + + +# Test class for Scenario +@try_manual +class MachinelearningservicesScenarioTest(ScenarioTest): + + def __init__(self, *args, **kwargs): + super(MachinelearningservicesScenarioTest, self).__init__(*args, **kwargs) + self.kwargs.update({ + 'subscription_id': self.get_subscription_id() + }) + + self.kwargs.update({ + 'myMachinelearningservice': 'connection-1', + 'myWorkspace6': 'default', + 'myPrivateLinkResource2': 'default', + 'myWorkspace3': 'demo_workspace1', + 'myWorkspace4': 'demo_workspace2', + 'myWorkspace': 'testworkspace', + 'myWorkspace2': 'workspaces123', + 'myWorkspace5': 'workspace-1', + 'myQuota': 'StandardDSv2Family', + 'myPrivateEndpointConnection': '{privateEndpointConnectionName}', + 'myPrivateLinkResource': 'Sql', + }) + + + @ResourceGroupPreparer(name_prefix='clitestmachinelearningservices_workspace-1234'[:7], key='rg', + parameter_name='rg') + @ResourceGroupPreparer(name_prefix='clitestmachinelearningservices_accountcrud-1234'[:7], key='rg_2', + parameter_name='rg_2') + @ResourceGroupPreparer(name_prefix='clitestmachinelearningservices_rg'[:7], key='rg_5', parameter_name='rg_5') + @ResourceGroupPreparer(name_prefix='clitestmachinelearningservices_testrg123'[:7], key='rg_3', + parameter_name='rg_3') + @ResourceGroupPreparer(name_prefix='clitestmachinelearningservices_myResourceGroup'[:7], key='rg_4', + parameter_name='rg_4') + @ResourceGroupPreparer(name_prefix='clitestmachinelearningservices_resourceGroup-1'[:7], key='rg_6', + parameter_name='rg_6') + @ResourceGroupPreparer(name_prefix='clitestmachinelearningservices_rg-1234'[:7], key='rg_7', + parameter_name='rg_7') + @StorageAccountPreparer(name_prefix='clitestmachinelearningservices_testStorageAccount'[:7], key='sa', + resource_group_parameter_name='rg_2') + def test_machinelearningservices_Scenario(self, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7): + call_scenario(self, rg, rg_2, rg_5, rg_3, rg_4, rg_6, rg_7) + calc_coverage(__file__) + raise_if() + diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/__init__.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/__init__.py new file mode 100644 index 00000000000..c9cfdc73e77 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/__init__.py @@ -0,0 +1,12 @@ +# 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. +# -------------------------------------------------------------------------- + +__path__ = __import__('pkgutil').extend_path(__path__, __name__) diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/__init__.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/__init__.py new file mode 100644 index 00000000000..dad2c6eeb01 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/__init__.py @@ -0,0 +1,16 @@ +# 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_machine_learning_workspaces import AzureMachineLearningWorkspaces +__all__ = ['AzureMachineLearningWorkspaces'] + +try: + from ._patch import patch_sdk # type: ignore + patch_sdk() +except ImportError: + pass diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/_azure_machine_learning_workspaces.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/_azure_machine_learning_workspaces.py new file mode 100644 index 00000000000..873682820bf --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/_azure_machine_learning_workspaces.py @@ -0,0 +1,120 @@ +# 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 TYPE_CHECKING + +from azure.mgmt.core import ARMPipelineClient +from msrest import Deserializer, Serializer + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Optional + + from azure.core.credentials import TokenCredential + +from ._configuration import AzureMachineLearningWorkspacesConfiguration +from .operations import Operations +from .operations import WorkspacesOperations +from .operations import WorkspaceFeaturesOperations +from .operations import NotebooksOperations +from .operations import UsagesOperations +from .operations import VirtualMachineSizesOperations +from .operations import QuotasOperations +from .operations import WorkspaceConnectionsOperations +from .operations import MachineLearningComputeOperations +from .operations import AzureMachineLearningWorkspacesOperationsMixin +from .operations import PrivateEndpointConnectionsOperations +from .operations import PrivateLinkResourcesOperations +from . import models + + +class AzureMachineLearningWorkspaces(AzureMachineLearningWorkspacesOperationsMixin): + """These APIs allow end users to operate on Azure Machine Learning Workspace resources. + + :ivar operations: Operations operations + :vartype operations: azure_machine_learning_workspaces.operations.Operations + :ivar workspaces: WorkspacesOperations operations + :vartype workspaces: azure_machine_learning_workspaces.operations.WorkspacesOperations + :ivar workspace_features: WorkspaceFeaturesOperations operations + :vartype workspace_features: azure_machine_learning_workspaces.operations.WorkspaceFeaturesOperations + :ivar notebooks: NotebooksOperations operations + :vartype notebooks: azure_machine_learning_workspaces.operations.NotebooksOperations + :ivar usages: UsagesOperations operations + :vartype usages: azure_machine_learning_workspaces.operations.UsagesOperations + :ivar virtual_machine_sizes: VirtualMachineSizesOperations operations + :vartype virtual_machine_sizes: azure_machine_learning_workspaces.operations.VirtualMachineSizesOperations + :ivar quotas: QuotasOperations operations + :vartype quotas: azure_machine_learning_workspaces.operations.QuotasOperations + :ivar workspace_connections: WorkspaceConnectionsOperations operations + :vartype workspace_connections: azure_machine_learning_workspaces.operations.WorkspaceConnectionsOperations + :ivar machine_learning_compute: MachineLearningComputeOperations operations + :vartype machine_learning_compute: azure_machine_learning_workspaces.operations.MachineLearningComputeOperations + :ivar private_endpoint_connections: PrivateEndpointConnectionsOperations operations + :vartype private_endpoint_connections: azure_machine_learning_workspaces.operations.PrivateEndpointConnectionsOperations + :ivar private_link_resources: PrivateLinkResourcesOperations operations + :vartype private_link_resources: azure_machine_learning_workspaces.operations.PrivateLinkResourcesOperations + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials.TokenCredential + :param subscription_id: Azure subscription identifier. + :type subscription_id: str + :param str base_url: Service URL + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + """ + + def __init__( + self, + credential, # type: "TokenCredential" + subscription_id, # type: str + base_url=None, # type: Optional[str] + **kwargs # type: Any + ): + # type: (...) -> None + if not base_url: + base_url = 'https://management.azure.com' + self._config = AzureMachineLearningWorkspacesConfiguration(credential, subscription_id, **kwargs) + self._client = 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) + self._deserialize = Deserializer(client_models) + + self.operations = Operations( + self._client, self._config, self._serialize, self._deserialize) + self.workspaces = WorkspacesOperations( + self._client, self._config, self._serialize, self._deserialize) + self.workspace_features = WorkspaceFeaturesOperations( + self._client, self._config, self._serialize, self._deserialize) + self.notebooks = NotebooksOperations( + self._client, self._config, self._serialize, self._deserialize) + self.usages = UsagesOperations( + self._client, self._config, self._serialize, self._deserialize) + self.virtual_machine_sizes = VirtualMachineSizesOperations( + self._client, self._config, self._serialize, self._deserialize) + self.quotas = QuotasOperations( + self._client, self._config, self._serialize, self._deserialize) + self.workspace_connections = WorkspaceConnectionsOperations( + self._client, self._config, self._serialize, self._deserialize) + self.machine_learning_compute = MachineLearningComputeOperations( + self._client, self._config, self._serialize, self._deserialize) + self.private_endpoint_connections = PrivateEndpointConnectionsOperations( + self._client, self._config, self._serialize, self._deserialize) + self.private_link_resources = PrivateLinkResourcesOperations( + self._client, self._config, self._serialize, self._deserialize) + + def close(self): + # type: () -> None + self._client.close() + + def __enter__(self): + # type: () -> AzureMachineLearningWorkspaces + self._client.__enter__() + return self + + def __exit__(self, *exc_details): + # type: (Any) -> None + self._client.__exit__(*exc_details) diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/_configuration.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/_configuration.py new file mode 100644 index 00000000000..0d9620bc63b --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/_configuration.py @@ -0,0 +1,70 @@ +# 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 TYPE_CHECKING + +from azure.core.configuration import Configuration +from azure.core.pipeline import policies +from azure.mgmt.core.policies import ARMHttpLoggingPolicy + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any + + from azure.core.credentials import TokenCredential + +VERSION = "unknown" + +class AzureMachineLearningWorkspacesConfiguration(Configuration): + """Configuration for AzureMachineLearningWorkspaces. + + Note that all parameters used to create this instance are saved as instance + attributes. + + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials.TokenCredential + :param subscription_id: Azure subscription identifier. + :type subscription_id: str + """ + + def __init__( + self, + credential, # type: "TokenCredential" + subscription_id, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + if credential is None: + raise ValueError("Parameter 'credential' must not be None.") + if subscription_id is None: + raise ValueError("Parameter 'subscription_id' must not be None.") + super(AzureMachineLearningWorkspacesConfiguration, self).__init__(**kwargs) + + self.credential = credential + self.subscription_id = subscription_id + self.api_version = "2020-08-01" + self.credential_scopes = kwargs.pop('credential_scopes', ['https://management.azure.com/.default']) + kwargs.setdefault('sdk_moniker', 'azuremachinelearningworkspaces/{}'.format(VERSION)) + self._configure(**kwargs) + + def _configure( + self, + **kwargs # type: Any + ): + # type: (...) -> None + self.user_agent_policy = kwargs.get('user_agent_policy') or policies.UserAgentPolicy(**kwargs) + self.headers_policy = kwargs.get('headers_policy') or policies.HeadersPolicy(**kwargs) + self.proxy_policy = kwargs.get('proxy_policy') or policies.ProxyPolicy(**kwargs) + self.logging_policy = kwargs.get('logging_policy') or policies.NetworkTraceLoggingPolicy(**kwargs) + self.http_logging_policy = kwargs.get('http_logging_policy') or ARMHttpLoggingPolicy(**kwargs) + self.retry_policy = kwargs.get('retry_policy') or policies.RetryPolicy(**kwargs) + self.custom_hook_policy = kwargs.get('custom_hook_policy') or policies.CustomHookPolicy(**kwargs) + self.redirect_policy = kwargs.get('redirect_policy') or policies.RedirectPolicy(**kwargs) + self.authentication_policy = kwargs.get('authentication_policy') + if self.credential and not self.authentication_policy: + self.authentication_policy = policies.BearerTokenCredentialPolicy(self.credential, *self.credential_scopes, **kwargs) diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/__init__.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/__init__.py new file mode 100644 index 00000000000..872474577c4 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/__init__.py @@ -0,0 +1,10 @@ +# 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_machine_learning_workspaces import AzureMachineLearningWorkspaces +__all__ = ['AzureMachineLearningWorkspaces'] diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/_azure_machine_learning_workspaces.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/_azure_machine_learning_workspaces.py new file mode 100644 index 00000000000..20e6e369512 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/_azure_machine_learning_workspaces.py @@ -0,0 +1,114 @@ +# 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, Optional, TYPE_CHECKING + +from azure.mgmt.core import AsyncARMPipelineClient +from msrest import Deserializer, Serializer + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from azure.core.credentials_async import AsyncTokenCredential + +from ._configuration import AzureMachineLearningWorkspacesConfiguration +from .operations import Operations +from .operations import WorkspacesOperations +from .operations import WorkspaceFeaturesOperations +from .operations import NotebooksOperations +from .operations import UsagesOperations +from .operations import VirtualMachineSizesOperations +from .operations import QuotasOperations +from .operations import WorkspaceConnectionsOperations +from .operations import MachineLearningComputeOperations +from .operations import AzureMachineLearningWorkspacesOperationsMixin +from .operations import PrivateEndpointConnectionsOperations +from .operations import PrivateLinkResourcesOperations +from .. import models + + +class AzureMachineLearningWorkspaces(AzureMachineLearningWorkspacesOperationsMixin): + """These APIs allow end users to operate on Azure Machine Learning Workspace resources. + + :ivar operations: Operations operations + :vartype operations: azure_machine_learning_workspaces.aio.operations.Operations + :ivar workspaces: WorkspacesOperations operations + :vartype workspaces: azure_machine_learning_workspaces.aio.operations.WorkspacesOperations + :ivar workspace_features: WorkspaceFeaturesOperations operations + :vartype workspace_features: azure_machine_learning_workspaces.aio.operations.WorkspaceFeaturesOperations + :ivar notebooks: NotebooksOperations operations + :vartype notebooks: azure_machine_learning_workspaces.aio.operations.NotebooksOperations + :ivar usages: UsagesOperations operations + :vartype usages: azure_machine_learning_workspaces.aio.operations.UsagesOperations + :ivar virtual_machine_sizes: VirtualMachineSizesOperations operations + :vartype virtual_machine_sizes: azure_machine_learning_workspaces.aio.operations.VirtualMachineSizesOperations + :ivar quotas: QuotasOperations operations + :vartype quotas: azure_machine_learning_workspaces.aio.operations.QuotasOperations + :ivar workspace_connections: WorkspaceConnectionsOperations operations + :vartype workspace_connections: azure_machine_learning_workspaces.aio.operations.WorkspaceConnectionsOperations + :ivar machine_learning_compute: MachineLearningComputeOperations operations + :vartype machine_learning_compute: azure_machine_learning_workspaces.aio.operations.MachineLearningComputeOperations + :ivar private_endpoint_connections: PrivateEndpointConnectionsOperations operations + :vartype private_endpoint_connections: azure_machine_learning_workspaces.aio.operations.PrivateEndpointConnectionsOperations + :ivar private_link_resources: PrivateLinkResourcesOperations operations + :vartype private_link_resources: azure_machine_learning_workspaces.aio.operations.PrivateLinkResourcesOperations + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials_async.AsyncTokenCredential + :param subscription_id: Azure subscription identifier. + :type subscription_id: str + :param str base_url: Service URL + :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. + """ + + def __init__( + self, + credential: "AsyncTokenCredential", + subscription_id: str, + base_url: Optional[str] = None, + **kwargs: Any + ) -> None: + if not base_url: + base_url = 'https://management.azure.com' + self._config = AzureMachineLearningWorkspacesConfiguration(credential, subscription_id, **kwargs) + self._client = 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) + self._deserialize = Deserializer(client_models) + + self.operations = Operations( + self._client, self._config, self._serialize, self._deserialize) + self.workspaces = WorkspacesOperations( + self._client, self._config, self._serialize, self._deserialize) + self.workspace_features = WorkspaceFeaturesOperations( + self._client, self._config, self._serialize, self._deserialize) + self.notebooks = NotebooksOperations( + self._client, self._config, self._serialize, self._deserialize) + self.usages = UsagesOperations( + self._client, self._config, self._serialize, self._deserialize) + self.virtual_machine_sizes = VirtualMachineSizesOperations( + self._client, self._config, self._serialize, self._deserialize) + self.quotas = QuotasOperations( + self._client, self._config, self._serialize, self._deserialize) + self.workspace_connections = WorkspaceConnectionsOperations( + self._client, self._config, self._serialize, self._deserialize) + self.machine_learning_compute = MachineLearningComputeOperations( + self._client, self._config, self._serialize, self._deserialize) + self.private_endpoint_connections = PrivateEndpointConnectionsOperations( + self._client, self._config, self._serialize, self._deserialize) + self.private_link_resources = PrivateLinkResourcesOperations( + self._client, self._config, self._serialize, self._deserialize) + + async def close(self) -> None: + await self._client.close() + + async def __aenter__(self) -> "AzureMachineLearningWorkspaces": + await self._client.__aenter__() + return self + + async def __aexit__(self, *exc_details) -> None: + await self._client.__aexit__(*exc_details) diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/_configuration.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/_configuration.py new file mode 100644 index 00000000000..673297675a4 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/_configuration.py @@ -0,0 +1,66 @@ +# 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, TYPE_CHECKING + +from azure.core.configuration import Configuration +from azure.core.pipeline import policies +from azure.mgmt.core.policies import ARMHttpLoggingPolicy + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from azure.core.credentials_async import AsyncTokenCredential + +VERSION = "unknown" + +class AzureMachineLearningWorkspacesConfiguration(Configuration): + """Configuration for AzureMachineLearningWorkspaces. + + Note that all parameters used to create this instance are saved as instance + attributes. + + :param credential: Credential needed for the client to connect to Azure. + :type credential: ~azure.core.credentials_async.AsyncTokenCredential + :param subscription_id: Azure subscription identifier. + :type subscription_id: str + """ + + def __init__( + self, + credential: "AsyncTokenCredential", + subscription_id: str, + **kwargs: Any + ) -> None: + if credential is None: + raise ValueError("Parameter 'credential' must not be None.") + if subscription_id is None: + raise ValueError("Parameter 'subscription_id' must not be None.") + super(AzureMachineLearningWorkspacesConfiguration, self).__init__(**kwargs) + + self.credential = credential + self.subscription_id = subscription_id + self.api_version = "2020-08-01" + self.credential_scopes = kwargs.pop('credential_scopes', ['https://management.azure.com/.default']) + kwargs.setdefault('sdk_moniker', 'azuremachinelearningworkspaces/{}'.format(VERSION)) + self._configure(**kwargs) + + def _configure( + self, + **kwargs: Any + ) -> None: + self.user_agent_policy = kwargs.get('user_agent_policy') or policies.UserAgentPolicy(**kwargs) + self.headers_policy = kwargs.get('headers_policy') or policies.HeadersPolicy(**kwargs) + self.proxy_policy = kwargs.get('proxy_policy') or policies.ProxyPolicy(**kwargs) + self.logging_policy = kwargs.get('logging_policy') or policies.NetworkTraceLoggingPolicy(**kwargs) + self.http_logging_policy = kwargs.get('http_logging_policy') or ARMHttpLoggingPolicy(**kwargs) + self.retry_policy = kwargs.get('retry_policy') or policies.AsyncRetryPolicy(**kwargs) + self.custom_hook_policy = kwargs.get('custom_hook_policy') or policies.CustomHookPolicy(**kwargs) + self.redirect_policy = kwargs.get('redirect_policy') or policies.AsyncRedirectPolicy(**kwargs) + self.authentication_policy = kwargs.get('authentication_policy') + if self.credential and not self.authentication_policy: + self.authentication_policy = policies.AsyncBearerTokenCredentialPolicy(self.credential, *self.credential_scopes, **kwargs) diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/__init__.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/__init__.py new file mode 100644 index 00000000000..516999b100d --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/__init__.py @@ -0,0 +1,35 @@ +# 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 ._operations import Operations +from ._workspaces_operations import WorkspacesOperations +from ._workspace_features_operations import WorkspaceFeaturesOperations +from ._notebooks_operations import NotebooksOperations +from ._usages_operations import UsagesOperations +from ._virtual_machine_sizes_operations import VirtualMachineSizesOperations +from ._quotas_operations import QuotasOperations +from ._workspace_connections_operations import WorkspaceConnectionsOperations +from ._machine_learning_compute_operations import MachineLearningComputeOperations +from ._azure_machine_learning_workspaces_operations import AzureMachineLearningWorkspacesOperationsMixin +from ._private_endpoint_connections_operations import PrivateEndpointConnectionsOperations +from ._private_link_resources_operations import PrivateLinkResourcesOperations + +__all__ = [ + 'Operations', + 'WorkspacesOperations', + 'WorkspaceFeaturesOperations', + 'NotebooksOperations', + 'UsagesOperations', + 'VirtualMachineSizesOperations', + 'QuotasOperations', + 'WorkspaceConnectionsOperations', + 'MachineLearningComputeOperations', + 'AzureMachineLearningWorkspacesOperationsMixin', + 'PrivateEndpointConnectionsOperations', + 'PrivateLinkResourcesOperations', +] diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_azure_machine_learning_workspaces_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_azure_machine_learning_workspaces_operations.py new file mode 100644 index 00000000000..8cf57106b6f --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_azure_machine_learning_workspaces_operations.py @@ -0,0 +1,89 @@ +# 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, Generic, Optional, TypeVar +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class AzureMachineLearningWorkspacesOperationsMixin: + + def list_skus( + self, + **kwargs + ) -> AsyncIterable["models.SkuListResult"]: + """Lists all skus with associated features. + + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either SkuListResult or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.SkuListResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.SkuListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_skus.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('SkuListResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list_skus.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/workspaces/skus'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_machine_learning_compute_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_machine_learning_compute_operations.py new file mode 100644 index 00000000000..8cfe9577f3c --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_machine_learning_compute_operations.py @@ -0,0 +1,914 @@ +# 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, Generic, Optional, TypeVar, Union +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class MachineLearningComputeOperations: + """MachineLearningComputeOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list_by_workspace( + self, + resource_group_name: str, + workspace_name: str, + skiptoken: Optional[str] = None, + **kwargs + ) -> AsyncIterable["models.PaginatedComputeResourcesList"]: + """Gets computes in specified workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedComputeResourcesList or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.PaginatedComputeResourcesList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PaginatedComputeResourcesList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_workspace.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('PaginatedComputeResourcesList', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list_by_workspace.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes'} # type: ignore + + async def get( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + **kwargs + ) -> "models.ComputeResource": + """Gets compute definition by its name. Any secrets (storage keys, service credentials, etc) are + not returned - use 'keys' nested resource to get them. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: ComputeResource, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.ComputeResource + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + async def _create_or_update_initial( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + parameters: "models.ComputeResource", + **kwargs + ) -> "models.ComputeResource": + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self._create_or_update_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'ComputeResource') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + response_headers = {} + if response.status_code == 200: + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if response.status_code == 201: + response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation')) + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, response_headers) + + return deserialized + _create_or_update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + async def begin_create_or_update( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + parameters: "models.ComputeResource", + **kwargs + ) -> AsyncLROPoller["models.ComputeResource"]: + """Creates or updates compute. This call will overwrite a compute if it exists. This is a + nonrecoverable operation. If your intent is to create a new compute, do a GET first to verify + that it does not exist yet. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :param parameters: Payload with Machine Learning compute definition. + :type parameters: ~azure_machine_learning_workspaces.models.ComputeResource + :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: True for ARMPolling, False for no polling, or a + polling object for 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 ComputeResource or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[~azure_machine_learning_workspaces.models.ComputeResource] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._create_or_update_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + response_headers = {} + response = pipeline_response.http_response + response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation')) + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, response_headers) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + async def _update_initial( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + parameters: "models.ClusterUpdateParameters", + **kwargs + ) -> "models.ComputeResource": + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self._update_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'ClusterUpdateParameters') + body_content_kwargs['content'] = body_content + request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + _update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + async def begin_update( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + parameters: "models.ClusterUpdateParameters", + **kwargs + ) -> AsyncLROPoller["models.ComputeResource"]: + """Updates properties of a compute. This call will overwrite a compute if it exists. This is a + nonrecoverable operation. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :param parameters: Additional parameters for cluster update. + :type parameters: ~azure_machine_learning_workspaces.models.ClusterUpdateParameters + :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: True for ARMPolling, False for no polling, or a + polling object for 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 ComputeResource or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[~azure_machine_learning_workspaces.models.ComputeResource] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._update_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + async def _delete_initial( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + underlying_resource_action: Union[str, "models.UnderlyingResourceAction"], + **kwargs + ) -> None: + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self._delete_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + query_parameters['underlyingResourceAction'] = self._serialize.query("underlying_resource_action", underlying_resource_action, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + response_headers = {} + if response.status_code == 202: + response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation')) + response_headers['Location']=self._deserialize('str', response.headers.get('Location')) + + if cls: + return cls(pipeline_response, None, response_headers) + + _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + async def begin_delete( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + underlying_resource_action: Union[str, "models.UnderlyingResourceAction"], + **kwargs + ) -> AsyncLROPoller[None]: + """Deletes specified Machine Learning compute. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :param underlying_resource_action: Delete the underlying compute if 'Delete', or detach the + underlying compute from workspace if 'Detach'. + :type underlying_resource_action: str or ~azure_machine_learning_workspaces.models.UnderlyingResourceAction + :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: True for ARMPolling, False for no polling, or a + polling object for 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: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[None] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._delete_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + underlying_resource_action=underlying_resource_action, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + if cls: + return cls(pipeline_response, None, {}) + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + def list_nodes( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + **kwargs + ) -> AsyncIterable["models.AmlComputeNodesInformation"]: + """Get the details (e.g IP address, port etc) of all the compute nodes in the compute. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either AmlComputeNodesInformation or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.AmlComputeNodesInformation] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.AmlComputeNodesInformation"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_nodes.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('AmlComputeNodesInformation', pipeline_response) + list_of_elem = deserialized.nodes + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list_nodes.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listNodes'} # type: ignore + + async def list_keys( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + **kwargs + ) -> "models.ComputeSecrets": + """Gets secrets related to Machine Learning compute (storage keys, service credentials, etc). + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: ComputeSecrets, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.ComputeSecrets + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeSecrets"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.list_keys.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ComputeSecrets', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listKeys'} # type: ignore + + async def start( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + **kwargs + ) -> None: + """Posts a start action to a compute instance. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.start.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + start.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/start'} # type: ignore + + async def stop( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + **kwargs + ) -> None: + """Posts a stop action to a compute instance. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.stop.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + stop.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/stop'} # type: ignore + + async def restart( + self, + resource_group_name: str, + workspace_name: str, + compute_name: str, + **kwargs + ) -> None: + """Posts a restart action to a compute instance. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.restart.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + restart.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/restart'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_notebooks_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_notebooks_operations.py new file mode 100644 index 00000000000..23fffbd7e42 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_notebooks_operations.py @@ -0,0 +1,160 @@ +# 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, Generic, Optional, TypeVar, Union +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class NotebooksOperations: + """NotebooksOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + async def _prepare_initial( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> Optional["models.NotebookResourceInfo"]: + cls = kwargs.pop('cls', None) # type: ClsType[Optional["models.NotebookResourceInfo"]] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self._prepare_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('NotebookResourceInfo', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + _prepare_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/prepareNotebook'} # type: ignore + + async def begin_prepare( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> AsyncLROPoller["models.NotebookResourceInfo"]: + """prepare. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_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: True for ARMPolling, False for no polling, or a + polling object for 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 NotebookResourceInfo or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[~azure_machine_learning_workspaces.models.NotebookResourceInfo] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["models.NotebookResourceInfo"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._prepare_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('NotebookResourceInfo', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_prepare.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/prepareNotebook'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_operations.py new file mode 100644 index 00000000000..9bc5433b754 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_operations.py @@ -0,0 +1,105 @@ +# 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, Generic, Optional, TypeVar +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class Operations: + """Operations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + **kwargs + ) -> AsyncIterable["models.OperationListResult"]: + """Lists all of the available Azure Machine Learning Workspaces REST API operations. + + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either OperationListResult or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.OperationListResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.OperationListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('OperationListResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list.metadata = {'url': '/providers/Microsoft.MachineLearningServices/operations'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_private_endpoint_connections_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_private_endpoint_connections_operations.py new file mode 100644 index 00000000000..3423a76fc69 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_private_endpoint_connections_operations.py @@ -0,0 +1,296 @@ +# 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, Generic, Optional, TypeVar, Union +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class PrivateEndpointConnectionsOperations: + """PrivateEndpointConnectionsOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + async def get( + self, + resource_group_name: str, + workspace_name: str, + private_endpoint_connection_name: str, + **kwargs + ) -> "models.PrivateEndpointConnection": + """Gets the specified private endpoint connection associated with the workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param private_endpoint_connection_name: The name of the private endpoint connection associated + with the workspace. + :type private_endpoint_connection_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: PrivateEndpointConnection, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.PrivateEndpointConnection + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PrivateEndpointConnection"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'privateEndpointConnectionName': self._serialize.url("private_endpoint_connection_name", private_endpoint_connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('PrivateEndpointConnection', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateEndpointConnections/{privateEndpointConnectionName}'} # type: ignore + + async def put( + self, + resource_group_name: str, + workspace_name: str, + private_endpoint_connection_name: str, + properties: "models.PrivateEndpointConnection", + **kwargs + ) -> "models.PrivateEndpointConnection": + """Update the state of specified private endpoint connection associated with the workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param private_endpoint_connection_name: The name of the private endpoint connection associated + with the workspace. + :type private_endpoint_connection_name: str + :param properties: The private endpoint connection properties. + :type properties: ~azure_machine_learning_workspaces.models.PrivateEndpointConnection + :keyword callable cls: A custom type or function that will be passed the direct response + :return: PrivateEndpointConnection, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.PrivateEndpointConnection + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PrivateEndpointConnection"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.put.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'privateEndpointConnectionName': self._serialize.url("private_endpoint_connection_name", private_endpoint_connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(properties, 'PrivateEndpointConnection') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('PrivateEndpointConnection', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + put.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateEndpointConnections/{privateEndpointConnectionName}'} # type: ignore + + async def _delete_initial( + self, + resource_group_name: str, + workspace_name: str, + private_endpoint_connection_name: str, + **kwargs + ) -> None: + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self._delete_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'privateEndpointConnectionName': self._serialize.url("private_endpoint_connection_name", private_endpoint_connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateEndpointConnections/{privateEndpointConnectionName}'} # type: ignore + + async def begin_delete( + self, + resource_group_name: str, + workspace_name: str, + private_endpoint_connection_name: str, + **kwargs + ) -> AsyncLROPoller[None]: + """Deletes the specified private endpoint connection associated with the workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param private_endpoint_connection_name: The name of the private endpoint connection associated + with the workspace. + :type private_endpoint_connection_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: True for ARMPolling, False for no polling, or a + polling object for 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: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[None] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._delete_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + private_endpoint_connection_name=private_endpoint_connection_name, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + if cls: + return cls(pipeline_response, None, {}) + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'privateEndpointConnectionName': self._serialize.url("private_endpoint_connection_name", private_endpoint_connection_name, 'str'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateEndpointConnections/{privateEndpointConnectionName}'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_private_link_resources_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_private_link_resources_operations.py new file mode 100644 index 00000000000..e30fb5e0d1e --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_private_link_resources_operations.py @@ -0,0 +1,99 @@ +# 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, Generic, Optional, TypeVar +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class PrivateLinkResourcesOperations: + """PrivateLinkResourcesOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + async def list_by_workspace( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> "models.PrivateLinkResourceListResult": + """Gets the private link resources that need to be created for a workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: PrivateLinkResourceListResult, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.PrivateLinkResourceListResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PrivateLinkResourceListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.list_by_workspace.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('PrivateLinkResourceListResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_by_workspace.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateLinkResources'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_quotas_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_quotas_operations.py new file mode 100644 index 00000000000..aef9ebc99e3 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_quotas_operations.py @@ -0,0 +1,175 @@ +# 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, Generic, Optional, TypeVar +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class QuotasOperations: + """QuotasOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + async def update( + self, + location: str, + parameters: "models.QuotaUpdateParameters", + **kwargs + ) -> "models.UpdateWorkspaceQuotasResult": + """Update quota for each VM family in workspace. + + :param location: The location for update quota is queried. + :type location: str + :param parameters: Quota update parameters. + :type parameters: ~azure_machine_learning_workspaces.models.QuotaUpdateParameters + :keyword callable cls: A custom type or function that will be passed the direct response + :return: UpdateWorkspaceQuotasResult, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.UpdateWorkspaceQuotasResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.UpdateWorkspaceQuotasResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.update.metadata['url'] # type: ignore + path_format_arguments = { + 'location': self._serialize.url("location", location, 'str', pattern=r'^[-\w\._]+$'), + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'QuotaUpdateParameters') + body_content_kwargs['content'] = body_content + request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('UpdateWorkspaceQuotasResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + update.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/locations/{location}/updateQuotas'} # type: ignore + + def list( + self, + location: str, + **kwargs + ) -> AsyncIterable["models.ListWorkspaceQuotas"]: + """Gets the currently assigned Workspace Quotas based on VMFamily. + + :param location: The location for which resource usage is queried. + :type location: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either ListWorkspaceQuotas or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.ListWorkspaceQuotas] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ListWorkspaceQuotas"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'location': self._serialize.url("location", location, 'str', pattern=r'^[-\w\._]+$'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('ListWorkspaceQuotas', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **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) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/locations/{location}/Quotas'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_usages_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_usages_operations.py new file mode 100644 index 00000000000..89f5d0a6cf9 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_usages_operations.py @@ -0,0 +1,113 @@ +# 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, Generic, Optional, TypeVar +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class UsagesOperations: + """UsagesOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + location: str, + **kwargs + ) -> AsyncIterable["models.ListUsagesResult"]: + """Gets the current usage information as well as limits for AML resources for given subscription + and location. + + :param location: The location for which resource usage is queried. + :type location: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either ListUsagesResult or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.ListUsagesResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ListUsagesResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'location': self._serialize.url("location", location, 'str', pattern=r'^[-\w\._]+$'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('ListUsagesResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **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) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/locations/{location}/usages'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_virtual_machine_sizes_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_virtual_machine_sizes_operations.py new file mode 100644 index 00000000000..70fe284ac62 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_virtual_machine_sizes_operations.py @@ -0,0 +1,105 @@ +# 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, Generic, Optional, TypeVar +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class VirtualMachineSizesOperations: + """VirtualMachineSizesOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + async def list( + self, + location: str, + compute_type: Optional[str] = None, + recommended: Optional[bool] = None, + **kwargs + ) -> "models.VirtualMachineSizeListResult": + """Returns supported VM Sizes in a location. + + :param location: The location upon which virtual-machine-sizes is queried. + :type location: str + :param compute_type: Type of compute to filter by. + :type compute_type: str + :param recommended: Specifies whether to return recommended vm sizes or all vm sizes. + :type recommended: bool + :keyword callable cls: A custom type or function that will be passed the direct response + :return: VirtualMachineSizeListResult, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.VirtualMachineSizeListResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.VirtualMachineSizeListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'location': self._serialize.url("location", location, 'str', pattern=r'^[-\w\._]+$'), + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if compute_type is not None: + query_parameters['compute-type'] = self._serialize.query("compute_type", compute_type, 'str') + if recommended is not None: + query_parameters['recommended'] = self._serialize.query("recommended", recommended, 'bool') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('VirtualMachineSizeListResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/locations/{location}/vmSizes'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspace_connections_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspace_connections_operations.py new file mode 100644 index 00000000000..5259a75af47 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspace_connections_operations.py @@ -0,0 +1,321 @@ +# 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, Generic, Optional, TypeVar +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class WorkspaceConnectionsOperations: + """WorkspaceConnectionsOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + resource_group_name: str, + workspace_name: str, + target: Optional[str] = None, + category: Optional[str] = None, + **kwargs + ) -> AsyncIterable["models.PaginatedWorkspaceConnectionsList"]: + """List all connections under a AML workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param target: Target of the workspace connection. + :type target: str + :param category: Category of the workspace connection. + :type category: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedWorkspaceConnectionsList or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.PaginatedWorkspaceConnectionsList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PaginatedWorkspaceConnectionsList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if target is not None: + query_parameters['target'] = self._serialize.query("target", target, 'str') + if category is not None: + query_parameters['category'] = self._serialize.query("category", category, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('PaginatedWorkspaceConnectionsList', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + 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/workspaces/{workspaceName}/connections'} # type: ignore + + async def create( + self, + resource_group_name: str, + workspace_name: str, + connection_name: str, + parameters: "models.WorkspaceConnectionDto", + **kwargs + ) -> "models.WorkspaceConnection": + """Add a new workspace connection. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param connection_name: Friendly name of the workspace connection. + :type connection_name: str + :param parameters: The object for creating or updating a new workspace connection. + :type parameters: ~azure_machine_learning_workspaces.models.WorkspaceConnectionDto + :keyword callable cls: A custom type or function that will be passed the direct response + :return: WorkspaceConnection, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.WorkspaceConnection + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.WorkspaceConnection"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.create.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'connectionName': self._serialize.url("connection_name", connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'WorkspaceConnectionDto') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('WorkspaceConnection', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + create.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/connections/{connectionName}'} # type: ignore + + async def get( + self, + resource_group_name: str, + workspace_name: str, + connection_name: str, + **kwargs + ) -> "models.WorkspaceConnection": + """Get the detail of a workspace connection. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param connection_name: Friendly name of the workspace connection. + :type connection_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: WorkspaceConnection, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.WorkspaceConnection + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.WorkspaceConnection"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'connectionName': self._serialize.url("connection_name", connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('WorkspaceConnection', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/connections/{connectionName}'} # type: ignore + + async def delete( + self, + resource_group_name: str, + workspace_name: str, + connection_name: str, + **kwargs + ) -> None: + """Delete a workspace connection. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param connection_name: Friendly name of the workspace connection. + :type connection_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.delete.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'connectionName': self._serialize.url("connection_name", connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200, 204]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/connections/{connectionName}'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspace_features_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspace_features_operations.py new file mode 100644 index 00000000000..7ad08485073 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspace_features_operations.py @@ -0,0 +1,117 @@ +# 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, Generic, Optional, TypeVar +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.mgmt.core.exceptions import ARMErrorFormat + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class WorkspaceFeaturesOperations: + """WorkspaceFeaturesOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> AsyncIterable["models.ListAmlUserFeatureResult"]: + """Lists all enabled features for a workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either ListAmlUserFeatureResult or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.ListAmlUserFeatureResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ListAmlUserFeatureResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('ListAmlUserFeatureResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + 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/workspaces/{workspaceName}/features'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspaces_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspaces_operations.py new file mode 100644 index 00000000000..fc12e6d6231 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/aio/operations/_workspaces_operations.py @@ -0,0 +1,674 @@ +# 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, Generic, Optional, TypeVar, Union +import warnings + +from azure.core.async_paging import AsyncItemPaged, AsyncList +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest +from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling + +from ... import models + +T = TypeVar('T') +ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] + +class WorkspacesOperations: + """WorkspacesOperations async operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer) -> None: + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + async def get( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> "models.Workspace": + """Gets the properties of the specified machine learning workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Workspace, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.Workspace + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.Workspace"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Workspace', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + async def _create_or_update_initial( + self, + resource_group_name: str, + workspace_name: str, + parameters: "models.Workspace", + **kwargs + ) -> Optional["models.Workspace"]: + cls = kwargs.pop('cls', None) # type: ClsType[Optional["models.Workspace"]] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self._create_or_update_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'Workspace') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200, 201, 202]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('Workspace', pipeline_response) + + if response.status_code == 201: + deserialized = self._deserialize('Workspace', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + _create_or_update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + async def begin_create_or_update( + self, + resource_group_name: str, + workspace_name: str, + parameters: "models.Workspace", + **kwargs + ) -> AsyncLROPoller["models.Workspace"]: + """Creates or updates a workspace with the specified parameters. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param parameters: The parameters for creating or updating a machine learning workspace. + :type parameters: ~azure_machine_learning_workspaces.models.Workspace + :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: True for ARMPolling, False for no polling, or a + polling object for 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 Workspace or the result of cls(response) + :rtype: ~azure.core.polling.AsyncLROPoller[~azure_machine_learning_workspaces.models.Workspace] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["models.Workspace"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._create_or_update_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + parameters=parameters, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('Workspace', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + async def _delete_initial( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> None: + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self._delete_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + async def begin_delete( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> AsyncLROPoller[None]: + """Deletes a machine learning workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_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: True for ARMPolling, False for no polling, or a + polling object for 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: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[None] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = await self._delete_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + if cls: + return cls(pipeline_response, None, {}) + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + + if polling is True: polling_method = AsyncARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + async def update( + self, + resource_group_name: str, + workspace_name: str, + parameters: "models.WorkspaceUpdateParameters", + **kwargs + ) -> "models.Workspace": + """Updates a machine learning workspace with the specified parameters. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param parameters: The parameters for updating a machine learning workspace. + :type parameters: ~azure_machine_learning_workspaces.models.WorkspaceUpdateParameters + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Workspace, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.Workspace + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.Workspace"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.update.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'WorkspaceUpdateParameters') + body_content_kwargs['content'] = body_content + request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Workspace', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + def list_by_resource_group( + self, + resource_group_name: str, + skiptoken: Optional[str] = None, + **kwargs + ) -> AsyncIterable["models.WorkspaceListResult"]: + """Lists all the available machine learning workspaces under the specified resource group. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either WorkspaceListResult or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.WorkspaceListResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.WorkspaceListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_resource_group.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('WorkspaceListResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return AsyncItemPaged( + get_next, extract_data + ) + list_by_resource_group.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces'} # type: ignore + + async def list_keys( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> "models.ListWorkspaceKeysResult": + """Lists all the keys associated with this workspace. This includes keys for the storage account, + app insights and password for container registry. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: ListWorkspaceKeysResult, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.ListWorkspaceKeysResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ListWorkspaceKeysResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.list_keys.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ListWorkspaceKeysResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/listKeys'} # type: ignore + + async def resync_keys( + self, + resource_group_name: str, + workspace_name: str, + **kwargs + ) -> None: + """Resync all the keys associated with this workspace. This includes keys for the storage account, + app insights and password for container registry. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.resync_keys.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = await self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + resync_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/resyncKeys'} # type: ignore + + def list_by_subscription( + self, + skiptoken: Optional[str] = None, + **kwargs + ) -> AsyncIterable["models.WorkspaceListResult"]: + """Lists all the available machine learning workspaces under the specified subscription. + + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either WorkspaceListResult or the result of cls(response) + :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure_machine_learning_workspaces.models.WorkspaceListResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.WorkspaceListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_subscription.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + async def extract_data(pipeline_response): + deserialized = self._deserialize('WorkspaceListResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, AsyncList(list_of_elem) + + async def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + 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/workspaces'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/__init__.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/__init__.py new file mode 100644 index 00000000000..b5c03186f1b --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/__init__.py @@ -0,0 +1,355 @@ +# 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. +# -------------------------------------------------------------------------- + +try: + from ._models_py3 import Aks + from ._models_py3 import AksComputeSecrets + from ._models_py3 import AksNetworkingConfiguration + from ._models_py3 import AksProperties + from ._models_py3 import AmlCompute + from ._models_py3 import AmlComputeNodeInformation + from ._models_py3 import AmlComputeNodesInformation + from ._models_py3 import AmlComputeProperties + from ._models_py3 import AmlUserFeature + from ._models_py3 import AssignedUser + from ._models_py3 import ClusterUpdateParameters + from ._models_py3 import ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties + from ._models_py3 import Compute + from ._models_py3 import ComputeInstance + from ._models_py3 import ComputeInstanceApplication + from ._models_py3 import ComputeInstanceConnectivityEndpoints + from ._models_py3 import ComputeInstanceCreatedBy + from ._models_py3 import ComputeInstanceLastOperation + from ._models_py3 import ComputeInstanceProperties + from ._models_py3 import ComputeInstanceSshSettings + from ._models_py3 import ComputeNodesInformation + from ._models_py3 import ComputeResource + from ._models_py3 import ComputeSecrets + from ._models_py3 import DataFactory + from ._models_py3 import DataLakeAnalytics + from ._models_py3 import DataLakeAnalyticsProperties + from ._models_py3 import Databricks + from ._models_py3 import DatabricksComputeSecrets + from ._models_py3 import DatabricksProperties + from ._models_py3 import EncryptionProperty + from ._models_py3 import ErrorDetail + from ._models_py3 import ErrorResponse + from ._models_py3 import EstimatedVmPrice + from ._models_py3 import EstimatedVmPrices + from ._models_py3 import HdInsight + from ._models_py3 import HdInsightProperties + from ._models_py3 import Identity + from ._models_py3 import KeyVaultProperties + from ._models_py3 import ListAmlUserFeatureResult + from ._models_py3 import ListUsagesResult + from ._models_py3 import ListWorkspaceKeysResult + from ._models_py3 import ListWorkspaceQuotas + from ._models_py3 import MachineLearningServiceError + from ._models_py3 import NodeStateCounts + from ._models_py3 import NotebookListCredentialsResult + from ._models_py3 import NotebookPreparationError + from ._models_py3 import NotebookResourceInfo + from ._models_py3 import Operation + from ._models_py3 import OperationDisplay + from ._models_py3 import OperationListResult + from ._models_py3 import PaginatedComputeResourcesList + from ._models_py3 import PaginatedWorkspaceConnectionsList + from ._models_py3 import Password + from ._models_py3 import PersonalComputeInstanceSettings + from ._models_py3 import PrivateEndpoint + from ._models_py3 import PrivateEndpointConnection + from ._models_py3 import PrivateLinkResource + from ._models_py3 import PrivateLinkResourceListResult + from ._models_py3 import PrivateLinkServiceConnectionState + from ._models_py3 import QuotaBaseProperties + from ._models_py3 import QuotaUpdateParameters + from ._models_py3 import RegistryListCredentialsResult + from ._models_py3 import Resource + from ._models_py3 import ResourceId + from ._models_py3 import ResourceName + from ._models_py3 import ResourceQuota + from ._models_py3 import ResourceSkuLocationInfo + from ._models_py3 import ResourceSkuZoneDetails + from ._models_py3 import Restriction + from ._models_py3 import ScaleSettings + from ._models_py3 import ServicePrincipalCredentials + from ._models_py3 import SharedPrivateLinkResource + from ._models_py3 import Sku + from ._models_py3 import SkuCapability + from ._models_py3 import SkuListResult + from ._models_py3 import SkuSettings + from ._models_py3 import SslConfiguration + from ._models_py3 import SystemService + from ._models_py3 import UpdateWorkspaceQuotas + from ._models_py3 import UpdateWorkspaceQuotasResult + from ._models_py3 import Usage + from ._models_py3 import UsageName + from ._models_py3 import UserAccountCredentials + from ._models_py3 import VirtualMachine + from ._models_py3 import VirtualMachineProperties + from ._models_py3 import VirtualMachineSecrets + from ._models_py3 import VirtualMachineSize + from ._models_py3 import VirtualMachineSizeListResult + from ._models_py3 import VirtualMachineSshCredentials + from ._models_py3 import Workspace + from ._models_py3 import WorkspaceConnection + from ._models_py3 import WorkspaceConnectionDto + from ._models_py3 import WorkspaceListResult + from ._models_py3 import WorkspaceSku + from ._models_py3 import WorkspaceUpdateParameters +except (SyntaxError, ImportError): + from ._models import Aks # type: ignore + from ._models import AksComputeSecrets # type: ignore + from ._models import AksNetworkingConfiguration # type: ignore + from ._models import AksProperties # type: ignore + from ._models import AmlCompute # type: ignore + from ._models import AmlComputeNodeInformation # type: ignore + from ._models import AmlComputeNodesInformation # type: ignore + from ._models import AmlComputeProperties # type: ignore + from ._models import AmlUserFeature # type: ignore + from ._models import AssignedUser # type: ignore + from ._models import ClusterUpdateParameters # type: ignore + from ._models import ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties # type: ignore + from ._models import Compute # type: ignore + from ._models import ComputeInstance # type: ignore + from ._models import ComputeInstanceApplication # type: ignore + from ._models import ComputeInstanceConnectivityEndpoints # type: ignore + from ._models import ComputeInstanceCreatedBy # type: ignore + from ._models import ComputeInstanceLastOperation # type: ignore + from ._models import ComputeInstanceProperties # type: ignore + from ._models import ComputeInstanceSshSettings # type: ignore + from ._models import ComputeNodesInformation # type: ignore + from ._models import ComputeResource # type: ignore + from ._models import ComputeSecrets # type: ignore + from ._models import DataFactory # type: ignore + from ._models import DataLakeAnalytics # type: ignore + from ._models import DataLakeAnalyticsProperties # type: ignore + from ._models import Databricks # type: ignore + from ._models import DatabricksComputeSecrets # type: ignore + from ._models import DatabricksProperties # type: ignore + from ._models import EncryptionProperty # type: ignore + from ._models import ErrorDetail # type: ignore + from ._models import ErrorResponse # type: ignore + from ._models import EstimatedVmPrice # type: ignore + from ._models import EstimatedVmPrices # type: ignore + from ._models import HdInsight # type: ignore + from ._models import HdInsightProperties # type: ignore + from ._models import Identity # type: ignore + from ._models import KeyVaultProperties # type: ignore + from ._models import ListAmlUserFeatureResult # type: ignore + from ._models import ListUsagesResult # type: ignore + from ._models import ListWorkspaceKeysResult # type: ignore + from ._models import ListWorkspaceQuotas # type: ignore + from ._models import MachineLearningServiceError # type: ignore + from ._models import NodeStateCounts # type: ignore + from ._models import NotebookListCredentialsResult # type: ignore + from ._models import NotebookPreparationError # type: ignore + from ._models import NotebookResourceInfo # type: ignore + from ._models import Operation # type: ignore + from ._models import OperationDisplay # type: ignore + from ._models import OperationListResult # type: ignore + from ._models import PaginatedComputeResourcesList # type: ignore + from ._models import PaginatedWorkspaceConnectionsList # type: ignore + from ._models import Password # type: ignore + from ._models import PersonalComputeInstanceSettings # type: ignore + from ._models import PrivateEndpoint # type: ignore + from ._models import PrivateEndpointConnection # type: ignore + from ._models import PrivateLinkResource # type: ignore + from ._models import PrivateLinkResourceListResult # type: ignore + from ._models import PrivateLinkServiceConnectionState # type: ignore + from ._models import QuotaBaseProperties # type: ignore + from ._models import QuotaUpdateParameters # type: ignore + from ._models import RegistryListCredentialsResult # type: ignore + from ._models import Resource # type: ignore + from ._models import ResourceId # type: ignore + from ._models import ResourceName # type: ignore + from ._models import ResourceQuota # type: ignore + from ._models import ResourceSkuLocationInfo # type: ignore + from ._models import ResourceSkuZoneDetails # type: ignore + from ._models import Restriction # type: ignore + from ._models import ScaleSettings # type: ignore + from ._models import ServicePrincipalCredentials # type: ignore + from ._models import SharedPrivateLinkResource # type: ignore + from ._models import Sku # type: ignore + from ._models import SkuCapability # type: ignore + from ._models import SkuListResult # type: ignore + from ._models import SkuSettings # type: ignore + from ._models import SslConfiguration # type: ignore + from ._models import SystemService # type: ignore + from ._models import UpdateWorkspaceQuotas # type: ignore + from ._models import UpdateWorkspaceQuotasResult # type: ignore + from ._models import Usage # type: ignore + from ._models import UsageName # type: ignore + from ._models import UserAccountCredentials # type: ignore + from ._models import VirtualMachine # type: ignore + from ._models import VirtualMachineProperties # type: ignore + from ._models import VirtualMachineSecrets # type: ignore + from ._models import VirtualMachineSize # type: ignore + from ._models import VirtualMachineSizeListResult # type: ignore + from ._models import VirtualMachineSshCredentials # type: ignore + from ._models import Workspace # type: ignore + from ._models import WorkspaceConnection # type: ignore + from ._models import WorkspaceConnectionDto # type: ignore + from ._models import WorkspaceListResult # type: ignore + from ._models import WorkspaceSku # type: ignore + from ._models import WorkspaceUpdateParameters # type: ignore + +from ._azure_machine_learning_workspaces_enums import ( + AllocationState, + ApplicationSharingPolicy, + BillingCurrency, + ComputeInstanceAuthorizationType, + ComputeInstanceState, + ComputeType, + EncryptionStatus, + NodeState, + OperationName, + OperationStatus, + OsType, + PrivateEndpointConnectionProvisioningState, + PrivateEndpointServiceConnectionStatus, + ProvisioningState, + QuotaUnit, + ReasonCode, + RemoteLoginPortPublicAccess, + ResourceIdentityType, + SshPublicAccess, + SslConfigurationStatus, + Status, + UnderlyingResourceAction, + UnitOfMeasure, + UsageUnit, + VmPriceOsType, + VmPriority, + VmTier, +) + +__all__ = [ + 'Aks', + 'AksComputeSecrets', + 'AksNetworkingConfiguration', + 'AksProperties', + 'AmlCompute', + 'AmlComputeNodeInformation', + 'AmlComputeNodesInformation', + 'AmlComputeProperties', + 'AmlUserFeature', + 'AssignedUser', + 'ClusterUpdateParameters', + 'ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties', + 'Compute', + 'ComputeInstance', + 'ComputeInstanceApplication', + 'ComputeInstanceConnectivityEndpoints', + 'ComputeInstanceCreatedBy', + 'ComputeInstanceLastOperation', + 'ComputeInstanceProperties', + 'ComputeInstanceSshSettings', + 'ComputeNodesInformation', + 'ComputeResource', + 'ComputeSecrets', + 'DataFactory', + 'DataLakeAnalytics', + 'DataLakeAnalyticsProperties', + 'Databricks', + 'DatabricksComputeSecrets', + 'DatabricksProperties', + 'EncryptionProperty', + 'ErrorDetail', + 'ErrorResponse', + 'EstimatedVmPrice', + 'EstimatedVmPrices', + 'HdInsight', + 'HdInsightProperties', + 'Identity', + 'KeyVaultProperties', + 'ListAmlUserFeatureResult', + 'ListUsagesResult', + 'ListWorkspaceKeysResult', + 'ListWorkspaceQuotas', + 'MachineLearningServiceError', + 'NodeStateCounts', + 'NotebookListCredentialsResult', + 'NotebookPreparationError', + 'NotebookResourceInfo', + 'Operation', + 'OperationDisplay', + 'OperationListResult', + 'PaginatedComputeResourcesList', + 'PaginatedWorkspaceConnectionsList', + 'Password', + 'PersonalComputeInstanceSettings', + 'PrivateEndpoint', + 'PrivateEndpointConnection', + 'PrivateLinkResource', + 'PrivateLinkResourceListResult', + 'PrivateLinkServiceConnectionState', + 'QuotaBaseProperties', + 'QuotaUpdateParameters', + 'RegistryListCredentialsResult', + 'Resource', + 'ResourceId', + 'ResourceName', + 'ResourceQuota', + 'ResourceSkuLocationInfo', + 'ResourceSkuZoneDetails', + 'Restriction', + 'ScaleSettings', + 'ServicePrincipalCredentials', + 'SharedPrivateLinkResource', + 'Sku', + 'SkuCapability', + 'SkuListResult', + 'SkuSettings', + 'SslConfiguration', + 'SystemService', + 'UpdateWorkspaceQuotas', + 'UpdateWorkspaceQuotasResult', + 'Usage', + 'UsageName', + 'UserAccountCredentials', + 'VirtualMachine', + 'VirtualMachineProperties', + 'VirtualMachineSecrets', + 'VirtualMachineSize', + 'VirtualMachineSizeListResult', + 'VirtualMachineSshCredentials', + 'Workspace', + 'WorkspaceConnection', + 'WorkspaceConnectionDto', + 'WorkspaceListResult', + 'WorkspaceSku', + 'WorkspaceUpdateParameters', + 'AllocationState', + 'ApplicationSharingPolicy', + 'BillingCurrency', + 'ComputeInstanceAuthorizationType', + 'ComputeInstanceState', + 'ComputeType', + 'EncryptionStatus', + 'NodeState', + 'OperationName', + 'OperationStatus', + 'OsType', + 'PrivateEndpointConnectionProvisioningState', + 'PrivateEndpointServiceConnectionStatus', + 'ProvisioningState', + 'QuotaUnit', + 'ReasonCode', + 'RemoteLoginPortPublicAccess', + 'ResourceIdentityType', + 'SshPublicAccess', + 'SslConfigurationStatus', + 'Status', + 'UnderlyingResourceAction', + 'UnitOfMeasure', + 'UsageUnit', + 'VmPriceOsType', + 'VmPriority', + 'VmTier', +] diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_azure_machine_learning_workspaces_enums.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_azure_machine_learning_workspaces_enums.py new file mode 100644 index 00000000000..8cfaec67bd3 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_azure_machine_learning_workspaces_enums.py @@ -0,0 +1,279 @@ +# 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 enum import Enum, EnumMeta +from six import with_metaclass + +class _CaseInsensitiveEnumMeta(EnumMeta): + def __getitem__(self, name): + return super().__getitem__(name.upper()) + + def __getattr__(cls, name): + """Return the enum member matching `name` + We use __getattr__ instead of descriptors or inserting into the enum + class' __dict__ in order to support `name` and `value` being both + properties for enum members (which live in the class' __dict__) and + enum members themselves. + """ + try: + return cls._member_map_[name.upper()] + except KeyError: + raise AttributeError(name) + + +class AllocationState(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Allocation state of the compute. Possible values are: steady - Indicates that the compute is + not resizing. There are no changes to the number of compute nodes in the compute in progress. A + compute enters this state when it is created and when no operations are being performed on the + compute to change the number of compute nodes. resizing - Indicates that the compute is + resizing; that is, compute nodes are being added to or removed from the compute. + """ + + STEADY = "Steady" + RESIZING = "Resizing" + +class ApplicationSharingPolicy(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Policy for sharing applications on this compute instance among users of parent workspace. If + Personal, only the creator can access applications on this compute instance. When Shared, any + workspace user can access applications on this instance depending on his/her assigned role. + """ + + PERSONAL = "Personal" + SHARED = "Shared" + +class BillingCurrency(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Three lettered code specifying the currency of the VM price. Example: USD + """ + + USD = "USD" + +class ComputeInstanceAuthorizationType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The Compute Instance Authorization type. Available values are personal (default). + """ + + PERSONAL = "personal" + +class ComputeInstanceState(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Current state of a ComputeInstance. + """ + + CREATING = "Creating" + CREATE_FAILED = "CreateFailed" + DELETING = "Deleting" + RUNNING = "Running" + RESTARTING = "Restarting" + JOB_RUNNING = "JobRunning" + SETTING_UP = "SettingUp" + SETUP_FAILED = "SetupFailed" + STARTING = "Starting" + STOPPED = "Stopped" + STOPPING = "Stopping" + USER_SETTING_UP = "UserSettingUp" + USER_SETUP_FAILED = "UserSetupFailed" + UNKNOWN = "Unknown" + UNUSABLE = "Unusable" + +class ComputeType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The type of compute + """ + + AKS = "AKS" + AML_COMPUTE = "AmlCompute" + COMPUTE_INSTANCE = "ComputeInstance" + DATA_FACTORY = "DataFactory" + VIRTUAL_MACHINE = "VirtualMachine" + HD_INSIGHT = "HDInsight" + DATABRICKS = "Databricks" + DATA_LAKE_ANALYTICS = "DataLakeAnalytics" + +class EncryptionStatus(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Indicates whether or not the encryption is enabled for the workspace. + """ + + ENABLED = "Enabled" + DISABLED = "Disabled" + +class NodeState(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """State of the compute node. Values are idle, running, preparing, unusable, leaving and + preempted. + """ + + IDLE = "idle" + RUNNING = "running" + PREPARING = "preparing" + UNUSABLE = "unusable" + LEAVING = "leaving" + PREEMPTED = "preempted" + +class OperationName(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Name of the last operation. + """ + + CREATE = "Create" + START = "Start" + STOP = "Stop" + RESTART = "Restart" + REIMAGE = "Reimage" + DELETE = "Delete" + +class OperationStatus(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Operation status. + """ + + IN_PROGRESS = "InProgress" + SUCCEEDED = "Succeeded" + CREATE_FAILED = "CreateFailed" + START_FAILED = "StartFailed" + STOP_FAILED = "StopFailed" + RESTART_FAILED = "RestartFailed" + REIMAGE_FAILED = "ReimageFailed" + DELETE_FAILED = "DeleteFailed" + +class OsType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Compute OS Type + """ + + LINUX = "Linux" + WINDOWS = "Windows" + +class PrivateEndpointConnectionProvisioningState(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The current provisioning state. + """ + + SUCCEEDED = "Succeeded" + CREATING = "Creating" + DELETING = "Deleting" + FAILED = "Failed" + +class PrivateEndpointServiceConnectionStatus(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The private endpoint connection status. + """ + + PENDING = "Pending" + APPROVED = "Approved" + REJECTED = "Rejected" + DISCONNECTED = "Disconnected" + TIMEOUT = "Timeout" + +class ProvisioningState(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The current deployment state of workspace resource. The provisioningState is to indicate states + for resource provisioning. + """ + + UNKNOWN = "Unknown" + UPDATING = "Updating" + CREATING = "Creating" + DELETING = "Deleting" + SUCCEEDED = "Succeeded" + FAILED = "Failed" + CANCELED = "Canceled" + +class QuotaUnit(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """An enum describing the unit of quota measurement. + """ + + COUNT = "Count" + +class ReasonCode(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The reason for the restriction. + """ + + NOT_SPECIFIED = "NotSpecified" + NOT_AVAILABLE_FOR_REGION = "NotAvailableForRegion" + NOT_AVAILABLE_FOR_SUBSCRIPTION = "NotAvailableForSubscription" + +class RemoteLoginPortPublicAccess(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """State of the public SSH port. Possible values are: Disabled - Indicates that the public ssh + port is closed on all nodes of the cluster. Enabled - Indicates that the public ssh port is + open on all nodes of the cluster. NotSpecified - Indicates that the public ssh port is closed + on all nodes of the cluster if VNet is defined, else is open all public nodes. It can be + default only during cluster creation time, after creation it will be either enabled or + disabled. + """ + + ENABLED = "Enabled" + DISABLED = "Disabled" + NOT_SPECIFIED = "NotSpecified" + +class ResourceIdentityType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The identity type. + """ + + SYSTEM_ASSIGNED = "SystemAssigned" + SYSTEM_ASSIGNED_USER_ASSIGNED = "SystemAssigned,UserAssigned" + USER_ASSIGNED = "UserAssigned" + NONE = "None" + +class SshPublicAccess(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """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 public ssh port is open and + accessible according to the VNet/subnet policy if applicable. + """ + + ENABLED = "Enabled" + DISABLED = "Disabled" + +class SslConfigurationStatus(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Enable or disable ssl for scoring + """ + + DISABLED = "Disabled" + ENABLED = "Enabled" + AUTO = "Auto" + +class Status(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Status of update workspace quota. + """ + + UNDEFINED = "Undefined" + SUCCESS = "Success" + FAILURE = "Failure" + INVALID_QUOTA_BELOW_CLUSTER_MINIMUM = "InvalidQuotaBelowClusterMinimum" + INVALID_QUOTA_EXCEEDS_SUBSCRIPTION_LIMIT = "InvalidQuotaExceedsSubscriptionLimit" + INVALID_VM_FAMILY_NAME = "InvalidVMFamilyName" + OPERATION_NOT_SUPPORTED_FOR_SKU = "OperationNotSupportedForSku" + OPERATION_NOT_ENABLED_FOR_REGION = "OperationNotEnabledForRegion" + +class UnderlyingResourceAction(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + + DELETE = "Delete" + DETACH = "Detach" + +class UnitOfMeasure(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The unit of time measurement for the specified VM price. Example: OneHour + """ + + ONE_HOUR = "OneHour" + +class UsageUnit(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """An enum describing the unit of usage measurement. + """ + + COUNT = "Count" + +class VmPriceOsType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Operating system type used by the VM. + """ + + LINUX = "Linux" + WINDOWS = "Windows" + +class VmPriority(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """Virtual Machine priority + """ + + DEDICATED = "Dedicated" + LOW_PRIORITY = "LowPriority" + +class VmTier(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)): + """The type of the VM. + """ + + STANDARD = "Standard" + LOW_PRIORITY = "LowPriority" + SPOT = "Spot" diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_models.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_models.py new file mode 100644 index 00000000000..5e0fa59882d --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_models.py @@ -0,0 +1,3721 @@ +# 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.core.exceptions import HttpResponseError +import msrest.serialization + + +class Compute(msrest.serialization.Model): + """Machine Learning compute object. + + You probably want to use the sub-classes and not this class directly. Known + sub-classes are: Aks, AmlCompute, ComputeInstance, DataFactory, DataLakeAnalytics, Databricks, HdInsight, VirtualMachine. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + } + + _subtype_map = { + 'compute_type': {'AKS': 'Aks', 'AmlCompute': 'AmlCompute', 'ComputeInstance': 'ComputeInstance', 'DataFactory': 'DataFactory', 'DataLakeAnalytics': 'DataLakeAnalytics', 'Databricks': 'Databricks', 'HDInsight': 'HdInsight', 'VirtualMachine': 'VirtualMachine'} + } + + def __init__( + self, + **kwargs + ): + super(Compute, self).__init__(**kwargs) + self.compute_type = None # type: Optional[str] + self.compute_location = kwargs.get('compute_location', None) + self.provisioning_state = None + self.description = kwargs.get('description', None) + self.created_on = None + self.modified_on = None + self.resource_id = kwargs.get('resource_id', None) + self.provisioning_errors = None + self.is_attached_compute = None + + +class Aks(Compute): + """A Machine Learning compute based on AKS. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: AKS properties. + :type properties: ~azure_machine_learning_workspaces.models.AksProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'AksProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(Aks, self).__init__(**kwargs) + self.compute_type = 'AKS' # type: str + self.properties = kwargs.get('properties', None) + + +class ComputeSecrets(msrest.serialization.Model): + """Secrets related to a Machine Learning compute. Might differ for every type of compute. + + You probably want to use the sub-classes and not this class directly. Known + sub-classes are: AksComputeSecrets, DatabricksComputeSecrets, VirtualMachineSecrets. + + All required parameters must be populated in order to send to Azure. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + """ + + _validation = { + 'compute_type': {'required': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + } + + _subtype_map = { + 'compute_type': {'AKS': 'AksComputeSecrets', 'Databricks': 'DatabricksComputeSecrets', 'VirtualMachine': 'VirtualMachineSecrets'} + } + + def __init__( + self, + **kwargs + ): + super(ComputeSecrets, self).__init__(**kwargs) + self.compute_type = None # type: Optional[str] + + +class AksComputeSecrets(ComputeSecrets): + """Secrets related to a Machine Learning compute based on AKS. + + All required parameters must be populated in order to send to Azure. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param user_kube_config: Content of kubeconfig file that can be used to connect to the + Kubernetes cluster. + :type user_kube_config: str + :param admin_kube_config: Content of kubeconfig file that can be used to connect to the + Kubernetes cluster. + :type admin_kube_config: str + :param image_pull_secret_name: Image registry pull secret. + :type image_pull_secret_name: str + """ + + _validation = { + 'compute_type': {'required': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'user_kube_config': {'key': 'userKubeConfig', 'type': 'str'}, + 'admin_kube_config': {'key': 'adminKubeConfig', 'type': 'str'}, + 'image_pull_secret_name': {'key': 'imagePullSecretName', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AksComputeSecrets, self).__init__(**kwargs) + self.compute_type = 'AKS' # type: str + self.user_kube_config = kwargs.get('user_kube_config', None) + self.admin_kube_config = kwargs.get('admin_kube_config', None) + self.image_pull_secret_name = kwargs.get('image_pull_secret_name', None) + + +class AksNetworkingConfiguration(msrest.serialization.Model): + """Advance configuration for AKS networking. + + :param subnet_id: Virtual network subnet resource ID the compute nodes belong to. + :type subnet_id: str + :param service_cidr: A CIDR notation IP range from which to assign service cluster IPs. It must + not overlap with any Subnet IP ranges. + :type service_cidr: str + :param dns_service_ip: An IP address assigned to the Kubernetes DNS service. It must be within + the Kubernetes service address range specified in serviceCidr. + :type dns_service_ip: str + :param docker_bridge_cidr: A CIDR notation IP range assigned to the Docker bridge network. It + must not overlap with any Subnet IP ranges or the Kubernetes service address range. + :type docker_bridge_cidr: str + """ + + _validation = { + 'service_cidr': {'pattern': r'^([0-9]{1,3}\.){3}[0-9]{1,3}(\/([0-9]|[1-2][0-9]|3[0-2]))?$'}, + 'dns_service_ip': {'pattern': r'^(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)$'}, + 'docker_bridge_cidr': {'pattern': r'^([0-9]{1,3}\.){3}[0-9]{1,3}(\/([0-9]|[1-2][0-9]|3[0-2]))?$'}, + } + + _attribute_map = { + 'subnet_id': {'key': 'subnetId', 'type': 'str'}, + 'service_cidr': {'key': 'serviceCidr', 'type': 'str'}, + 'dns_service_ip': {'key': 'dnsServiceIP', 'type': 'str'}, + 'docker_bridge_cidr': {'key': 'dockerBridgeCidr', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AksNetworkingConfiguration, self).__init__(**kwargs) + self.subnet_id = kwargs.get('subnet_id', None) + self.service_cidr = kwargs.get('service_cidr', None) + self.dns_service_ip = kwargs.get('dns_service_ip', None) + self.docker_bridge_cidr = kwargs.get('docker_bridge_cidr', None) + + +class AksProperties(msrest.serialization.Model): + """AKS properties. + + Variables are only populated by the server, and will be ignored when sending a request. + + :param cluster_fqdn: Cluster full qualified domain name. + :type cluster_fqdn: str + :ivar system_services: System services. + :vartype system_services: list[~azure_machine_learning_workspaces.models.SystemService] + :param agent_count: Number of agents. + :type agent_count: int + :param agent_vm_size: Agent virtual machine size. + :type agent_vm_size: str + :param ssl_configuration: SSL configuration. + :type ssl_configuration: ~azure_machine_learning_workspaces.models.SslConfiguration + :param aks_networking_configuration: AKS networking configuration for vnet. + :type aks_networking_configuration: + ~azure_machine_learning_workspaces.models.AksNetworkingConfiguration + """ + + _validation = { + 'system_services': {'readonly': True}, + 'agent_count': {'minimum': 1}, + } + + _attribute_map = { + 'cluster_fqdn': {'key': 'clusterFqdn', 'type': 'str'}, + 'system_services': {'key': 'systemServices', 'type': '[SystemService]'}, + 'agent_count': {'key': 'agentCount', 'type': 'int'}, + 'agent_vm_size': {'key': 'agentVmSize', 'type': 'str'}, + 'ssl_configuration': {'key': 'sslConfiguration', 'type': 'SslConfiguration'}, + 'aks_networking_configuration': {'key': 'aksNetworkingConfiguration', 'type': 'AksNetworkingConfiguration'}, + } + + def __init__( + self, + **kwargs + ): + super(AksProperties, self).__init__(**kwargs) + self.cluster_fqdn = kwargs.get('cluster_fqdn', None) + self.system_services = None + self.agent_count = kwargs.get('agent_count', None) + self.agent_vm_size = kwargs.get('agent_vm_size', None) + self.ssl_configuration = kwargs.get('ssl_configuration', None) + self.aks_networking_configuration = kwargs.get('aks_networking_configuration', None) + + +class AmlCompute(Compute): + """An Azure Machine Learning compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: AML Compute properties. + :type properties: ~azure_machine_learning_workspaces.models.AmlComputeProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'AmlComputeProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(AmlCompute, self).__init__(**kwargs) + self.compute_type = 'AmlCompute' # type: str + self.properties = kwargs.get('properties', None) + + +class AmlComputeNodeInformation(msrest.serialization.Model): + """Compute node information related to a AmlCompute. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar node_id: ID of the compute node. + :vartype node_id: str + :ivar private_ip_address: Private IP address of the compute node. + :vartype private_ip_address: str + :ivar public_ip_address: Public IP address of the compute node. + :vartype public_ip_address: str + :ivar port: SSH port number of the node. + :vartype port: int + :ivar node_state: State of the compute node. Values are idle, running, preparing, unusable, + leaving and preempted. Possible values include: "idle", "running", "preparing", "unusable", + "leaving", "preempted". + :vartype node_state: str or ~azure_machine_learning_workspaces.models.NodeState + :ivar run_id: ID of the Experiment running on the node, if any else null. + :vartype run_id: str + """ + + _validation = { + 'node_id': {'readonly': True}, + 'private_ip_address': {'readonly': True}, + 'public_ip_address': {'readonly': True}, + 'port': {'readonly': True}, + 'node_state': {'readonly': True}, + 'run_id': {'readonly': True}, + } + + _attribute_map = { + 'node_id': {'key': 'nodeId', 'type': 'str'}, + 'private_ip_address': {'key': 'privateIpAddress', 'type': 'str'}, + 'public_ip_address': {'key': 'publicIpAddress', 'type': 'str'}, + 'port': {'key': 'port', 'type': 'int'}, + 'node_state': {'key': 'nodeState', 'type': 'str'}, + 'run_id': {'key': 'runId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AmlComputeNodeInformation, self).__init__(**kwargs) + self.node_id = None + self.private_ip_address = None + self.public_ip_address = None + self.port = None + self.node_state = None + self.run_id = None + + +class ComputeNodesInformation(msrest.serialization.Model): + """Compute nodes information related to a Machine Learning compute. Might differ for every type of compute. + + You probably want to use the sub-classes and not this class directly. Known + sub-classes are: AmlComputeNodesInformation. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :ivar next_link: The continuation token. + :vartype next_link: str + """ + + _validation = { + 'compute_type': {'required': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + _subtype_map = { + 'compute_type': {'AmlCompute': 'AmlComputeNodesInformation'} + } + + def __init__( + self, + **kwargs + ): + super(ComputeNodesInformation, self).__init__(**kwargs) + self.compute_type = None # type: Optional[str] + self.next_link = None + + +class AmlComputeNodesInformation(ComputeNodesInformation): + """Compute node information related to a AmlCompute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :ivar next_link: The continuation token. + :vartype next_link: str + :ivar nodes: The collection of returned AmlCompute nodes details. + :vartype nodes: list[~azure_machine_learning_workspaces.models.AmlComputeNodeInformation] + """ + + _validation = { + 'compute_type': {'required': True}, + 'next_link': {'readonly': True}, + 'nodes': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + 'nodes': {'key': 'nodes', 'type': '[AmlComputeNodeInformation]'}, + } + + def __init__( + self, + **kwargs + ): + super(AmlComputeNodesInformation, self).__init__(**kwargs) + self.compute_type = 'AmlCompute' # type: str + self.nodes = None + + +class AmlComputeProperties(msrest.serialization.Model): + """AML Compute properties. + + Variables are only populated by the server, and will be ignored when sending a request. + + :param os_type: Compute OS Type. Possible values include: "Linux", "Windows". Default value: + "Linux". + :type os_type: str or ~azure_machine_learning_workspaces.models.OsType + :param vm_size: Virtual Machine Size. + :type vm_size: str + :param vm_priority: Virtual Machine priority. Possible values include: "Dedicated", + "LowPriority". + :type vm_priority: str or ~azure_machine_learning_workspaces.models.VmPriority + :param scale_settings: Scale settings for AML Compute. + :type scale_settings: ~azure_machine_learning_workspaces.models.ScaleSettings + :param user_account_credentials: Credentials for an administrator user account that will be + created on each compute node. + :type user_account_credentials: + ~azure_machine_learning_workspaces.models.UserAccountCredentials + :param subnet: Virtual network subnet resource ID the compute nodes belong to. + :type subnet: ~azure_machine_learning_workspaces.models.ResourceId + :param remote_login_port_public_access: State of the public SSH port. Possible values are: + Disabled - Indicates that the public ssh port is closed on all nodes of the cluster. Enabled - + Indicates that the public ssh port is open on all nodes of the cluster. NotSpecified - + Indicates that the public ssh port is closed on all nodes of the cluster if VNet is defined, + else is open all public nodes. It can be default only during cluster creation time, after + creation it will be either enabled or disabled. Possible values include: "Enabled", "Disabled", + "NotSpecified". Default value: "NotSpecified". + :type remote_login_port_public_access: str or + ~azure_machine_learning_workspaces.models.RemoteLoginPortPublicAccess + :ivar allocation_state: Allocation state of the compute. Possible values are: steady - + Indicates that the compute is not resizing. There are no changes to the number of compute nodes + in the compute in progress. A compute enters this state when it is created and when no + operations are being performed on the compute to change the number of compute nodes. resizing - + Indicates that the compute is resizing; that is, compute nodes are being added to or removed + from the compute. Possible values include: "Steady", "Resizing". + :vartype allocation_state: str or ~azure_machine_learning_workspaces.models.AllocationState + :ivar allocation_state_transition_time: The time at which the compute entered its current + allocation state. + :vartype allocation_state_transition_time: ~datetime.datetime + :ivar errors: Collection of errors encountered by various compute nodes during node setup. + :vartype errors: list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar current_node_count: The number of compute nodes currently assigned to the compute. + :vartype current_node_count: int + :ivar target_node_count: The target number of compute nodes for the compute. If the + allocationState is resizing, this property denotes the target node count for the ongoing resize + operation. If the allocationState is steady, this property denotes the target node count for + the previous resize operation. + :vartype target_node_count: int + :ivar node_state_counts: Counts of various node states on the compute. + :vartype node_state_counts: ~azure_machine_learning_workspaces.models.NodeStateCounts + """ + + _validation = { + 'allocation_state': {'readonly': True}, + 'allocation_state_transition_time': {'readonly': True}, + 'errors': {'readonly': True}, + 'current_node_count': {'readonly': True}, + 'target_node_count': {'readonly': True}, + 'node_state_counts': {'readonly': True}, + } + + _attribute_map = { + 'os_type': {'key': 'osType', 'type': 'str'}, + 'vm_size': {'key': 'vmSize', 'type': 'str'}, + 'vm_priority': {'key': 'vmPriority', 'type': 'str'}, + 'scale_settings': {'key': 'scaleSettings', 'type': 'ScaleSettings'}, + 'user_account_credentials': {'key': 'userAccountCredentials', 'type': 'UserAccountCredentials'}, + 'subnet': {'key': 'subnet', 'type': 'ResourceId'}, + 'remote_login_port_public_access': {'key': 'remoteLoginPortPublicAccess', 'type': 'str'}, + 'allocation_state': {'key': 'allocationState', 'type': 'str'}, + 'allocation_state_transition_time': {'key': 'allocationStateTransitionTime', 'type': 'iso-8601'}, + 'errors': {'key': 'errors', 'type': '[MachineLearningServiceError]'}, + 'current_node_count': {'key': 'currentNodeCount', 'type': 'int'}, + 'target_node_count': {'key': 'targetNodeCount', 'type': 'int'}, + 'node_state_counts': {'key': 'nodeStateCounts', 'type': 'NodeStateCounts'}, + } + + def __init__( + self, + **kwargs + ): + super(AmlComputeProperties, self).__init__(**kwargs) + self.os_type = kwargs.get('os_type', "Linux") + self.vm_size = kwargs.get('vm_size', None) + self.vm_priority = kwargs.get('vm_priority', None) + self.scale_settings = kwargs.get('scale_settings', None) + self.user_account_credentials = kwargs.get('user_account_credentials', None) + self.subnet = kwargs.get('subnet', None) + self.remote_login_port_public_access = kwargs.get('remote_login_port_public_access', "NotSpecified") + self.allocation_state = None + self.allocation_state_transition_time = None + self.errors = None + self.current_node_count = None + self.target_node_count = None + self.node_state_counts = None + + +class AmlUserFeature(msrest.serialization.Model): + """Features enabled for a workspace. + + :param id: Specifies the feature ID. + :type id: str + :param display_name: Specifies the feature name. + :type display_name: str + :param description: Describes the feature for user experience. + :type description: str + """ + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'display_name': {'key': 'displayName', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AmlUserFeature, self).__init__(**kwargs) + self.id = kwargs.get('id', None) + self.display_name = kwargs.get('display_name', None) + self.description = kwargs.get('description', None) + + +class AssignedUser(msrest.serialization.Model): + """A user that can be assigned to a compute instance. + + All required parameters must be populated in order to send to Azure. + + :param object_id: Required. User’s AAD Object Id. + :type object_id: str + :param tenant_id: Required. User’s AAD Tenant Id. + :type tenant_id: str + """ + + _validation = { + 'object_id': {'required': True}, + 'tenant_id': {'required': True}, + } + + _attribute_map = { + 'object_id': {'key': 'objectId', 'type': 'str'}, + 'tenant_id': {'key': 'tenantId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AssignedUser, self).__init__(**kwargs) + self.object_id = kwargs['object_id'] + self.tenant_id = kwargs['tenant_id'] + + +class ClusterUpdateParameters(msrest.serialization.Model): + """AmlCompute update parameters. + + :param scale_settings: Desired scale settings for the amlCompute. + :type scale_settings: ~azure_machine_learning_workspaces.models.ScaleSettings + """ + + _attribute_map = { + 'scale_settings': {'key': 'properties.scaleSettings', 'type': 'ScaleSettings'}, + } + + def __init__( + self, + **kwargs + ): + super(ClusterUpdateParameters, self).__init__(**kwargs) + self.scale_settings = kwargs.get('scale_settings', None) + + +class ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties(msrest.serialization.Model): + """ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar principal_id: The principal id of user assigned identity. + :vartype principal_id: str + :ivar client_id: The client id of user assigned identity. + :vartype client_id: str + """ + + _validation = { + 'principal_id': {'readonly': True}, + 'client_id': {'readonly': True}, + } + + _attribute_map = { + 'principal_id': {'key': 'principalId', 'type': 'str'}, + 'client_id': {'key': 'clientId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties, self).__init__(**kwargs) + self.principal_id = None + self.client_id = None + + +class ComputeInstance(Compute): + """An Azure Machine Learning compute instance. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: Compute Instance properties. + :type properties: ~azure_machine_learning_workspaces.models.ComputeInstanceProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'ComputeInstanceProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstance, self).__init__(**kwargs) + self.compute_type = 'ComputeInstance' # type: str + self.properties = kwargs.get('properties', None) + + +class ComputeInstanceApplication(msrest.serialization.Model): + """Defines an Aml Instance application and its connectivity endpoint URI. + + :param display_name: Name of the ComputeInstance application. + :type display_name: str + :param endpoint_uri: Application' endpoint URI. + :type endpoint_uri: str + """ + + _attribute_map = { + 'display_name': {'key': 'displayName', 'type': 'str'}, + 'endpoint_uri': {'key': 'endpointUri', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstanceApplication, self).__init__(**kwargs) + self.display_name = kwargs.get('display_name', None) + self.endpoint_uri = kwargs.get('endpoint_uri', None) + + +class ComputeInstanceConnectivityEndpoints(msrest.serialization.Model): + """Defines all connectivity endpoints and properties for a ComputeInstance. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar public_ip_address: Public IP Address of this ComputeInstance. + :vartype public_ip_address: str + :ivar private_ip_address: Private IP Address of this ComputeInstance (local to the VNET in + which the compute instance is deployed). + :vartype private_ip_address: str + """ + + _validation = { + 'public_ip_address': {'readonly': True}, + 'private_ip_address': {'readonly': True}, + } + + _attribute_map = { + 'public_ip_address': {'key': 'publicIpAddress', 'type': 'str'}, + 'private_ip_address': {'key': 'privateIpAddress', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstanceConnectivityEndpoints, self).__init__(**kwargs) + self.public_ip_address = None + self.private_ip_address = None + + +class ComputeInstanceCreatedBy(msrest.serialization.Model): + """Describes information on user who created this ComputeInstance. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar user_name: Name of the user. + :vartype user_name: str + :ivar user_org_id: Uniquely identifies user' Azure Active Directory organization. + :vartype user_org_id: str + :ivar user_id: Uniquely identifies the user within his/her organization. + :vartype user_id: str + """ + + _validation = { + 'user_name': {'readonly': True}, + 'user_org_id': {'readonly': True}, + 'user_id': {'readonly': True}, + } + + _attribute_map = { + 'user_name': {'key': 'userName', 'type': 'str'}, + 'user_org_id': {'key': 'userOrgId', 'type': 'str'}, + 'user_id': {'key': 'userId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstanceCreatedBy, self).__init__(**kwargs) + self.user_name = None + self.user_org_id = None + self.user_id = None + + +class ComputeInstanceLastOperation(msrest.serialization.Model): + """The last operation on ComputeInstance. + + :param operation_name: Name of the last operation. Possible values include: "Create", "Start", + "Stop", "Restart", "Reimage", "Delete". + :type operation_name: str or ~azure_machine_learning_workspaces.models.OperationName + :param operation_time: Time of the last operation. + :type operation_time: ~datetime.datetime + :param operation_status: Operation status. Possible values include: "InProgress", "Succeeded", + "CreateFailed", "StartFailed", "StopFailed", "RestartFailed", "ReimageFailed", "DeleteFailed". + :type operation_status: str or ~azure_machine_learning_workspaces.models.OperationStatus + """ + + _attribute_map = { + 'operation_name': {'key': 'operationName', 'type': 'str'}, + 'operation_time': {'key': 'operationTime', 'type': 'iso-8601'}, + 'operation_status': {'key': 'operationStatus', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstanceLastOperation, self).__init__(**kwargs) + self.operation_name = kwargs.get('operation_name', None) + self.operation_time = kwargs.get('operation_time', None) + self.operation_status = kwargs.get('operation_status', None) + + +class ComputeInstanceProperties(msrest.serialization.Model): + """Compute Instance properties. + + Variables are only populated by the server, and will be ignored when sending a request. + + :param vm_size: Virtual Machine Size. + :type vm_size: str + :param subnet: Virtual network subnet resource ID the compute nodes belong to. + :type subnet: ~azure_machine_learning_workspaces.models.ResourceId + :param application_sharing_policy: Policy for sharing applications on this compute instance + among users of parent workspace. If Personal, only the creator can access applications on this + compute instance. When Shared, any workspace user can access applications on this instance + depending on his/her assigned role. Possible values include: "Personal", "Shared". Default + value: "Shared". + :type application_sharing_policy: str or + ~azure_machine_learning_workspaces.models.ApplicationSharingPolicy + :param ssh_settings: Specifies policy and settings for SSH access. + :type ssh_settings: ~azure_machine_learning_workspaces.models.ComputeInstanceSshSettings + :ivar connectivity_endpoints: Describes all connectivity endpoints available for this + ComputeInstance. + :vartype connectivity_endpoints: + ~azure_machine_learning_workspaces.models.ComputeInstanceConnectivityEndpoints + :ivar applications: Describes available applications and their endpoints on this + ComputeInstance. + :vartype applications: + list[~azure_machine_learning_workspaces.models.ComputeInstanceApplication] + :ivar created_by: Describes information on user who created this ComputeInstance. + :vartype created_by: ~azure_machine_learning_workspaces.models.ComputeInstanceCreatedBy + :ivar errors: Collection of errors encountered on this ComputeInstance. + :vartype errors: list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar state: The current state of this ComputeInstance. Possible values include: "Creating", + "CreateFailed", "Deleting", "Running", "Restarting", "JobRunning", "SettingUp", "SetupFailed", + "Starting", "Stopped", "Stopping", "UserSettingUp", "UserSetupFailed", "Unknown", "Unusable". + :vartype state: str or ~azure_machine_learning_workspaces.models.ComputeInstanceState + :param compute_instance_authorization_type: The Compute Instance Authorization type. Available + values are personal (default). Possible values include: "personal". Default value: "personal". + :type compute_instance_authorization_type: str or + ~azure_machine_learning_workspaces.models.ComputeInstanceAuthorizationType + :param personal_compute_instance_settings: Settings for a personal compute instance. + :type personal_compute_instance_settings: + ~azure_machine_learning_workspaces.models.PersonalComputeInstanceSettings + :ivar last_operation: The last operation on ComputeInstance. + :vartype last_operation: ~azure_machine_learning_workspaces.models.ComputeInstanceLastOperation + """ + + _validation = { + 'connectivity_endpoints': {'readonly': True}, + 'applications': {'readonly': True}, + 'created_by': {'readonly': True}, + 'errors': {'readonly': True}, + 'state': {'readonly': True}, + 'last_operation': {'readonly': True}, + } + + _attribute_map = { + 'vm_size': {'key': 'vmSize', 'type': 'str'}, + 'subnet': {'key': 'subnet', 'type': 'ResourceId'}, + 'application_sharing_policy': {'key': 'applicationSharingPolicy', 'type': 'str'}, + 'ssh_settings': {'key': 'sshSettings', 'type': 'ComputeInstanceSshSettings'}, + 'connectivity_endpoints': {'key': 'connectivityEndpoints', 'type': 'ComputeInstanceConnectivityEndpoints'}, + 'applications': {'key': 'applications', 'type': '[ComputeInstanceApplication]'}, + 'created_by': {'key': 'createdBy', 'type': 'ComputeInstanceCreatedBy'}, + 'errors': {'key': 'errors', 'type': '[MachineLearningServiceError]'}, + 'state': {'key': 'state', 'type': 'str'}, + 'compute_instance_authorization_type': {'key': 'computeInstanceAuthorizationType', 'type': 'str'}, + 'personal_compute_instance_settings': {'key': 'personalComputeInstanceSettings', 'type': 'PersonalComputeInstanceSettings'}, + 'last_operation': {'key': 'lastOperation', 'type': 'ComputeInstanceLastOperation'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstanceProperties, self).__init__(**kwargs) + self.vm_size = kwargs.get('vm_size', None) + self.subnet = kwargs.get('subnet', None) + self.application_sharing_policy = kwargs.get('application_sharing_policy', "Shared") + self.ssh_settings = kwargs.get('ssh_settings', None) + self.connectivity_endpoints = None + self.applications = None + self.created_by = None + self.errors = None + self.state = None + self.compute_instance_authorization_type = kwargs.get('compute_instance_authorization_type', "personal") + self.personal_compute_instance_settings = kwargs.get('personal_compute_instance_settings', None) + self.last_operation = None + + +class ComputeInstanceSshSettings(msrest.serialization.Model): + """Specifies policy and settings for SSH access. + + Variables are only populated by the server, and will be ignored when sending a request. + + :param 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 + public ssh port is open and accessible according to the VNet/subnet policy if applicable. + Possible values include: "Enabled", "Disabled". Default value: "Disabled". + :type ssh_public_access: str or ~azure_machine_learning_workspaces.models.SshPublicAccess + :ivar admin_user_name: Describes the admin user name. + :vartype admin_user_name: str + :ivar ssh_port: Describes the port for connecting through SSH. + :vartype ssh_port: int + :param admin_public_key: Specifies the SSH rsa public key file as a string. Use "ssh-keygen -t + rsa -b 2048" to generate your SSH key pairs. + :type admin_public_key: str + """ + + _validation = { + 'admin_user_name': {'readonly': True}, + 'ssh_port': {'readonly': True}, + } + + _attribute_map = { + 'ssh_public_access': {'key': 'sshPublicAccess', 'type': 'str'}, + 'admin_user_name': {'key': 'adminUserName', 'type': 'str'}, + 'ssh_port': {'key': 'sshPort', 'type': 'int'}, + 'admin_public_key': {'key': 'adminPublicKey', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstanceSshSettings, self).__init__(**kwargs) + self.ssh_public_access = kwargs.get('ssh_public_access', "Disabled") + self.admin_user_name = None + self.ssh_port = None + self.admin_public_key = kwargs.get('admin_public_key', None) + + +class Resource(msrest.serialization.Model): + """Azure Resource Manager resource envelope. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param identity: The identity of the resource. + :type identity: ~azure_machine_learning_workspaces.models.Identity + :param location: Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'identity': {'key': 'identity', 'type': 'Identity'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + } + + def __init__( + self, + **kwargs + ): + super(Resource, self).__init__(**kwargs) + self.id = None + self.name = None + self.identity = kwargs.get('identity', None) + self.location = kwargs.get('location', None) + self.type = None + self.tags = kwargs.get('tags', None) + self.sku = kwargs.get('sku', None) + + +class ComputeResource(Resource): + """Machine Learning compute object wrapped into ARM resource envelope. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param identity: The identity of the resource. + :type identity: ~azure_machine_learning_workspaces.models.Identity + :param location: Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + :param properties: Compute properties. + :type properties: ~azure_machine_learning_workspaces.models.Compute + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'identity': {'key': 'identity', 'type': 'Identity'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + 'properties': {'key': 'properties', 'type': 'Compute'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeResource, self).__init__(**kwargs) + self.properties = kwargs.get('properties', None) + + +class Databricks(Compute): + """A DataFactory compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: + :type properties: ~azure_machine_learning_workspaces.models.DatabricksProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'DatabricksProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(Databricks, self).__init__(**kwargs) + self.compute_type = 'Databricks' # type: str + self.properties = kwargs.get('properties', None) + + +class DatabricksComputeSecrets(ComputeSecrets): + """Secrets related to a Machine Learning compute based on Databricks. + + All required parameters must be populated in order to send to Azure. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param databricks_access_token: access token for databricks account. + :type databricks_access_token: str + """ + + _validation = { + 'compute_type': {'required': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'databricks_access_token': {'key': 'databricksAccessToken', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(DatabricksComputeSecrets, self).__init__(**kwargs) + self.compute_type = 'Databricks' # type: str + self.databricks_access_token = kwargs.get('databricks_access_token', None) + + +class DatabricksProperties(msrest.serialization.Model): + """DatabricksProperties. + + :param databricks_access_token: Databricks access token. + :type databricks_access_token: str + """ + + _attribute_map = { + 'databricks_access_token': {'key': 'databricksAccessToken', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(DatabricksProperties, self).__init__(**kwargs) + self.databricks_access_token = kwargs.get('databricks_access_token', None) + + +class DataFactory(Compute): + """A DataFactory compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + } + + def __init__( + self, + **kwargs + ): + super(DataFactory, self).__init__(**kwargs) + self.compute_type = 'DataFactory' # type: str + + +class DataLakeAnalytics(Compute): + """A DataLakeAnalytics compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: + :type properties: ~azure_machine_learning_workspaces.models.DataLakeAnalyticsProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'DataLakeAnalyticsProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(DataLakeAnalytics, self).__init__(**kwargs) + self.compute_type = 'DataLakeAnalytics' # type: str + self.properties = kwargs.get('properties', None) + + +class DataLakeAnalyticsProperties(msrest.serialization.Model): + """DataLakeAnalyticsProperties. + + :param data_lake_store_account_name: DataLake Store Account Name. + :type data_lake_store_account_name: str + """ + + _attribute_map = { + 'data_lake_store_account_name': {'key': 'dataLakeStoreAccountName', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(DataLakeAnalyticsProperties, self).__init__(**kwargs) + self.data_lake_store_account_name = kwargs.get('data_lake_store_account_name', None) + + +class EncryptionProperty(msrest.serialization.Model): + """EncryptionProperty. + + All required parameters must be populated in order to send to Azure. + + :param status: Required. Indicates whether or not the encryption is enabled for the workspace. + Possible values include: "Enabled", "Disabled". + :type status: str or ~azure_machine_learning_workspaces.models.EncryptionStatus + :param key_vault_properties: Required. Customer Key vault properties. + :type key_vault_properties: ~azure_machine_learning_workspaces.models.KeyVaultProperties + """ + + _validation = { + 'status': {'required': True}, + 'key_vault_properties': {'required': True}, + } + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'key_vault_properties': {'key': 'keyVaultProperties', 'type': 'KeyVaultProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(EncryptionProperty, self).__init__(**kwargs) + self.status = kwargs['status'] + self.key_vault_properties = kwargs['key_vault_properties'] + + +class ErrorDetail(msrest.serialization.Model): + """Error detail information. + + All required parameters must be populated in order to send to Azure. + + :param code: Required. Error code. + :type code: str + :param message: Required. Error message. + :type message: str + """ + + _validation = { + 'code': {'required': True}, + 'message': {'required': True}, + } + + _attribute_map = { + 'code': {'key': 'code', 'type': 'str'}, + 'message': {'key': 'message', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ErrorDetail, self).__init__(**kwargs) + self.code = kwargs['code'] + self.message = kwargs['message'] + + +class ErrorResponse(msrest.serialization.Model): + """Error response information. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar code: Error code. + :vartype code: str + :ivar message: Error message. + :vartype message: str + :ivar details: An array of error detail objects. + :vartype details: list[~azure_machine_learning_workspaces.models.ErrorDetail] + """ + + _validation = { + 'code': {'readonly': True}, + 'message': {'readonly': True}, + 'details': {'readonly': True}, + } + + _attribute_map = { + 'code': {'key': 'code', 'type': 'str'}, + 'message': {'key': 'message', 'type': 'str'}, + 'details': {'key': 'details', 'type': '[ErrorDetail]'}, + } + + def __init__( + self, + **kwargs + ): + super(ErrorResponse, self).__init__(**kwargs) + self.code = None + self.message = None + self.details = None + + +class EstimatedVmPrice(msrest.serialization.Model): + """The estimated price info for using a VM of a particular OS type, tier, etc. + + All required parameters must be populated in order to send to Azure. + + :param retail_price: Required. The price charged for using the VM. + :type retail_price: float + :param os_type: Required. Operating system type used by the VM. Possible values include: + "Linux", "Windows". + :type os_type: str or ~azure_machine_learning_workspaces.models.VmPriceOsType + :param vm_tier: Required. The type of the VM. Possible values include: "Standard", + "LowPriority", "Spot". + :type vm_tier: str or ~azure_machine_learning_workspaces.models.VmTier + """ + + _validation = { + 'retail_price': {'required': True}, + 'os_type': {'required': True}, + 'vm_tier': {'required': True}, + } + + _attribute_map = { + 'retail_price': {'key': 'retailPrice', 'type': 'float'}, + 'os_type': {'key': 'osType', 'type': 'str'}, + 'vm_tier': {'key': 'vmTier', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(EstimatedVmPrice, self).__init__(**kwargs) + self.retail_price = kwargs['retail_price'] + self.os_type = kwargs['os_type'] + self.vm_tier = kwargs['vm_tier'] + + +class EstimatedVmPrices(msrest.serialization.Model): + """The estimated price info for using a VM. + + All required parameters must be populated in order to send to Azure. + + :param billing_currency: Required. Three lettered code specifying the currency of the VM price. + Example: USD. Possible values include: "USD". + :type billing_currency: str or ~azure_machine_learning_workspaces.models.BillingCurrency + :param unit_of_measure: Required. The unit of time measurement for the specified VM price. + Example: OneHour. Possible values include: "OneHour". + :type unit_of_measure: str or ~azure_machine_learning_workspaces.models.UnitOfMeasure + :param values: Required. The list of estimated prices for using a VM of a particular OS type, + tier, etc. + :type values: list[~azure_machine_learning_workspaces.models.EstimatedVmPrice] + """ + + _validation = { + 'billing_currency': {'required': True}, + 'unit_of_measure': {'required': True}, + 'values': {'required': True}, + } + + _attribute_map = { + 'billing_currency': {'key': 'billingCurrency', 'type': 'str'}, + 'unit_of_measure': {'key': 'unitOfMeasure', 'type': 'str'}, + 'values': {'key': 'values', 'type': '[EstimatedVmPrice]'}, + } + + def __init__( + self, + **kwargs + ): + super(EstimatedVmPrices, self).__init__(**kwargs) + self.billing_currency = kwargs['billing_currency'] + self.unit_of_measure = kwargs['unit_of_measure'] + self.values = kwargs['values'] + + +class HdInsight(Compute): + """A HDInsight compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: + :type properties: ~azure_machine_learning_workspaces.models.HdInsightProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'HdInsightProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(HdInsight, self).__init__(**kwargs) + self.compute_type = 'HDInsight' # type: str + self.properties = kwargs.get('properties', None) + + +class HdInsightProperties(msrest.serialization.Model): + """HdInsightProperties. + + :param ssh_port: Port open for ssh connections on the master node of the cluster. + :type ssh_port: int + :param address: Public IP address of the master node of the cluster. + :type address: str + :param administrator_account: Admin credentials for master node of the cluster. + :type administrator_account: + ~azure_machine_learning_workspaces.models.VirtualMachineSshCredentials + """ + + _attribute_map = { + 'ssh_port': {'key': 'sshPort', 'type': 'int'}, + 'address': {'key': 'address', 'type': 'str'}, + 'administrator_account': {'key': 'administratorAccount', 'type': 'VirtualMachineSshCredentials'}, + } + + def __init__( + self, + **kwargs + ): + super(HdInsightProperties, self).__init__(**kwargs) + self.ssh_port = kwargs.get('ssh_port', None) + self.address = kwargs.get('address', None) + self.administrator_account = kwargs.get('administrator_account', None) + + +class Identity(msrest.serialization.Model): + """Identity for the resource. + + 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 principal ID of resource identity. + :vartype principal_id: str + :ivar tenant_id: The tenant ID of resource. + :vartype tenant_id: str + :param type: Required. The identity type. Possible values include: "SystemAssigned", + "SystemAssigned,UserAssigned", "UserAssigned", "None". + :type type: str or ~azure_machine_learning_workspaces.models.ResourceIdentityType + :param user_assigned_identities: The list of user identities associated with resource. The user + identity dictionary key references will be ARM resource ids in the form: + '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'. + :type user_assigned_identities: dict[str, + ~azure_machine_learning_workspaces.models.ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties] + """ + + _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': '{ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties}'}, + } + + def __init__( + self, + **kwargs + ): + super(Identity, self).__init__(**kwargs) + self.principal_id = None + self.tenant_id = None + self.type = kwargs['type'] + self.user_assigned_identities = kwargs.get('user_assigned_identities', None) + + +class KeyVaultProperties(msrest.serialization.Model): + """KeyVaultProperties. + + All required parameters must be populated in order to send to Azure. + + :param key_vault_arm_id: Required. The ArmId of the keyVault where the customer owned + encryption key is present. + :type key_vault_arm_id: str + :param key_identifier: Required. Key vault uri to access the encryption key. + :type key_identifier: str + :param identity_client_id: For future use - The client id of the identity which will be used to + access key vault. + :type identity_client_id: str + """ + + _validation = { + 'key_vault_arm_id': {'required': True}, + 'key_identifier': {'required': True}, + } + + _attribute_map = { + 'key_vault_arm_id': {'key': 'keyVaultArmId', 'type': 'str'}, + 'key_identifier': {'key': 'keyIdentifier', 'type': 'str'}, + 'identity_client_id': {'key': 'identityClientId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(KeyVaultProperties, self).__init__(**kwargs) + self.key_vault_arm_id = kwargs['key_vault_arm_id'] + self.key_identifier = kwargs['key_identifier'] + self.identity_client_id = kwargs.get('identity_client_id', None) + + +class ListAmlUserFeatureResult(msrest.serialization.Model): + """The List Aml user feature operation response. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The list of AML user facing features. + :vartype value: list[~azure_machine_learning_workspaces.models.AmlUserFeature] + :ivar next_link: The URI to fetch the next page of AML user features information. Call + ListNext() with this to fetch the next page of AML user features information. + :vartype next_link: str + """ + + _validation = { + 'value': {'readonly': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': '[AmlUserFeature]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ListAmlUserFeatureResult, self).__init__(**kwargs) + self.value = None + self.next_link = None + + +class ListUsagesResult(msrest.serialization.Model): + """The List Usages operation response. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The list of AML resource usages. + :vartype value: list[~azure_machine_learning_workspaces.models.Usage] + :ivar next_link: The URI to fetch the next page of AML resource usage information. Call + ListNext() with this to fetch the next page of AML resource usage information. + :vartype next_link: str + """ + + _validation = { + 'value': {'readonly': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': '[Usage]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ListUsagesResult, self).__init__(**kwargs) + self.value = None + self.next_link = None + + +class ListWorkspaceKeysResult(msrest.serialization.Model): + """ListWorkspaceKeysResult. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar user_storage_key: + :vartype user_storage_key: str + :ivar user_storage_resource_id: + :vartype user_storage_resource_id: str + :ivar app_insights_instrumentation_key: + :vartype app_insights_instrumentation_key: str + :ivar container_registry_credentials: + :vartype container_registry_credentials: + ~azure_machine_learning_workspaces.models.RegistryListCredentialsResult + :param notebook_access_keys: + :type notebook_access_keys: + ~azure_machine_learning_workspaces.models.NotebookListCredentialsResult + """ + + _validation = { + 'user_storage_key': {'readonly': True}, + 'user_storage_resource_id': {'readonly': True}, + 'app_insights_instrumentation_key': {'readonly': True}, + 'container_registry_credentials': {'readonly': True}, + } + + _attribute_map = { + 'user_storage_key': {'key': 'userStorageKey', 'type': 'str'}, + 'user_storage_resource_id': {'key': 'userStorageResourceId', 'type': 'str'}, + 'app_insights_instrumentation_key': {'key': 'appInsightsInstrumentationKey', 'type': 'str'}, + 'container_registry_credentials': {'key': 'containerRegistryCredentials', 'type': 'RegistryListCredentialsResult'}, + 'notebook_access_keys': {'key': 'notebookAccessKeys', 'type': 'NotebookListCredentialsResult'}, + } + + def __init__( + self, + **kwargs + ): + super(ListWorkspaceKeysResult, self).__init__(**kwargs) + self.user_storage_key = None + self.user_storage_resource_id = None + self.app_insights_instrumentation_key = None + self.container_registry_credentials = None + self.notebook_access_keys = kwargs.get('notebook_access_keys', None) + + +class ListWorkspaceQuotas(msrest.serialization.Model): + """The List WorkspaceQuotasByVMFamily operation response. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The list of Workspace Quotas by VM Family. + :vartype value: list[~azure_machine_learning_workspaces.models.ResourceQuota] + :ivar next_link: The URI to fetch the next page of workspace quota information by VM Family. + Call ListNext() with this to fetch the next page of Workspace Quota information. + :vartype next_link: str + """ + + _validation = { + 'value': {'readonly': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': '[ResourceQuota]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ListWorkspaceQuotas, self).__init__(**kwargs) + self.value = None + self.next_link = None + + +class MachineLearningServiceError(msrest.serialization.Model): + """Wrapper for error response to follow ARM guidelines. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar error: The error response. + :vartype error: ~azure_machine_learning_workspaces.models.ErrorResponse + """ + + _validation = { + 'error': {'readonly': True}, + } + + _attribute_map = { + 'error': {'key': 'error', 'type': 'ErrorResponse'}, + } + + def __init__( + self, + **kwargs + ): + super(MachineLearningServiceError, self).__init__(**kwargs) + self.error = None + + +class NodeStateCounts(msrest.serialization.Model): + """Counts of various compute node states on the amlCompute. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar idle_node_count: Number of compute nodes in idle state. + :vartype idle_node_count: int + :ivar running_node_count: Number of compute nodes which are running jobs. + :vartype running_node_count: int + :ivar preparing_node_count: Number of compute nodes which are being prepared. + :vartype preparing_node_count: int + :ivar unusable_node_count: Number of compute nodes which are in unusable state. + :vartype unusable_node_count: int + :ivar leaving_node_count: Number of compute nodes which are leaving the amlCompute. + :vartype leaving_node_count: int + :ivar preempted_node_count: Number of compute nodes which are in preempted state. + :vartype preempted_node_count: int + """ + + _validation = { + 'idle_node_count': {'readonly': True}, + 'running_node_count': {'readonly': True}, + 'preparing_node_count': {'readonly': True}, + 'unusable_node_count': {'readonly': True}, + 'leaving_node_count': {'readonly': True}, + 'preempted_node_count': {'readonly': True}, + } + + _attribute_map = { + 'idle_node_count': {'key': 'idleNodeCount', 'type': 'int'}, + 'running_node_count': {'key': 'runningNodeCount', 'type': 'int'}, + 'preparing_node_count': {'key': 'preparingNodeCount', 'type': 'int'}, + 'unusable_node_count': {'key': 'unusableNodeCount', 'type': 'int'}, + 'leaving_node_count': {'key': 'leavingNodeCount', 'type': 'int'}, + 'preempted_node_count': {'key': 'preemptedNodeCount', 'type': 'int'}, + } + + def __init__( + self, + **kwargs + ): + super(NodeStateCounts, self).__init__(**kwargs) + self.idle_node_count = None + self.running_node_count = None + self.preparing_node_count = None + self.unusable_node_count = None + self.leaving_node_count = None + self.preempted_node_count = None + + +class NotebookListCredentialsResult(msrest.serialization.Model): + """NotebookListCredentialsResult. + + :param primary_access_key: + :type primary_access_key: str + :param secondary_access_key: + :type secondary_access_key: str + """ + + _attribute_map = { + 'primary_access_key': {'key': 'primaryAccessKey', 'type': 'str'}, + 'secondary_access_key': {'key': 'secondaryAccessKey', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(NotebookListCredentialsResult, self).__init__(**kwargs) + self.primary_access_key = kwargs.get('primary_access_key', None) + self.secondary_access_key = kwargs.get('secondary_access_key', None) + + +class NotebookPreparationError(msrest.serialization.Model): + """NotebookPreparationError. + + :param error_message: + :type error_message: str + :param status_code: + :type status_code: int + """ + + _attribute_map = { + 'error_message': {'key': 'errorMessage', 'type': 'str'}, + 'status_code': {'key': 'statusCode', 'type': 'int'}, + } + + def __init__( + self, + **kwargs + ): + super(NotebookPreparationError, self).__init__(**kwargs) + self.error_message = kwargs.get('error_message', None) + self.status_code = kwargs.get('status_code', None) + + +class NotebookResourceInfo(msrest.serialization.Model): + """NotebookResourceInfo. + + :param fqdn: + :type fqdn: str + :param resource_id: the data plane resourceId that used to initialize notebook component. + :type resource_id: str + :param notebook_preparation_error: The error that occurs when preparing notebook. + :type notebook_preparation_error: + ~azure_machine_learning_workspaces.models.NotebookPreparationError + """ + + _attribute_map = { + 'fqdn': {'key': 'fqdn', 'type': 'str'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'notebook_preparation_error': {'key': 'notebookPreparationError', 'type': 'NotebookPreparationError'}, + } + + def __init__( + self, + **kwargs + ): + super(NotebookResourceInfo, self).__init__(**kwargs) + self.fqdn = kwargs.get('fqdn', None) + self.resource_id = kwargs.get('resource_id', None) + self.notebook_preparation_error = kwargs.get('notebook_preparation_error', None) + + +class Operation(msrest.serialization.Model): + """Azure Machine Learning workspace REST API operation. + + :param name: Operation name: {provider}/{resource}/{operation}. + :type name: str + :param display: Display name of operation. + :type display: ~azure_machine_learning_workspaces.models.OperationDisplay + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'display': {'key': 'display', 'type': 'OperationDisplay'}, + } + + def __init__( + self, + **kwargs + ): + super(Operation, self).__init__(**kwargs) + self.name = kwargs.get('name', None) + self.display = kwargs.get('display', None) + + +class OperationDisplay(msrest.serialization.Model): + """Display name of operation. + + :param provider: The resource provider name: Microsoft.MachineLearningExperimentation. + :type provider: str + :param resource: The resource on which the operation is performed. + :type resource: str + :param operation: The operation that users can perform. + :type operation: str + :param description: The description for the operation. + :type description: str + """ + + _attribute_map = { + 'provider': {'key': 'provider', 'type': 'str'}, + 'resource': {'key': 'resource', 'type': 'str'}, + 'operation': {'key': 'operation', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(OperationDisplay, self).__init__(**kwargs) + self.provider = kwargs.get('provider', None) + self.resource = kwargs.get('resource', None) + self.operation = kwargs.get('operation', None) + self.description = kwargs.get('description', None) + + +class OperationListResult(msrest.serialization.Model): + """An array of operations supported by the resource provider. + + :param value: List of AML workspace operations supported by the AML workspace resource + provider. + :type value: list[~azure_machine_learning_workspaces.models.Operation] + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[Operation]'}, + } + + def __init__( + self, + **kwargs + ): + super(OperationListResult, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + + +class PaginatedComputeResourcesList(msrest.serialization.Model): + """Paginated list of Machine Learning compute objects wrapped in ARM resource envelope. + + :param value: An array of Machine Learning compute objects wrapped in ARM resource envelope. + :type value: list[~azure_machine_learning_workspaces.models.ComputeResource] + :param next_link: A continuation link (absolute URI) to the next page of results in the list. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[ComputeResource]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(PaginatedComputeResourcesList, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + self.next_link = kwargs.get('next_link', None) + + +class PaginatedWorkspaceConnectionsList(msrest.serialization.Model): + """Paginated list of Workspace connection objects. + + :param value: An array of Workspace connection objects. + :type value: list[~azure_machine_learning_workspaces.models.WorkspaceConnection] + :param next_link: A continuation link (absolute URI) to the next page of results in the list. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[WorkspaceConnection]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(PaginatedWorkspaceConnectionsList, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + self.next_link = kwargs.get('next_link', None) + + +class Password(msrest.serialization.Model): + """Password. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar name: + :vartype name: str + :ivar value: + :vartype value: str + """ + + _validation = { + 'name': {'readonly': True}, + 'value': {'readonly': True}, + } + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'value': {'key': 'value', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(Password, self).__init__(**kwargs) + self.name = None + self.value = None + + +class PersonalComputeInstanceSettings(msrest.serialization.Model): + """Settings for a personal compute instance. + + :param assigned_user: A user explicitly assigned to a personal compute instance. + :type assigned_user: ~azure_machine_learning_workspaces.models.AssignedUser + """ + + _attribute_map = { + 'assigned_user': {'key': 'assignedUser', 'type': 'AssignedUser'}, + } + + def __init__( + self, + **kwargs + ): + super(PersonalComputeInstanceSettings, self).__init__(**kwargs) + self.assigned_user = kwargs.get('assigned_user', None) + + +class PrivateEndpoint(msrest.serialization.Model): + """The Private Endpoint resource. + + 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 + """ + + _validation = { + 'id': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(PrivateEndpoint, self).__init__(**kwargs) + self.id = None + + +class PrivateEndpointConnection(msrest.serialization.Model): + """The Private Endpoint Connection resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: ResourceId of the private endpoint connection. + :vartype id: str + :ivar name: Friendly name of the private endpoint connection. + :vartype name: str + :ivar type: Resource type of private endpoint connection. + :vartype type: str + :param private_endpoint: The resource of private end point. + :type private_endpoint: ~azure_machine_learning_workspaces.models.PrivateEndpoint + :param private_link_service_connection_state: A collection of information about the state of + the connection between service consumer and provider. + :type private_link_service_connection_state: + ~azure_machine_learning_workspaces.models.PrivateLinkServiceConnectionState + :ivar provisioning_state: The provisioning state of the private endpoint connection resource. + Possible values include: "Succeeded", "Creating", "Deleting", "Failed". + :vartype provisioning_state: str or + ~azure_machine_learning_workspaces.models.PrivateEndpointConnectionProvisioningState + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + 'provisioning_state': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'private_endpoint': {'key': 'properties.privateEndpoint', 'type': 'PrivateEndpoint'}, + 'private_link_service_connection_state': {'key': 'properties.privateLinkServiceConnectionState', 'type': 'PrivateLinkServiceConnectionState'}, + 'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(PrivateEndpointConnection, self).__init__(**kwargs) + self.id = None + self.name = None + self.type = None + self.private_endpoint = kwargs.get('private_endpoint', None) + self.private_link_service_connection_state = kwargs.get('private_link_service_connection_state', None) + self.provisioning_state = None + + +class PrivateLinkResource(Resource): + """A private link resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param identity: The identity of the resource. + :type identity: ~azure_machine_learning_workspaces.models.Identity + :param location: Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + :ivar group_id: The private link resource group id. + :vartype group_id: str + :ivar required_members: The private link resource required member names. + :vartype required_members: list[str] + :param required_zone_names: The private link resource Private link DNS zone name. + :type required_zone_names: list[str] + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + 'group_id': {'readonly': True}, + 'required_members': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'identity': {'key': 'identity', 'type': 'Identity'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + 'group_id': {'key': 'properties.groupId', 'type': 'str'}, + 'required_members': {'key': 'properties.requiredMembers', 'type': '[str]'}, + 'required_zone_names': {'key': 'properties.requiredZoneNames', 'type': '[str]'}, + } + + def __init__( + self, + **kwargs + ): + super(PrivateLinkResource, self).__init__(**kwargs) + self.group_id = None + self.required_members = None + self.required_zone_names = kwargs.get('required_zone_names', None) + + +class PrivateLinkResourceListResult(msrest.serialization.Model): + """A list of private link resources. + + :param value: Array of private link resources. + :type value: list[~azure_machine_learning_workspaces.models.PrivateLinkResource] + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[PrivateLinkResource]'}, + } + + def __init__( + self, + **kwargs + ): + super(PrivateLinkResourceListResult, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + + +class PrivateLinkServiceConnectionState(msrest.serialization.Model): + """A collection of information about the state of the connection between service consumer and provider. + + :param status: Indicates whether the connection has been Approved/Rejected/Removed by the owner + of the service. Possible values include: "Pending", "Approved", "Rejected", "Disconnected", + "Timeout". + :type status: str or + ~azure_machine_learning_workspaces.models.PrivateEndpointServiceConnectionStatus + :param description: The reason for approval/rejection of the connection. + :type description: str + :param actions_required: A message indicating if changes on the service provider require any + updates on the consumer. + :type actions_required: str + """ + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'actions_required': {'key': 'actionsRequired', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(PrivateLinkServiceConnectionState, self).__init__(**kwargs) + self.status = kwargs.get('status', None) + self.description = kwargs.get('description', None) + self.actions_required = kwargs.get('actions_required', None) + + +class QuotaBaseProperties(msrest.serialization.Model): + """The properties for Quota update or retrieval. + + :param id: Specifies the resource ID. + :type id: str + :param type: Specifies the resource type. + :type type: str + :param limit: The maximum permitted quota of the resource. + :type limit: long + :param unit: An enum describing the unit of quota measurement. Possible values include: + "Count". + :type unit: str or ~azure_machine_learning_workspaces.models.QuotaUnit + """ + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'limit': {'key': 'limit', 'type': 'long'}, + 'unit': {'key': 'unit', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(QuotaBaseProperties, self).__init__(**kwargs) + self.id = kwargs.get('id', None) + self.type = kwargs.get('type', None) + self.limit = kwargs.get('limit', None) + self.unit = kwargs.get('unit', None) + + +class QuotaUpdateParameters(msrest.serialization.Model): + """Quota update parameters. + + :param value: The list for update quota. + :type value: list[~azure_machine_learning_workspaces.models.QuotaBaseProperties] + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[QuotaBaseProperties]'}, + } + + def __init__( + self, + **kwargs + ): + super(QuotaUpdateParameters, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + + +class RegistryListCredentialsResult(msrest.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 + :param passwords: + :type passwords: list[~azure_machine_learning_workspaces.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, + **kwargs + ): + super(RegistryListCredentialsResult, self).__init__(**kwargs) + self.location = None + self.username = None + self.passwords = kwargs.get('passwords', None) + + +class ResourceId(msrest.serialization.Model): + """Represents a resource ID. For example, for a subnet, it is the resource URL for the subnet. + + All required parameters must be populated in order to send to Azure. + + :param id: Required. The ID of the resource. + :type id: str + """ + + _validation = { + 'id': {'required': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceId, self).__init__(**kwargs) + self.id = kwargs['id'] + + +class ResourceName(msrest.serialization.Model): + """The Resource Name. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The name of the resource. + :vartype value: str + :ivar localized_value: The localized name of the resource. + :vartype localized_value: str + """ + + _validation = { + 'value': {'readonly': True}, + 'localized_value': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': 'str'}, + 'localized_value': {'key': 'localizedValue', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceName, self).__init__(**kwargs) + self.value = None + self.localized_value = None + + +class ResourceQuota(msrest.serialization.Model): + """The quota assigned to a resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar type: Specifies the resource type. + :vartype type: str + :ivar name: Name of the resource. + :vartype name: ~azure_machine_learning_workspaces.models.ResourceName + :ivar limit: The maximum permitted quota of the resource. + :vartype limit: long + :ivar unit: An enum describing the unit of quota measurement. Possible values include: "Count". + :vartype unit: str or ~azure_machine_learning_workspaces.models.QuotaUnit + """ + + _validation = { + 'id': {'readonly': True}, + 'type': {'readonly': True}, + 'name': {'readonly': True}, + 'limit': {'readonly': True}, + 'unit': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'ResourceName'}, + 'limit': {'key': 'limit', 'type': 'long'}, + 'unit': {'key': 'unit', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceQuota, self).__init__(**kwargs) + self.id = None + self.type = None + self.name = None + self.limit = None + self.unit = None + + +class ResourceSkuLocationInfo(msrest.serialization.Model): + """ResourceSkuLocationInfo. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar location: Location of the SKU. + :vartype location: str + :ivar zones: List of availability zones where the SKU is supported. + :vartype zones: list[str] + :ivar zone_details: Details of capabilities available to a SKU in specific zones. + :vartype zone_details: list[~azure_machine_learning_workspaces.models.ResourceSkuZoneDetails] + """ + + _validation = { + 'location': {'readonly': True}, + 'zones': {'readonly': True}, + 'zone_details': {'readonly': True}, + } + + _attribute_map = { + 'location': {'key': 'location', 'type': 'str'}, + 'zones': {'key': 'zones', 'type': '[str]'}, + 'zone_details': {'key': 'zoneDetails', 'type': '[ResourceSkuZoneDetails]'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceSkuLocationInfo, self).__init__(**kwargs) + self.location = None + self.zones = None + self.zone_details = None + + +class ResourceSkuZoneDetails(msrest.serialization.Model): + """Describes The zonal capabilities of a SKU. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar name: The set of zones that the SKU is available in with the specified capabilities. + :vartype name: list[str] + :ivar capabilities: A list of capabilities that are available for the SKU in the specified list + of zones. + :vartype capabilities: list[~azure_machine_learning_workspaces.models.SkuCapability] + """ + + _validation = { + 'name': {'readonly': True}, + 'capabilities': {'readonly': True}, + } + + _attribute_map = { + 'name': {'key': 'name', 'type': '[str]'}, + 'capabilities': {'key': 'capabilities', 'type': '[SkuCapability]'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceSkuZoneDetails, self).__init__(**kwargs) + self.name = None + self.capabilities = None + + +class Restriction(msrest.serialization.Model): + """The restriction because of which SKU cannot be used. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar type: The type of restrictions. As of now only possible value for this is location. + :vartype type: str + :ivar values: The value of restrictions. If the restriction type is set to location. This would + be different locations where the SKU is restricted. + :vartype values: list[str] + :param reason_code: The reason for the restriction. Possible values include: "NotSpecified", + "NotAvailableForRegion", "NotAvailableForSubscription". + :type reason_code: str or ~azure_machine_learning_workspaces.models.ReasonCode + """ + + _validation = { + 'type': {'readonly': True}, + 'values': {'readonly': True}, + } + + _attribute_map = { + 'type': {'key': 'type', 'type': 'str'}, + 'values': {'key': 'values', 'type': '[str]'}, + 'reason_code': {'key': 'reasonCode', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(Restriction, self).__init__(**kwargs) + self.type = None + self.values = None + self.reason_code = kwargs.get('reason_code', None) + + +class ScaleSettings(msrest.serialization.Model): + """scale settings for AML Compute. + + All required parameters must be populated in order to send to Azure. + + :param max_node_count: Required. Max number of nodes to use. + :type max_node_count: int + :param min_node_count: Min number of nodes to use. + :type min_node_count: int + :param node_idle_time_before_scale_down: Node Idle Time before scaling down amlCompute. This + string needs to be in the RFC Format. + :type node_idle_time_before_scale_down: ~datetime.timedelta + """ + + _validation = { + 'max_node_count': {'required': True}, + } + + _attribute_map = { + 'max_node_count': {'key': 'maxNodeCount', 'type': 'int'}, + 'min_node_count': {'key': 'minNodeCount', 'type': 'int'}, + 'node_idle_time_before_scale_down': {'key': 'nodeIdleTimeBeforeScaleDown', 'type': 'duration'}, + } + + def __init__( + self, + **kwargs + ): + super(ScaleSettings, self).__init__(**kwargs) + self.max_node_count = kwargs['max_node_count'] + self.min_node_count = kwargs.get('min_node_count', 0) + self.node_idle_time_before_scale_down = kwargs.get('node_idle_time_before_scale_down', None) + + +class ServicePrincipalCredentials(msrest.serialization.Model): + """Service principal credentials. + + All required parameters must be populated in order to send to Azure. + + :param client_id: Required. Client Id. + :type client_id: str + :param client_secret: Required. Client secret. + :type client_secret: str + """ + + _validation = { + 'client_id': {'required': True}, + 'client_secret': {'required': True}, + } + + _attribute_map = { + 'client_id': {'key': 'clientId', 'type': 'str'}, + 'client_secret': {'key': 'clientSecret', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ServicePrincipalCredentials, self).__init__(**kwargs) + self.client_id = kwargs['client_id'] + self.client_secret = kwargs['client_secret'] + + +class SharedPrivateLinkResource(msrest.serialization.Model): + """SharedPrivateLinkResource. + + :param name: Unique name of the private link. + :type name: str + :param private_link_resource_id: The resource id that private link links to. + :type private_link_resource_id: str + :param group_id: The private link resource group id. + :type group_id: str + :param request_message: Request message. + :type request_message: str + :param status: Indicates whether the connection has been Approved/Rejected/Removed by the owner + of the service. Possible values include: "Pending", "Approved", "Rejected", "Disconnected", + "Timeout". + :type status: str or + ~azure_machine_learning_workspaces.models.PrivateEndpointServiceConnectionStatus + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'private_link_resource_id': {'key': 'properties.privateLinkResourceId', 'type': 'str'}, + 'group_id': {'key': 'properties.groupId', 'type': 'str'}, + 'request_message': {'key': 'properties.requestMessage', 'type': 'str'}, + 'status': {'key': 'properties.status', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(SharedPrivateLinkResource, self).__init__(**kwargs) + self.name = kwargs.get('name', None) + self.private_link_resource_id = kwargs.get('private_link_resource_id', None) + self.group_id = kwargs.get('group_id', None) + self.request_message = kwargs.get('request_message', None) + self.status = kwargs.get('status', None) + + +class Sku(msrest.serialization.Model): + """Sku of the resource. + + :param name: Name of the sku. + :type name: str + :param tier: Tier of the sku like Basic or Enterprise. + :type tier: str + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'tier': {'key': 'tier', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(Sku, self).__init__(**kwargs) + self.name = kwargs.get('name', None) + self.tier = kwargs.get('tier', None) + + +class SkuCapability(msrest.serialization.Model): + """Features/user capabilities associated with the sku. + + :param name: Capability/Feature ID. + :type name: str + :param value: Details about the feature/capability. + :type value: str + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'value': {'key': 'value', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(SkuCapability, self).__init__(**kwargs) + self.name = kwargs.get('name', None) + self.value = kwargs.get('value', None) + + +class SkuListResult(msrest.serialization.Model): + """List of skus with features. + + :param value: + :type value: list[~azure_machine_learning_workspaces.models.WorkspaceSku] + :param next_link: The URI to fetch the next page of Workspace Skus. Call ListNext() with this + URI to fetch the next page of Workspace Skus. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[WorkspaceSku]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(SkuListResult, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + self.next_link = kwargs.get('next_link', None) + + +class SkuSettings(msrest.serialization.Model): + """Describes Workspace Sku details and features. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar locations: The set of locations that the SKU is available. This will be supported and + registered Azure Geo Regions (e.g. West US, East US, Southeast Asia, etc.). + :vartype locations: list[str] + :ivar location_info: A list of locations and availability zones in those locations where the + SKU is available. + :vartype location_info: list[~azure_machine_learning_workspaces.models.ResourceSkuLocationInfo] + :ivar tier: Sku Tier like Basic or Enterprise. + :vartype tier: str + :ivar resource_type: + :vartype resource_type: str + :ivar name: + :vartype name: str + :ivar capabilities: List of features/user capabilities associated with the sku. + :vartype capabilities: list[~azure_machine_learning_workspaces.models.SkuCapability] + :param restrictions: The restrictions because of which SKU cannot be used. This is empty if + there are no restrictions. + :type restrictions: list[~azure_machine_learning_workspaces.models.Restriction] + """ + + _validation = { + 'locations': {'readonly': True}, + 'location_info': {'readonly': True}, + 'tier': {'readonly': True}, + 'resource_type': {'readonly': True}, + 'name': {'readonly': True}, + 'capabilities': {'readonly': True}, + } + + _attribute_map = { + 'locations': {'key': 'locations', 'type': '[str]'}, + 'location_info': {'key': 'locationInfo', 'type': '[ResourceSkuLocationInfo]'}, + 'tier': {'key': 'tier', 'type': 'str'}, + 'resource_type': {'key': 'resourceType', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'capabilities': {'key': 'capabilities', 'type': '[SkuCapability]'}, + 'restrictions': {'key': 'restrictions', 'type': '[Restriction]'}, + } + + def __init__( + self, + **kwargs + ): + super(SkuSettings, self).__init__(**kwargs) + self.locations = None + self.location_info = None + self.tier = None + self.resource_type = None + self.name = None + self.capabilities = None + self.restrictions = kwargs.get('restrictions', None) + + +class SslConfiguration(msrest.serialization.Model): + """The ssl configuration for scoring. + + :param status: Enable or disable ssl for scoring. Possible values include: "Disabled", + "Enabled", "Auto". + :type status: str or ~azure_machine_learning_workspaces.models.SslConfigurationStatus + :param cert: Cert data. + :type cert: str + :param key: Key data. + :type key: str + :param cname: CNAME of the cert. + :type cname: str + """ + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'cert': {'key': 'cert', 'type': 'str'}, + 'key': {'key': 'key', 'type': 'str'}, + 'cname': {'key': 'cname', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(SslConfiguration, self).__init__(**kwargs) + self.status = kwargs.get('status', None) + self.cert = kwargs.get('cert', None) + self.key = kwargs.get('key', None) + self.cname = kwargs.get('cname', None) + + +class SystemService(msrest.serialization.Model): + """A system service running on a compute. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar system_service_type: The type of this system service. + :vartype system_service_type: str + :ivar public_ip_address: Public IP address. + :vartype public_ip_address: str + :ivar version: The version for this type. + :vartype version: str + """ + + _validation = { + 'system_service_type': {'readonly': True}, + 'public_ip_address': {'readonly': True}, + 'version': {'readonly': True}, + } + + _attribute_map = { + 'system_service_type': {'key': 'systemServiceType', 'type': 'str'}, + 'public_ip_address': {'key': 'publicIpAddress', 'type': 'str'}, + 'version': {'key': 'version', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(SystemService, self).__init__(**kwargs) + self.system_service_type = None + self.public_ip_address = None + self.version = None + + +class UpdateWorkspaceQuotas(msrest.serialization.Model): + """The properties for update Quota response. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar type: Specifies the resource type. + :vartype type: str + :param limit: The maximum permitted quota of the resource. + :type limit: long + :ivar unit: An enum describing the unit of quota measurement. Possible values include: "Count". + :vartype unit: str or ~azure_machine_learning_workspaces.models.QuotaUnit + :param status: Status of update workspace quota. Possible values include: "Undefined", + "Success", "Failure", "InvalidQuotaBelowClusterMinimum", + "InvalidQuotaExceedsSubscriptionLimit", "InvalidVMFamilyName", "OperationNotSupportedForSku", + "OperationNotEnabledForRegion". + :type status: str or ~azure_machine_learning_workspaces.models.Status + """ + + _validation = { + 'id': {'readonly': True}, + 'type': {'readonly': True}, + 'unit': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'limit': {'key': 'limit', 'type': 'long'}, + 'unit': {'key': 'unit', 'type': 'str'}, + 'status': {'key': 'status', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(UpdateWorkspaceQuotas, self).__init__(**kwargs) + self.id = None + self.type = None + self.limit = kwargs.get('limit', None) + self.unit = None + self.status = kwargs.get('status', None) + + +class UpdateWorkspaceQuotasResult(msrest.serialization.Model): + """The result of update workspace quota. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The list of workspace quota update result. + :vartype value: list[~azure_machine_learning_workspaces.models.UpdateWorkspaceQuotas] + :ivar next_link: The URI to fetch the next page of workspace quota update result. Call + ListNext() with this to fetch the next page of Workspace Quota update result. + :vartype next_link: str + """ + + _validation = { + 'value': {'readonly': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': '[UpdateWorkspaceQuotas]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(UpdateWorkspaceQuotasResult, self).__init__(**kwargs) + self.value = None + self.next_link = None + + +class Usage(msrest.serialization.Model): + """Describes AML Resource Usage. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar type: Specifies the resource type. + :vartype type: str + :ivar unit: An enum describing the unit of usage measurement. Possible values include: "Count". + :vartype unit: str or ~azure_machine_learning_workspaces.models.UsageUnit + :ivar current_value: The current usage of the resource. + :vartype current_value: long + :ivar limit: The maximum permitted usage of the resource. + :vartype limit: long + :ivar name: The name of the type of usage. + :vartype name: ~azure_machine_learning_workspaces.models.UsageName + """ + + _validation = { + 'id': {'readonly': True}, + 'type': {'readonly': True}, + 'unit': {'readonly': True}, + 'current_value': {'readonly': True}, + 'limit': {'readonly': True}, + 'name': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'unit': {'key': 'unit', 'type': 'str'}, + 'current_value': {'key': 'currentValue', 'type': 'long'}, + 'limit': {'key': 'limit', 'type': 'long'}, + 'name': {'key': 'name', 'type': 'UsageName'}, + } + + def __init__( + self, + **kwargs + ): + super(Usage, self).__init__(**kwargs) + self.id = None + self.type = None + self.unit = None + self.current_value = None + self.limit = None + self.name = None + + +class UsageName(msrest.serialization.Model): + """The Usage Names. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The name of the resource. + :vartype value: str + :ivar localized_value: The localized name of the resource. + :vartype localized_value: str + """ + + _validation = { + 'value': {'readonly': True}, + 'localized_value': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': 'str'}, + 'localized_value': {'key': 'localizedValue', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(UsageName, self).__init__(**kwargs) + self.value = None + self.localized_value = None + + +class UserAccountCredentials(msrest.serialization.Model): + """Settings for user account that gets created on each on the nodes of a compute. + + All required parameters must be populated in order to send to Azure. + + :param admin_user_name: Required. Name of the administrator user account which can be used to + SSH to nodes. + :type admin_user_name: str + :param admin_user_ssh_public_key: SSH public key of the administrator user account. + :type admin_user_ssh_public_key: str + :param admin_user_password: Password of the administrator user account. + :type admin_user_password: str + """ + + _validation = { + 'admin_user_name': {'required': True}, + } + + _attribute_map = { + 'admin_user_name': {'key': 'adminUserName', 'type': 'str'}, + 'admin_user_ssh_public_key': {'key': 'adminUserSshPublicKey', 'type': 'str'}, + 'admin_user_password': {'key': 'adminUserPassword', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(UserAccountCredentials, self).__init__(**kwargs) + self.admin_user_name = kwargs['admin_user_name'] + self.admin_user_ssh_public_key = kwargs.get('admin_user_ssh_public_key', None) + self.admin_user_password = kwargs.get('admin_user_password', None) + + +class VirtualMachine(Compute): + """A Machine Learning compute based on Azure Virtual Machines. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: + :type properties: ~azure_machine_learning_workspaces.models.VirtualMachineProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'VirtualMachineProperties'}, + } + + def __init__( + self, + **kwargs + ): + super(VirtualMachine, self).__init__(**kwargs) + self.compute_type = 'VirtualMachine' # type: str + self.properties = kwargs.get('properties', None) + + +class VirtualMachineProperties(msrest.serialization.Model): + """VirtualMachineProperties. + + :param virtual_machine_size: Virtual Machine size. + :type virtual_machine_size: str + :param ssh_port: Port open for ssh connections. + :type ssh_port: int + :param address: Public IP address of the virtual machine. + :type address: str + :param administrator_account: Admin credentials for virtual machine. + :type administrator_account: + ~azure_machine_learning_workspaces.models.VirtualMachineSshCredentials + """ + + _attribute_map = { + 'virtual_machine_size': {'key': 'virtualMachineSize', 'type': 'str'}, + 'ssh_port': {'key': 'sshPort', 'type': 'int'}, + 'address': {'key': 'address', 'type': 'str'}, + 'administrator_account': {'key': 'administratorAccount', 'type': 'VirtualMachineSshCredentials'}, + } + + def __init__( + self, + **kwargs + ): + super(VirtualMachineProperties, self).__init__(**kwargs) + self.virtual_machine_size = kwargs.get('virtual_machine_size', None) + self.ssh_port = kwargs.get('ssh_port', None) + self.address = kwargs.get('address', None) + self.administrator_account = kwargs.get('administrator_account', None) + + +class VirtualMachineSecrets(ComputeSecrets): + """Secrets related to a Machine Learning compute based on AKS. + + All required parameters must be populated in order to send to Azure. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param administrator_account: Admin credentials for virtual machine. + :type administrator_account: + ~azure_machine_learning_workspaces.models.VirtualMachineSshCredentials + """ + + _validation = { + 'compute_type': {'required': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'administrator_account': {'key': 'administratorAccount', 'type': 'VirtualMachineSshCredentials'}, + } + + def __init__( + self, + **kwargs + ): + super(VirtualMachineSecrets, self).__init__(**kwargs) + self.compute_type = 'VirtualMachine' # type: str + self.administrator_account = kwargs.get('administrator_account', None) + + +class VirtualMachineSize(msrest.serialization.Model): + """Describes the properties of a VM size. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar name: The name of the virtual machine size. + :vartype name: str + :ivar family: The family name of the virtual machine size. + :vartype family: str + :ivar v_cp_us: The number of vCPUs supported by the virtual machine size. + :vartype v_cp_us: int + :ivar gpus: The number of gPUs supported by the virtual machine size. + :vartype gpus: int + :ivar os_vhd_size_mb: The OS VHD disk size, in MB, allowed by the virtual machine size. + :vartype os_vhd_size_mb: int + :ivar max_resource_volume_mb: The resource volume size, in MB, allowed by the virtual machine + size. + :vartype max_resource_volume_mb: int + :ivar memory_gb: The amount of memory, in GB, supported by the virtual machine size. + :vartype memory_gb: float + :ivar low_priority_capable: Specifies if the virtual machine size supports low priority VMs. + :vartype low_priority_capable: bool + :ivar premium_io: Specifies if the virtual machine size supports premium IO. + :vartype premium_io: bool + :param estimated_vm_prices: The estimated price information for using a VM. + :type estimated_vm_prices: ~azure_machine_learning_workspaces.models.EstimatedVmPrices + :param supported_compute_types: Specifies the compute types supported by the virtual machine + size. + :type supported_compute_types: list[str] + """ + + _validation = { + 'name': {'readonly': True}, + 'family': {'readonly': True}, + 'v_cp_us': {'readonly': True}, + 'gpus': {'readonly': True}, + 'os_vhd_size_mb': {'readonly': True}, + 'max_resource_volume_mb': {'readonly': True}, + 'memory_gb': {'readonly': True}, + 'low_priority_capable': {'readonly': True}, + 'premium_io': {'readonly': True}, + } + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'family': {'key': 'family', 'type': 'str'}, + 'v_cp_us': {'key': 'vCPUs', 'type': 'int'}, + 'gpus': {'key': 'gpus', 'type': 'int'}, + 'os_vhd_size_mb': {'key': 'osVhdSizeMB', 'type': 'int'}, + 'max_resource_volume_mb': {'key': 'maxResourceVolumeMB', 'type': 'int'}, + 'memory_gb': {'key': 'memoryGB', 'type': 'float'}, + 'low_priority_capable': {'key': 'lowPriorityCapable', 'type': 'bool'}, + 'premium_io': {'key': 'premiumIO', 'type': 'bool'}, + 'estimated_vm_prices': {'key': 'estimatedVMPrices', 'type': 'EstimatedVmPrices'}, + 'supported_compute_types': {'key': 'supportedComputeTypes', 'type': '[str]'}, + } + + def __init__( + self, + **kwargs + ): + super(VirtualMachineSize, self).__init__(**kwargs) + self.name = None + self.family = None + self.v_cp_us = None + self.gpus = None + self.os_vhd_size_mb = None + self.max_resource_volume_mb = None + self.memory_gb = None + self.low_priority_capable = None + self.premium_io = None + self.estimated_vm_prices = kwargs.get('estimated_vm_prices', None) + self.supported_compute_types = kwargs.get('supported_compute_types', None) + + +class VirtualMachineSizeListResult(msrest.serialization.Model): + """The List Virtual Machine size operation response. + + :param aml_compute: The list of virtual machine sizes supported by AmlCompute. + :type aml_compute: list[~azure_machine_learning_workspaces.models.VirtualMachineSize] + """ + + _attribute_map = { + 'aml_compute': {'key': 'amlCompute', 'type': '[VirtualMachineSize]'}, + } + + def __init__( + self, + **kwargs + ): + super(VirtualMachineSizeListResult, self).__init__(**kwargs) + self.aml_compute = kwargs.get('aml_compute', None) + + +class VirtualMachineSshCredentials(msrest.serialization.Model): + """Admin credentials for virtual machine. + + :param username: Username of admin account. + :type username: str + :param password: Password of admin account. + :type password: str + :param public_key_data: Public key data. + :type public_key_data: str + :param private_key_data: Private key data. + :type private_key_data: str + """ + + _attribute_map = { + 'username': {'key': 'username', 'type': 'str'}, + 'password': {'key': 'password', 'type': 'str'}, + 'public_key_data': {'key': 'publicKeyData', 'type': 'str'}, + 'private_key_data': {'key': 'privateKeyData', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(VirtualMachineSshCredentials, self).__init__(**kwargs) + self.username = kwargs.get('username', None) + self.password = kwargs.get('password', None) + self.public_key_data = kwargs.get('public_key_data', None) + self.private_key_data = kwargs.get('private_key_data', None) + + +class Workspace(Resource): + """An object that represents a machine learning workspace. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param identity: The identity of the resource. + :type identity: ~azure_machine_learning_workspaces.models.Identity + :param location: Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + :ivar workspace_id: The immutable id associated with this workspace. + :vartype workspace_id: str + :param description: The description of this workspace. + :type description: str + :param friendly_name: The friendly name for this workspace. This name in mutable. + :type friendly_name: str + :ivar creation_time: The creation time of the machine learning workspace in ISO8601 format. + :vartype creation_time: ~datetime.datetime + :param key_vault: ARM id of the key vault associated with this workspace. This cannot be + changed once the workspace has been created. + :type key_vault: str + :param application_insights: ARM id of the application insights associated with this workspace. + This cannot be changed once the workspace has been created. + :type application_insights: str + :param container_registry: ARM id of the container registry associated with this workspace. + This cannot be changed once the workspace has been created. + :type container_registry: str + :param storage_account: ARM id of the storage account associated with this workspace. This + cannot be changed once the workspace has been created. + :type storage_account: str + :param discovery_url: Url for the discovery service to identify regional endpoints for machine + learning experimentation services. + :type discovery_url: str + :ivar provisioning_state: The current deployment state of workspace resource. The + provisioningState is to indicate states for resource provisioning. Possible values include: + "Unknown", "Updating", "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param encryption: The encryption settings of Azure ML workspace. + :type encryption: ~azure_machine_learning_workspaces.models.EncryptionProperty + :param hbi_workspace: The flag to signal HBI data in the workspace and reduce diagnostic data + collected by the service. + :type hbi_workspace: bool + :ivar service_provisioned_resource_group: The name of the managed resource group created by + workspace RP in customer subscription if the workspace is CMK workspace. + :vartype service_provisioned_resource_group: str + :ivar private_link_count: Count of private connections in the workspace. + :vartype private_link_count: int + :param image_build_compute: The compute name for image build. + :type image_build_compute: str + :param allow_public_access_when_behind_vnet: The flag to indicate whether to allow public + access when behind VNet. + :type allow_public_access_when_behind_vnet: bool + :ivar private_endpoint_connections: The list of private endpoint connections in the workspace. + :vartype private_endpoint_connections: + list[~azure_machine_learning_workspaces.models.PrivateEndpointConnection] + :param shared_private_link_resources: The list of shared private link resources in this + workspace. + :type shared_private_link_resources: + list[~azure_machine_learning_workspaces.models.SharedPrivateLinkResource] + :ivar notebook_info: The notebook info of Azure ML workspace. + :vartype notebook_info: ~azure_machine_learning_workspaces.models.NotebookResourceInfo + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + 'workspace_id': {'readonly': True}, + 'creation_time': {'readonly': True}, + 'provisioning_state': {'readonly': True}, + 'service_provisioned_resource_group': {'readonly': True}, + 'private_link_count': {'readonly': True}, + 'private_endpoint_connections': {'readonly': True}, + 'notebook_info': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'identity': {'key': 'identity', 'type': 'Identity'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + 'workspace_id': {'key': 'properties.workspaceId', 'type': 'str'}, + 'description': {'key': 'properties.description', 'type': 'str'}, + 'friendly_name': {'key': 'properties.friendlyName', 'type': 'str'}, + 'creation_time': {'key': 'properties.creationTime', 'type': 'iso-8601'}, + 'key_vault': {'key': 'properties.keyVault', 'type': 'str'}, + 'application_insights': {'key': 'properties.applicationInsights', 'type': 'str'}, + 'container_registry': {'key': 'properties.containerRegistry', 'type': 'str'}, + 'storage_account': {'key': 'properties.storageAccount', 'type': 'str'}, + 'discovery_url': {'key': 'properties.discoveryUrl', 'type': 'str'}, + 'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'}, + 'encryption': {'key': 'properties.encryption', 'type': 'EncryptionProperty'}, + 'hbi_workspace': {'key': 'properties.hbiWorkspace', 'type': 'bool'}, + 'service_provisioned_resource_group': {'key': 'properties.serviceProvisionedResourceGroup', 'type': 'str'}, + 'private_link_count': {'key': 'properties.privateLinkCount', 'type': 'int'}, + 'image_build_compute': {'key': 'properties.imageBuildCompute', 'type': 'str'}, + 'allow_public_access_when_behind_vnet': {'key': 'properties.allowPublicAccessWhenBehindVnet', 'type': 'bool'}, + 'private_endpoint_connections': {'key': 'properties.privateEndpointConnections', 'type': '[PrivateEndpointConnection]'}, + 'shared_private_link_resources': {'key': 'properties.sharedPrivateLinkResources', 'type': '[SharedPrivateLinkResource]'}, + 'notebook_info': {'key': 'properties.notebookInfo', 'type': 'NotebookResourceInfo'}, + } + + def __init__( + self, + **kwargs + ): + super(Workspace, self).__init__(**kwargs) + self.workspace_id = None + self.description = kwargs.get('description', None) + self.friendly_name = kwargs.get('friendly_name', None) + self.creation_time = None + self.key_vault = kwargs.get('key_vault', None) + self.application_insights = kwargs.get('application_insights', None) + self.container_registry = kwargs.get('container_registry', None) + self.storage_account = kwargs.get('storage_account', None) + self.discovery_url = kwargs.get('discovery_url', None) + self.provisioning_state = None + self.encryption = kwargs.get('encryption', None) + self.hbi_workspace = kwargs.get('hbi_workspace', False) + self.service_provisioned_resource_group = None + self.private_link_count = None + self.image_build_compute = kwargs.get('image_build_compute', None) + self.allow_public_access_when_behind_vnet = kwargs.get('allow_public_access_when_behind_vnet', False) + self.private_endpoint_connections = None + self.shared_private_link_resources = kwargs.get('shared_private_link_resources', None) + self.notebook_info = None + + +class WorkspaceConnection(msrest.serialization.Model): + """Workspace connection. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: ResourceId of the workspace connection. + :vartype id: str + :ivar name: Friendly name of the workspace connection. + :vartype name: str + :ivar type: Resource type of workspace connection. + :vartype type: str + :param category: Category of the workspace connection. + :type category: str + :param target: Target of the workspace connection. + :type target: str + :param auth_type: Authorization type of the workspace connection. + :type auth_type: str + :param value: Value details of the workspace connection. + :type value: str + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'category': {'key': 'properties.category', 'type': 'str'}, + 'target': {'key': 'properties.target', 'type': 'str'}, + 'auth_type': {'key': 'properties.authType', 'type': 'str'}, + 'value': {'key': 'properties.value', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(WorkspaceConnection, self).__init__(**kwargs) + self.id = None + self.name = None + self.type = None + self.category = kwargs.get('category', None) + self.target = kwargs.get('target', None) + self.auth_type = kwargs.get('auth_type', None) + self.value = kwargs.get('value', None) + + +class WorkspaceConnectionDto(msrest.serialization.Model): + """object used for creating workspace connection. + + :param name: Friendly name of the workspace connection. + :type name: str + :param category: Category of the workspace connection. + :type category: str + :param target: Target of the workspace connection. + :type target: str + :param auth_type: Authorization type of the workspace connection. + :type auth_type: str + :param value: Value details of the workspace connection. + :type value: str + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'category': {'key': 'properties.category', 'type': 'str'}, + 'target': {'key': 'properties.target', 'type': 'str'}, + 'auth_type': {'key': 'properties.authType', 'type': 'str'}, + 'value': {'key': 'properties.value', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(WorkspaceConnectionDto, self).__init__(**kwargs) + self.name = kwargs.get('name', None) + self.category = kwargs.get('category', None) + self.target = kwargs.get('target', None) + self.auth_type = kwargs.get('auth_type', None) + self.value = kwargs.get('value', None) + + +class WorkspaceListResult(msrest.serialization.Model): + """The result of a request to list machine learning workspaces. + + :param 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. + :type value: list[~azure_machine_learning_workspaces.models.Workspace] + :param next_link: The URI that can be used to request the next list of machine learning + workspaces. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[Workspace]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(WorkspaceListResult, self).__init__(**kwargs) + self.value = kwargs.get('value', None) + self.next_link = kwargs.get('next_link', None) + + +class WorkspaceSku(msrest.serialization.Model): + """AML workspace sku information. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar resource_type: + :vartype resource_type: str + :ivar skus: The list of workspace sku settings. + :vartype skus: list[~azure_machine_learning_workspaces.models.SkuSettings] + """ + + _validation = { + 'resource_type': {'readonly': True}, + 'skus': {'readonly': True}, + } + + _attribute_map = { + 'resource_type': {'key': 'resourceType', 'type': 'str'}, + 'skus': {'key': 'skus', 'type': '[SkuSettings]'}, + } + + def __init__( + self, + **kwargs + ): + super(WorkspaceSku, self).__init__(**kwargs) + self.resource_type = None + self.skus = None + + +class WorkspaceUpdateParameters(msrest.serialization.Model): + """The parameters for updating a machine learning workspace. + + :param tags: A set of tags. The resource tags for the machine learning workspace. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + :param description: The description of this workspace. + :type description: str + :param friendly_name: The friendly name for this workspace. + :type friendly_name: str + """ + + _attribute_map = { + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + 'description': {'key': 'properties.description', 'type': 'str'}, + 'friendly_name': {'key': 'properties.friendlyName', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(WorkspaceUpdateParameters, self).__init__(**kwargs) + self.tags = kwargs.get('tags', None) + self.sku = kwargs.get('sku', None) + self.description = kwargs.get('description', None) + self.friendly_name = kwargs.get('friendly_name', None) diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_models_py3.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_models_py3.py new file mode 100644 index 00000000000..0eaa2638e0e --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/models/_models_py3.py @@ -0,0 +1,4007 @@ +# 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. +# -------------------------------------------------------------------------- + +import datetime +from typing import Dict, List, Optional, Union + +from azure.core.exceptions import HttpResponseError +import msrest.serialization + +from ._azure_machine_learning_workspaces_enums import * + + +class Compute(msrest.serialization.Model): + """Machine Learning compute object. + + You probably want to use the sub-classes and not this class directly. Known + sub-classes are: Aks, AmlCompute, ComputeInstance, DataFactory, DataLakeAnalytics, Databricks, HdInsight, VirtualMachine. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + } + + _subtype_map = { + 'compute_type': {'AKS': 'Aks', 'AmlCompute': 'AmlCompute', 'ComputeInstance': 'ComputeInstance', 'DataFactory': 'DataFactory', 'DataLakeAnalytics': 'DataLakeAnalytics', 'Databricks': 'Databricks', 'HDInsight': 'HdInsight', 'VirtualMachine': 'VirtualMachine'} + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + **kwargs + ): + super(Compute, self).__init__(**kwargs) + self.compute_type = None # type: Optional[str] + self.compute_location = compute_location + self.provisioning_state = None + self.description = description + self.created_on = None + self.modified_on = None + self.resource_id = resource_id + self.provisioning_errors = None + self.is_attached_compute = None + + +class Aks(Compute): + """A Machine Learning compute based on AKS. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: AKS properties. + :type properties: ~azure_machine_learning_workspaces.models.AksProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'AksProperties'}, + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + properties: Optional["AksProperties"] = None, + **kwargs + ): + super(Aks, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs) + self.compute_type = 'AKS' # type: str + self.properties = properties + + +class ComputeSecrets(msrest.serialization.Model): + """Secrets related to a Machine Learning compute. Might differ for every type of compute. + + You probably want to use the sub-classes and not this class directly. Known + sub-classes are: AksComputeSecrets, DatabricksComputeSecrets, VirtualMachineSecrets. + + All required parameters must be populated in order to send to Azure. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + """ + + _validation = { + 'compute_type': {'required': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + } + + _subtype_map = { + 'compute_type': {'AKS': 'AksComputeSecrets', 'Databricks': 'DatabricksComputeSecrets', 'VirtualMachine': 'VirtualMachineSecrets'} + } + + def __init__( + self, + **kwargs + ): + super(ComputeSecrets, self).__init__(**kwargs) + self.compute_type = None # type: Optional[str] + + +class AksComputeSecrets(ComputeSecrets): + """Secrets related to a Machine Learning compute based on AKS. + + All required parameters must be populated in order to send to Azure. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param user_kube_config: Content of kubeconfig file that can be used to connect to the + Kubernetes cluster. + :type user_kube_config: str + :param admin_kube_config: Content of kubeconfig file that can be used to connect to the + Kubernetes cluster. + :type admin_kube_config: str + :param image_pull_secret_name: Image registry pull secret. + :type image_pull_secret_name: str + """ + + _validation = { + 'compute_type': {'required': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'user_kube_config': {'key': 'userKubeConfig', 'type': 'str'}, + 'admin_kube_config': {'key': 'adminKubeConfig', 'type': 'str'}, + 'image_pull_secret_name': {'key': 'imagePullSecretName', 'type': 'str'}, + } + + def __init__( + self, + *, + user_kube_config: Optional[str] = None, + admin_kube_config: Optional[str] = None, + image_pull_secret_name: Optional[str] = None, + **kwargs + ): + super(AksComputeSecrets, self).__init__(**kwargs) + self.compute_type = 'AKS' # type: str + self.user_kube_config = user_kube_config + self.admin_kube_config = admin_kube_config + self.image_pull_secret_name = image_pull_secret_name + + +class AksNetworkingConfiguration(msrest.serialization.Model): + """Advance configuration for AKS networking. + + :param subnet_id: Virtual network subnet resource ID the compute nodes belong to. + :type subnet_id: str + :param service_cidr: A CIDR notation IP range from which to assign service cluster IPs. It must + not overlap with any Subnet IP ranges. + :type service_cidr: str + :param dns_service_ip: An IP address assigned to the Kubernetes DNS service. It must be within + the Kubernetes service address range specified in serviceCidr. + :type dns_service_ip: str + :param docker_bridge_cidr: A CIDR notation IP range assigned to the Docker bridge network. It + must not overlap with any Subnet IP ranges or the Kubernetes service address range. + :type docker_bridge_cidr: str + """ + + _validation = { + 'service_cidr': {'pattern': r'^([0-9]{1,3}\.){3}[0-9]{1,3}(\/([0-9]|[1-2][0-9]|3[0-2]))?$'}, + 'dns_service_ip': {'pattern': r'^(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)$'}, + 'docker_bridge_cidr': {'pattern': r'^([0-9]{1,3}\.){3}[0-9]{1,3}(\/([0-9]|[1-2][0-9]|3[0-2]))?$'}, + } + + _attribute_map = { + 'subnet_id': {'key': 'subnetId', 'type': 'str'}, + 'service_cidr': {'key': 'serviceCidr', 'type': 'str'}, + 'dns_service_ip': {'key': 'dnsServiceIP', 'type': 'str'}, + 'docker_bridge_cidr': {'key': 'dockerBridgeCidr', 'type': 'str'}, + } + + def __init__( + self, + *, + subnet_id: Optional[str] = None, + service_cidr: Optional[str] = None, + dns_service_ip: Optional[str] = None, + docker_bridge_cidr: Optional[str] = None, + **kwargs + ): + super(AksNetworkingConfiguration, self).__init__(**kwargs) + self.subnet_id = subnet_id + self.service_cidr = service_cidr + self.dns_service_ip = dns_service_ip + self.docker_bridge_cidr = docker_bridge_cidr + + +class AksProperties(msrest.serialization.Model): + """AKS properties. + + Variables are only populated by the server, and will be ignored when sending a request. + + :param cluster_fqdn: Cluster full qualified domain name. + :type cluster_fqdn: str + :ivar system_services: System services. + :vartype system_services: list[~azure_machine_learning_workspaces.models.SystemService] + :param agent_count: Number of agents. + :type agent_count: int + :param agent_vm_size: Agent virtual machine size. + :type agent_vm_size: str + :param ssl_configuration: SSL configuration. + :type ssl_configuration: ~azure_machine_learning_workspaces.models.SslConfiguration + :param aks_networking_configuration: AKS networking configuration for vnet. + :type aks_networking_configuration: + ~azure_machine_learning_workspaces.models.AksNetworkingConfiguration + """ + + _validation = { + 'system_services': {'readonly': True}, + 'agent_count': {'minimum': 1}, + } + + _attribute_map = { + 'cluster_fqdn': {'key': 'clusterFqdn', 'type': 'str'}, + 'system_services': {'key': 'systemServices', 'type': '[SystemService]'}, + 'agent_count': {'key': 'agentCount', 'type': 'int'}, + 'agent_vm_size': {'key': 'agentVmSize', 'type': 'str'}, + 'ssl_configuration': {'key': 'sslConfiguration', 'type': 'SslConfiguration'}, + 'aks_networking_configuration': {'key': 'aksNetworkingConfiguration', 'type': 'AksNetworkingConfiguration'}, + } + + def __init__( + self, + *, + cluster_fqdn: Optional[str] = None, + agent_count: Optional[int] = None, + agent_vm_size: Optional[str] = None, + ssl_configuration: Optional["SslConfiguration"] = None, + aks_networking_configuration: Optional["AksNetworkingConfiguration"] = None, + **kwargs + ): + super(AksProperties, self).__init__(**kwargs) + self.cluster_fqdn = cluster_fqdn + self.system_services = None + self.agent_count = agent_count + self.agent_vm_size = agent_vm_size + self.ssl_configuration = ssl_configuration + self.aks_networking_configuration = aks_networking_configuration + + +class AmlCompute(Compute): + """An Azure Machine Learning compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: AML Compute properties. + :type properties: ~azure_machine_learning_workspaces.models.AmlComputeProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'AmlComputeProperties'}, + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + properties: Optional["AmlComputeProperties"] = None, + **kwargs + ): + super(AmlCompute, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs) + self.compute_type = 'AmlCompute' # type: str + self.properties = properties + + +class AmlComputeNodeInformation(msrest.serialization.Model): + """Compute node information related to a AmlCompute. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar node_id: ID of the compute node. + :vartype node_id: str + :ivar private_ip_address: Private IP address of the compute node. + :vartype private_ip_address: str + :ivar public_ip_address: Public IP address of the compute node. + :vartype public_ip_address: str + :ivar port: SSH port number of the node. + :vartype port: int + :ivar node_state: State of the compute node. Values are idle, running, preparing, unusable, + leaving and preempted. Possible values include: "idle", "running", "preparing", "unusable", + "leaving", "preempted". + :vartype node_state: str or ~azure_machine_learning_workspaces.models.NodeState + :ivar run_id: ID of the Experiment running on the node, if any else null. + :vartype run_id: str + """ + + _validation = { + 'node_id': {'readonly': True}, + 'private_ip_address': {'readonly': True}, + 'public_ip_address': {'readonly': True}, + 'port': {'readonly': True}, + 'node_state': {'readonly': True}, + 'run_id': {'readonly': True}, + } + + _attribute_map = { + 'node_id': {'key': 'nodeId', 'type': 'str'}, + 'private_ip_address': {'key': 'privateIpAddress', 'type': 'str'}, + 'public_ip_address': {'key': 'publicIpAddress', 'type': 'str'}, + 'port': {'key': 'port', 'type': 'int'}, + 'node_state': {'key': 'nodeState', 'type': 'str'}, + 'run_id': {'key': 'runId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(AmlComputeNodeInformation, self).__init__(**kwargs) + self.node_id = None + self.private_ip_address = None + self.public_ip_address = None + self.port = None + self.node_state = None + self.run_id = None + + +class ComputeNodesInformation(msrest.serialization.Model): + """Compute nodes information related to a Machine Learning compute. Might differ for every type of compute. + + You probably want to use the sub-classes and not this class directly. Known + sub-classes are: AmlComputeNodesInformation. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :ivar next_link: The continuation token. + :vartype next_link: str + """ + + _validation = { + 'compute_type': {'required': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + _subtype_map = { + 'compute_type': {'AmlCompute': 'AmlComputeNodesInformation'} + } + + def __init__( + self, + **kwargs + ): + super(ComputeNodesInformation, self).__init__(**kwargs) + self.compute_type = None # type: Optional[str] + self.next_link = None + + +class AmlComputeNodesInformation(ComputeNodesInformation): + """Compute node information related to a AmlCompute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :ivar next_link: The continuation token. + :vartype next_link: str + :ivar nodes: The collection of returned AmlCompute nodes details. + :vartype nodes: list[~azure_machine_learning_workspaces.models.AmlComputeNodeInformation] + """ + + _validation = { + 'compute_type': {'required': True}, + 'next_link': {'readonly': True}, + 'nodes': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + 'nodes': {'key': 'nodes', 'type': '[AmlComputeNodeInformation]'}, + } + + def __init__( + self, + **kwargs + ): + super(AmlComputeNodesInformation, self).__init__(**kwargs) + self.compute_type = 'AmlCompute' # type: str + self.nodes = None + + +class AmlComputeProperties(msrest.serialization.Model): + """AML Compute properties. + + Variables are only populated by the server, and will be ignored when sending a request. + + :param os_type: Compute OS Type. Possible values include: "Linux", "Windows". Default value: + "Linux". + :type os_type: str or ~azure_machine_learning_workspaces.models.OsType + :param vm_size: Virtual Machine Size. + :type vm_size: str + :param vm_priority: Virtual Machine priority. Possible values include: "Dedicated", + "LowPriority". + :type vm_priority: str or ~azure_machine_learning_workspaces.models.VmPriority + :param scale_settings: Scale settings for AML Compute. + :type scale_settings: ~azure_machine_learning_workspaces.models.ScaleSettings + :param user_account_credentials: Credentials for an administrator user account that will be + created on each compute node. + :type user_account_credentials: + ~azure_machine_learning_workspaces.models.UserAccountCredentials + :param subnet: Virtual network subnet resource ID the compute nodes belong to. + :type subnet: ~azure_machine_learning_workspaces.models.ResourceId + :param remote_login_port_public_access: State of the public SSH port. Possible values are: + Disabled - Indicates that the public ssh port is closed on all nodes of the cluster. Enabled - + Indicates that the public ssh port is open on all nodes of the cluster. NotSpecified - + Indicates that the public ssh port is closed on all nodes of the cluster if VNet is defined, + else is open all public nodes. It can be default only during cluster creation time, after + creation it will be either enabled or disabled. Possible values include: "Enabled", "Disabled", + "NotSpecified". Default value: "NotSpecified". + :type remote_login_port_public_access: str or + ~azure_machine_learning_workspaces.models.RemoteLoginPortPublicAccess + :ivar allocation_state: Allocation state of the compute. Possible values are: steady - + Indicates that the compute is not resizing. There are no changes to the number of compute nodes + in the compute in progress. A compute enters this state when it is created and when no + operations are being performed on the compute to change the number of compute nodes. resizing - + Indicates that the compute is resizing; that is, compute nodes are being added to or removed + from the compute. Possible values include: "Steady", "Resizing". + :vartype allocation_state: str or ~azure_machine_learning_workspaces.models.AllocationState + :ivar allocation_state_transition_time: The time at which the compute entered its current + allocation state. + :vartype allocation_state_transition_time: ~datetime.datetime + :ivar errors: Collection of errors encountered by various compute nodes during node setup. + :vartype errors: list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar current_node_count: The number of compute nodes currently assigned to the compute. + :vartype current_node_count: int + :ivar target_node_count: The target number of compute nodes for the compute. If the + allocationState is resizing, this property denotes the target node count for the ongoing resize + operation. If the allocationState is steady, this property denotes the target node count for + the previous resize operation. + :vartype target_node_count: int + :ivar node_state_counts: Counts of various node states on the compute. + :vartype node_state_counts: ~azure_machine_learning_workspaces.models.NodeStateCounts + """ + + _validation = { + 'allocation_state': {'readonly': True}, + 'allocation_state_transition_time': {'readonly': True}, + 'errors': {'readonly': True}, + 'current_node_count': {'readonly': True}, + 'target_node_count': {'readonly': True}, + 'node_state_counts': {'readonly': True}, + } + + _attribute_map = { + 'os_type': {'key': 'osType', 'type': 'str'}, + 'vm_size': {'key': 'vmSize', 'type': 'str'}, + 'vm_priority': {'key': 'vmPriority', 'type': 'str'}, + 'scale_settings': {'key': 'scaleSettings', 'type': 'ScaleSettings'}, + 'user_account_credentials': {'key': 'userAccountCredentials', 'type': 'UserAccountCredentials'}, + 'subnet': {'key': 'subnet', 'type': 'ResourceId'}, + 'remote_login_port_public_access': {'key': 'remoteLoginPortPublicAccess', 'type': 'str'}, + 'allocation_state': {'key': 'allocationState', 'type': 'str'}, + 'allocation_state_transition_time': {'key': 'allocationStateTransitionTime', 'type': 'iso-8601'}, + 'errors': {'key': 'errors', 'type': '[MachineLearningServiceError]'}, + 'current_node_count': {'key': 'currentNodeCount', 'type': 'int'}, + 'target_node_count': {'key': 'targetNodeCount', 'type': 'int'}, + 'node_state_counts': {'key': 'nodeStateCounts', 'type': 'NodeStateCounts'}, + } + + def __init__( + self, + *, + os_type: Optional[Union[str, "OsType"]] = "Linux", + vm_size: Optional[str] = None, + vm_priority: Optional[Union[str, "VmPriority"]] = None, + scale_settings: Optional["ScaleSettings"] = None, + user_account_credentials: Optional["UserAccountCredentials"] = None, + subnet: Optional["ResourceId"] = None, + remote_login_port_public_access: Optional[Union[str, "RemoteLoginPortPublicAccess"]] = "NotSpecified", + **kwargs + ): + super(AmlComputeProperties, self).__init__(**kwargs) + self.os_type = os_type + self.vm_size = vm_size + self.vm_priority = vm_priority + self.scale_settings = scale_settings + self.user_account_credentials = user_account_credentials + self.subnet = subnet + self.remote_login_port_public_access = remote_login_port_public_access + self.allocation_state = None + self.allocation_state_transition_time = None + self.errors = None + self.current_node_count = None + self.target_node_count = None + self.node_state_counts = None + + +class AmlUserFeature(msrest.serialization.Model): + """Features enabled for a workspace. + + :param id: Specifies the feature ID. + :type id: str + :param display_name: Specifies the feature name. + :type display_name: str + :param description: Describes the feature for user experience. + :type description: str + """ + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'display_name': {'key': 'displayName', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + } + + def __init__( + self, + *, + id: Optional[str] = None, + display_name: Optional[str] = None, + description: Optional[str] = None, + **kwargs + ): + super(AmlUserFeature, self).__init__(**kwargs) + self.id = id + self.display_name = display_name + self.description = description + + +class AssignedUser(msrest.serialization.Model): + """A user that can be assigned to a compute instance. + + All required parameters must be populated in order to send to Azure. + + :param object_id: Required. User’s AAD Object Id. + :type object_id: str + :param tenant_id: Required. User’s AAD Tenant Id. + :type tenant_id: str + """ + + _validation = { + 'object_id': {'required': True}, + 'tenant_id': {'required': True}, + } + + _attribute_map = { + 'object_id': {'key': 'objectId', 'type': 'str'}, + 'tenant_id': {'key': 'tenantId', 'type': 'str'}, + } + + def __init__( + self, + *, + object_id: str, + tenant_id: str, + **kwargs + ): + super(AssignedUser, self).__init__(**kwargs) + self.object_id = object_id + self.tenant_id = tenant_id + + +class ClusterUpdateParameters(msrest.serialization.Model): + """AmlCompute update parameters. + + :param scale_settings: Desired scale settings for the amlCompute. + :type scale_settings: ~azure_machine_learning_workspaces.models.ScaleSettings + """ + + _attribute_map = { + 'scale_settings': {'key': 'properties.scaleSettings', 'type': 'ScaleSettings'}, + } + + def __init__( + self, + *, + scale_settings: Optional["ScaleSettings"] = None, + **kwargs + ): + super(ClusterUpdateParameters, self).__init__(**kwargs) + self.scale_settings = scale_settings + + +class ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties(msrest.serialization.Model): + """ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar principal_id: The principal id of user assigned identity. + :vartype principal_id: str + :ivar client_id: The client id of user assigned identity. + :vartype client_id: str + """ + + _validation = { + 'principal_id': {'readonly': True}, + 'client_id': {'readonly': True}, + } + + _attribute_map = { + 'principal_id': {'key': 'principalId', 'type': 'str'}, + 'client_id': {'key': 'clientId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties, self).__init__(**kwargs) + self.principal_id = None + self.client_id = None + + +class ComputeInstance(Compute): + """An Azure Machine Learning compute instance. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: Compute Instance properties. + :type properties: ~azure_machine_learning_workspaces.models.ComputeInstanceProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'ComputeInstanceProperties'}, + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + properties: Optional["ComputeInstanceProperties"] = None, + **kwargs + ): + super(ComputeInstance, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs) + self.compute_type = 'ComputeInstance' # type: str + self.properties = properties + + +class ComputeInstanceApplication(msrest.serialization.Model): + """Defines an Aml Instance application and its connectivity endpoint URI. + + :param display_name: Name of the ComputeInstance application. + :type display_name: str + :param endpoint_uri: Application' endpoint URI. + :type endpoint_uri: str + """ + + _attribute_map = { + 'display_name': {'key': 'displayName', 'type': 'str'}, + 'endpoint_uri': {'key': 'endpointUri', 'type': 'str'}, + } + + def __init__( + self, + *, + display_name: Optional[str] = None, + endpoint_uri: Optional[str] = None, + **kwargs + ): + super(ComputeInstanceApplication, self).__init__(**kwargs) + self.display_name = display_name + self.endpoint_uri = endpoint_uri + + +class ComputeInstanceConnectivityEndpoints(msrest.serialization.Model): + """Defines all connectivity endpoints and properties for a ComputeInstance. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar public_ip_address: Public IP Address of this ComputeInstance. + :vartype public_ip_address: str + :ivar private_ip_address: Private IP Address of this ComputeInstance (local to the VNET in + which the compute instance is deployed). + :vartype private_ip_address: str + """ + + _validation = { + 'public_ip_address': {'readonly': True}, + 'private_ip_address': {'readonly': True}, + } + + _attribute_map = { + 'public_ip_address': {'key': 'publicIpAddress', 'type': 'str'}, + 'private_ip_address': {'key': 'privateIpAddress', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstanceConnectivityEndpoints, self).__init__(**kwargs) + self.public_ip_address = None + self.private_ip_address = None + + +class ComputeInstanceCreatedBy(msrest.serialization.Model): + """Describes information on user who created this ComputeInstance. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar user_name: Name of the user. + :vartype user_name: str + :ivar user_org_id: Uniquely identifies user' Azure Active Directory organization. + :vartype user_org_id: str + :ivar user_id: Uniquely identifies the user within his/her organization. + :vartype user_id: str + """ + + _validation = { + 'user_name': {'readonly': True}, + 'user_org_id': {'readonly': True}, + 'user_id': {'readonly': True}, + } + + _attribute_map = { + 'user_name': {'key': 'userName', 'type': 'str'}, + 'user_org_id': {'key': 'userOrgId', 'type': 'str'}, + 'user_id': {'key': 'userId', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ComputeInstanceCreatedBy, self).__init__(**kwargs) + self.user_name = None + self.user_org_id = None + self.user_id = None + + +class ComputeInstanceLastOperation(msrest.serialization.Model): + """The last operation on ComputeInstance. + + :param operation_name: Name of the last operation. Possible values include: "Create", "Start", + "Stop", "Restart", "Reimage", "Delete". + :type operation_name: str or ~azure_machine_learning_workspaces.models.OperationName + :param operation_time: Time of the last operation. + :type operation_time: ~datetime.datetime + :param operation_status: Operation status. Possible values include: "InProgress", "Succeeded", + "CreateFailed", "StartFailed", "StopFailed", "RestartFailed", "ReimageFailed", "DeleteFailed". + :type operation_status: str or ~azure_machine_learning_workspaces.models.OperationStatus + """ + + _attribute_map = { + 'operation_name': {'key': 'operationName', 'type': 'str'}, + 'operation_time': {'key': 'operationTime', 'type': 'iso-8601'}, + 'operation_status': {'key': 'operationStatus', 'type': 'str'}, + } + + def __init__( + self, + *, + operation_name: Optional[Union[str, "OperationName"]] = None, + operation_time: Optional[datetime.datetime] = None, + operation_status: Optional[Union[str, "OperationStatus"]] = None, + **kwargs + ): + super(ComputeInstanceLastOperation, self).__init__(**kwargs) + self.operation_name = operation_name + self.operation_time = operation_time + self.operation_status = operation_status + + +class ComputeInstanceProperties(msrest.serialization.Model): + """Compute Instance properties. + + Variables are only populated by the server, and will be ignored when sending a request. + + :param vm_size: Virtual Machine Size. + :type vm_size: str + :param subnet: Virtual network subnet resource ID the compute nodes belong to. + :type subnet: ~azure_machine_learning_workspaces.models.ResourceId + :param application_sharing_policy: Policy for sharing applications on this compute instance + among users of parent workspace. If Personal, only the creator can access applications on this + compute instance. When Shared, any workspace user can access applications on this instance + depending on his/her assigned role. Possible values include: "Personal", "Shared". Default + value: "Shared". + :type application_sharing_policy: str or + ~azure_machine_learning_workspaces.models.ApplicationSharingPolicy + :param ssh_settings: Specifies policy and settings for SSH access. + :type ssh_settings: ~azure_machine_learning_workspaces.models.ComputeInstanceSshSettings + :ivar connectivity_endpoints: Describes all connectivity endpoints available for this + ComputeInstance. + :vartype connectivity_endpoints: + ~azure_machine_learning_workspaces.models.ComputeInstanceConnectivityEndpoints + :ivar applications: Describes available applications and their endpoints on this + ComputeInstance. + :vartype applications: + list[~azure_machine_learning_workspaces.models.ComputeInstanceApplication] + :ivar created_by: Describes information on user who created this ComputeInstance. + :vartype created_by: ~azure_machine_learning_workspaces.models.ComputeInstanceCreatedBy + :ivar errors: Collection of errors encountered on this ComputeInstance. + :vartype errors: list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar state: The current state of this ComputeInstance. Possible values include: "Creating", + "CreateFailed", "Deleting", "Running", "Restarting", "JobRunning", "SettingUp", "SetupFailed", + "Starting", "Stopped", "Stopping", "UserSettingUp", "UserSetupFailed", "Unknown", "Unusable". + :vartype state: str or ~azure_machine_learning_workspaces.models.ComputeInstanceState + :param compute_instance_authorization_type: The Compute Instance Authorization type. Available + values are personal (default). Possible values include: "personal". Default value: "personal". + :type compute_instance_authorization_type: str or + ~azure_machine_learning_workspaces.models.ComputeInstanceAuthorizationType + :param personal_compute_instance_settings: Settings for a personal compute instance. + :type personal_compute_instance_settings: + ~azure_machine_learning_workspaces.models.PersonalComputeInstanceSettings + :ivar last_operation: The last operation on ComputeInstance. + :vartype last_operation: ~azure_machine_learning_workspaces.models.ComputeInstanceLastOperation + """ + + _validation = { + 'connectivity_endpoints': {'readonly': True}, + 'applications': {'readonly': True}, + 'created_by': {'readonly': True}, + 'errors': {'readonly': True}, + 'state': {'readonly': True}, + 'last_operation': {'readonly': True}, + } + + _attribute_map = { + 'vm_size': {'key': 'vmSize', 'type': 'str'}, + 'subnet': {'key': 'subnet', 'type': 'ResourceId'}, + 'application_sharing_policy': {'key': 'applicationSharingPolicy', 'type': 'str'}, + 'ssh_settings': {'key': 'sshSettings', 'type': 'ComputeInstanceSshSettings'}, + 'connectivity_endpoints': {'key': 'connectivityEndpoints', 'type': 'ComputeInstanceConnectivityEndpoints'}, + 'applications': {'key': 'applications', 'type': '[ComputeInstanceApplication]'}, + 'created_by': {'key': 'createdBy', 'type': 'ComputeInstanceCreatedBy'}, + 'errors': {'key': 'errors', 'type': '[MachineLearningServiceError]'}, + 'state': {'key': 'state', 'type': 'str'}, + 'compute_instance_authorization_type': {'key': 'computeInstanceAuthorizationType', 'type': 'str'}, + 'personal_compute_instance_settings': {'key': 'personalComputeInstanceSettings', 'type': 'PersonalComputeInstanceSettings'}, + 'last_operation': {'key': 'lastOperation', 'type': 'ComputeInstanceLastOperation'}, + } + + def __init__( + self, + *, + vm_size: Optional[str] = None, + subnet: Optional["ResourceId"] = None, + application_sharing_policy: Optional[Union[str, "ApplicationSharingPolicy"]] = "Shared", + ssh_settings: Optional["ComputeInstanceSshSettings"] = None, + compute_instance_authorization_type: Optional[Union[str, "ComputeInstanceAuthorizationType"]] = "personal", + personal_compute_instance_settings: Optional["PersonalComputeInstanceSettings"] = None, + **kwargs + ): + super(ComputeInstanceProperties, self).__init__(**kwargs) + self.vm_size = vm_size + self.subnet = subnet + self.application_sharing_policy = application_sharing_policy + self.ssh_settings = ssh_settings + self.connectivity_endpoints = None + self.applications = None + self.created_by = None + self.errors = None + self.state = None + self.compute_instance_authorization_type = compute_instance_authorization_type + self.personal_compute_instance_settings = personal_compute_instance_settings + self.last_operation = None + + +class ComputeInstanceSshSettings(msrest.serialization.Model): + """Specifies policy and settings for SSH access. + + Variables are only populated by the server, and will be ignored when sending a request. + + :param 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 + public ssh port is open and accessible according to the VNet/subnet policy if applicable. + Possible values include: "Enabled", "Disabled". Default value: "Disabled". + :type ssh_public_access: str or ~azure_machine_learning_workspaces.models.SshPublicAccess + :ivar admin_user_name: Describes the admin user name. + :vartype admin_user_name: str + :ivar ssh_port: Describes the port for connecting through SSH. + :vartype ssh_port: int + :param admin_public_key: Specifies the SSH rsa public key file as a string. Use "ssh-keygen -t + rsa -b 2048" to generate your SSH key pairs. + :type admin_public_key: str + """ + + _validation = { + 'admin_user_name': {'readonly': True}, + 'ssh_port': {'readonly': True}, + } + + _attribute_map = { + 'ssh_public_access': {'key': 'sshPublicAccess', 'type': 'str'}, + 'admin_user_name': {'key': 'adminUserName', 'type': 'str'}, + 'ssh_port': {'key': 'sshPort', 'type': 'int'}, + 'admin_public_key': {'key': 'adminPublicKey', 'type': 'str'}, + } + + def __init__( + self, + *, + ssh_public_access: Optional[Union[str, "SshPublicAccess"]] = "Disabled", + admin_public_key: Optional[str] = None, + **kwargs + ): + super(ComputeInstanceSshSettings, self).__init__(**kwargs) + self.ssh_public_access = ssh_public_access + self.admin_user_name = None + self.ssh_port = None + self.admin_public_key = admin_public_key + + +class Resource(msrest.serialization.Model): + """Azure Resource Manager resource envelope. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param identity: The identity of the resource. + :type identity: ~azure_machine_learning_workspaces.models.Identity + :param location: Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'identity': {'key': 'identity', 'type': 'Identity'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + } + + def __init__( + self, + *, + identity: Optional["Identity"] = None, + location: Optional[str] = None, + tags: Optional[Dict[str, str]] = None, + sku: Optional["Sku"] = None, + **kwargs + ): + super(Resource, self).__init__(**kwargs) + self.id = None + self.name = None + self.identity = identity + self.location = location + self.type = None + self.tags = tags + self.sku = sku + + +class ComputeResource(Resource): + """Machine Learning compute object wrapped into ARM resource envelope. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param identity: The identity of the resource. + :type identity: ~azure_machine_learning_workspaces.models.Identity + :param location: Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + :param properties: Compute properties. + :type properties: ~azure_machine_learning_workspaces.models.Compute + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'identity': {'key': 'identity', 'type': 'Identity'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + 'properties': {'key': 'properties', 'type': 'Compute'}, + } + + def __init__( + self, + *, + identity: Optional["Identity"] = None, + location: Optional[str] = None, + tags: Optional[Dict[str, str]] = None, + sku: Optional["Sku"] = None, + properties: Optional["Compute"] = None, + **kwargs + ): + super(ComputeResource, self).__init__(identity=identity, location=location, tags=tags, sku=sku, **kwargs) + self.properties = properties + + +class Databricks(Compute): + """A DataFactory compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: + :type properties: ~azure_machine_learning_workspaces.models.DatabricksProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'DatabricksProperties'}, + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + properties: Optional["DatabricksProperties"] = None, + **kwargs + ): + super(Databricks, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs) + self.compute_type = 'Databricks' # type: str + self.properties = properties + + +class DatabricksComputeSecrets(ComputeSecrets): + """Secrets related to a Machine Learning compute based on Databricks. + + All required parameters must be populated in order to send to Azure. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param databricks_access_token: access token for databricks account. + :type databricks_access_token: str + """ + + _validation = { + 'compute_type': {'required': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'databricks_access_token': {'key': 'databricksAccessToken', 'type': 'str'}, + } + + def __init__( + self, + *, + databricks_access_token: Optional[str] = None, + **kwargs + ): + super(DatabricksComputeSecrets, self).__init__(**kwargs) + self.compute_type = 'Databricks' # type: str + self.databricks_access_token = databricks_access_token + + +class DatabricksProperties(msrest.serialization.Model): + """DatabricksProperties. + + :param databricks_access_token: Databricks access token. + :type databricks_access_token: str + """ + + _attribute_map = { + 'databricks_access_token': {'key': 'databricksAccessToken', 'type': 'str'}, + } + + def __init__( + self, + *, + databricks_access_token: Optional[str] = None, + **kwargs + ): + super(DatabricksProperties, self).__init__(**kwargs) + self.databricks_access_token = databricks_access_token + + +class DataFactory(Compute): + """A DataFactory compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + **kwargs + ): + super(DataFactory, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs) + self.compute_type = 'DataFactory' # type: str + + +class DataLakeAnalytics(Compute): + """A DataLakeAnalytics compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: + :type properties: ~azure_machine_learning_workspaces.models.DataLakeAnalyticsProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'DataLakeAnalyticsProperties'}, + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + properties: Optional["DataLakeAnalyticsProperties"] = None, + **kwargs + ): + super(DataLakeAnalytics, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs) + self.compute_type = 'DataLakeAnalytics' # type: str + self.properties = properties + + +class DataLakeAnalyticsProperties(msrest.serialization.Model): + """DataLakeAnalyticsProperties. + + :param data_lake_store_account_name: DataLake Store Account Name. + :type data_lake_store_account_name: str + """ + + _attribute_map = { + 'data_lake_store_account_name': {'key': 'dataLakeStoreAccountName', 'type': 'str'}, + } + + def __init__( + self, + *, + data_lake_store_account_name: Optional[str] = None, + **kwargs + ): + super(DataLakeAnalyticsProperties, self).__init__(**kwargs) + self.data_lake_store_account_name = data_lake_store_account_name + + +class EncryptionProperty(msrest.serialization.Model): + """EncryptionProperty. + + All required parameters must be populated in order to send to Azure. + + :param status: Required. Indicates whether or not the encryption is enabled for the workspace. + Possible values include: "Enabled", "Disabled". + :type status: str or ~azure_machine_learning_workspaces.models.EncryptionStatus + :param key_vault_properties: Required. Customer Key vault properties. + :type key_vault_properties: ~azure_machine_learning_workspaces.models.KeyVaultProperties + """ + + _validation = { + 'status': {'required': True}, + 'key_vault_properties': {'required': True}, + } + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'key_vault_properties': {'key': 'keyVaultProperties', 'type': 'KeyVaultProperties'}, + } + + def __init__( + self, + *, + status: Union[str, "EncryptionStatus"], + key_vault_properties: "KeyVaultProperties", + **kwargs + ): + super(EncryptionProperty, self).__init__(**kwargs) + self.status = status + self.key_vault_properties = key_vault_properties + + +class ErrorDetail(msrest.serialization.Model): + """Error detail information. + + All required parameters must be populated in order to send to Azure. + + :param code: Required. Error code. + :type code: str + :param message: Required. Error message. + :type message: str + """ + + _validation = { + 'code': {'required': True}, + 'message': {'required': True}, + } + + _attribute_map = { + 'code': {'key': 'code', 'type': 'str'}, + 'message': {'key': 'message', 'type': 'str'}, + } + + def __init__( + self, + *, + code: str, + message: str, + **kwargs + ): + super(ErrorDetail, self).__init__(**kwargs) + self.code = code + self.message = message + + +class ErrorResponse(msrest.serialization.Model): + """Error response information. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar code: Error code. + :vartype code: str + :ivar message: Error message. + :vartype message: str + :ivar details: An array of error detail objects. + :vartype details: list[~azure_machine_learning_workspaces.models.ErrorDetail] + """ + + _validation = { + 'code': {'readonly': True}, + 'message': {'readonly': True}, + 'details': {'readonly': True}, + } + + _attribute_map = { + 'code': {'key': 'code', 'type': 'str'}, + 'message': {'key': 'message', 'type': 'str'}, + 'details': {'key': 'details', 'type': '[ErrorDetail]'}, + } + + def __init__( + self, + **kwargs + ): + super(ErrorResponse, self).__init__(**kwargs) + self.code = None + self.message = None + self.details = None + + +class EstimatedVmPrice(msrest.serialization.Model): + """The estimated price info for using a VM of a particular OS type, tier, etc. + + All required parameters must be populated in order to send to Azure. + + :param retail_price: Required. The price charged for using the VM. + :type retail_price: float + :param os_type: Required. Operating system type used by the VM. Possible values include: + "Linux", "Windows". + :type os_type: str or ~azure_machine_learning_workspaces.models.VmPriceOsType + :param vm_tier: Required. The type of the VM. Possible values include: "Standard", + "LowPriority", "Spot". + :type vm_tier: str or ~azure_machine_learning_workspaces.models.VmTier + """ + + _validation = { + 'retail_price': {'required': True}, + 'os_type': {'required': True}, + 'vm_tier': {'required': True}, + } + + _attribute_map = { + 'retail_price': {'key': 'retailPrice', 'type': 'float'}, + 'os_type': {'key': 'osType', 'type': 'str'}, + 'vm_tier': {'key': 'vmTier', 'type': 'str'}, + } + + def __init__( + self, + *, + retail_price: float, + os_type: Union[str, "VmPriceOsType"], + vm_tier: Union[str, "VmTier"], + **kwargs + ): + super(EstimatedVmPrice, self).__init__(**kwargs) + self.retail_price = retail_price + self.os_type = os_type + self.vm_tier = vm_tier + + +class EstimatedVmPrices(msrest.serialization.Model): + """The estimated price info for using a VM. + + All required parameters must be populated in order to send to Azure. + + :param billing_currency: Required. Three lettered code specifying the currency of the VM price. + Example: USD. Possible values include: "USD". + :type billing_currency: str or ~azure_machine_learning_workspaces.models.BillingCurrency + :param unit_of_measure: Required. The unit of time measurement for the specified VM price. + Example: OneHour. Possible values include: "OneHour". + :type unit_of_measure: str or ~azure_machine_learning_workspaces.models.UnitOfMeasure + :param values: Required. The list of estimated prices for using a VM of a particular OS type, + tier, etc. + :type values: list[~azure_machine_learning_workspaces.models.EstimatedVmPrice] + """ + + _validation = { + 'billing_currency': {'required': True}, + 'unit_of_measure': {'required': True}, + 'values': {'required': True}, + } + + _attribute_map = { + 'billing_currency': {'key': 'billingCurrency', 'type': 'str'}, + 'unit_of_measure': {'key': 'unitOfMeasure', 'type': 'str'}, + 'values': {'key': 'values', 'type': '[EstimatedVmPrice]'}, + } + + def __init__( + self, + *, + billing_currency: Union[str, "BillingCurrency"], + unit_of_measure: Union[str, "UnitOfMeasure"], + values: List["EstimatedVmPrice"], + **kwargs + ): + super(EstimatedVmPrices, self).__init__(**kwargs) + self.billing_currency = billing_currency + self.unit_of_measure = unit_of_measure + self.values = values + + +class HdInsight(Compute): + """A HDInsight compute. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: + :type properties: ~azure_machine_learning_workspaces.models.HdInsightProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'HdInsightProperties'}, + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + properties: Optional["HdInsightProperties"] = None, + **kwargs + ): + super(HdInsight, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs) + self.compute_type = 'HDInsight' # type: str + self.properties = properties + + +class HdInsightProperties(msrest.serialization.Model): + """HdInsightProperties. + + :param ssh_port: Port open for ssh connections on the master node of the cluster. + :type ssh_port: int + :param address: Public IP address of the master node of the cluster. + :type address: str + :param administrator_account: Admin credentials for master node of the cluster. + :type administrator_account: + ~azure_machine_learning_workspaces.models.VirtualMachineSshCredentials + """ + + _attribute_map = { + 'ssh_port': {'key': 'sshPort', 'type': 'int'}, + 'address': {'key': 'address', 'type': 'str'}, + 'administrator_account': {'key': 'administratorAccount', 'type': 'VirtualMachineSshCredentials'}, + } + + def __init__( + self, + *, + ssh_port: Optional[int] = None, + address: Optional[str] = None, + administrator_account: Optional["VirtualMachineSshCredentials"] = None, + **kwargs + ): + super(HdInsightProperties, self).__init__(**kwargs) + self.ssh_port = ssh_port + self.address = address + self.administrator_account = administrator_account + + +class Identity(msrest.serialization.Model): + """Identity for the resource. + + 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 principal ID of resource identity. + :vartype principal_id: str + :ivar tenant_id: The tenant ID of resource. + :vartype tenant_id: str + :param type: Required. The identity type. Possible values include: "SystemAssigned", + "SystemAssigned,UserAssigned", "UserAssigned", "None". + :type type: str or ~azure_machine_learning_workspaces.models.ResourceIdentityType + :param user_assigned_identities: The list of user identities associated with resource. The user + identity dictionary key references will be ARM resource ids in the form: + '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'. + :type user_assigned_identities: dict[str, + ~azure_machine_learning_workspaces.models.ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties] + """ + + _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': '{ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties}'}, + } + + def __init__( + self, + *, + type: Union[str, "ResourceIdentityType"], + user_assigned_identities: Optional[Dict[str, "ComponentsSgqdofSchemasIdentityPropertiesUserassignedidentitiesAdditionalproperties"]] = None, + **kwargs + ): + super(Identity, self).__init__(**kwargs) + self.principal_id = None + self.tenant_id = None + self.type = type + self.user_assigned_identities = user_assigned_identities + + +class KeyVaultProperties(msrest.serialization.Model): + """KeyVaultProperties. + + All required parameters must be populated in order to send to Azure. + + :param key_vault_arm_id: Required. The ArmId of the keyVault where the customer owned + encryption key is present. + :type key_vault_arm_id: str + :param key_identifier: Required. Key vault uri to access the encryption key. + :type key_identifier: str + :param identity_client_id: For future use - The client id of the identity which will be used to + access key vault. + :type identity_client_id: str + """ + + _validation = { + 'key_vault_arm_id': {'required': True}, + 'key_identifier': {'required': True}, + } + + _attribute_map = { + 'key_vault_arm_id': {'key': 'keyVaultArmId', 'type': 'str'}, + 'key_identifier': {'key': 'keyIdentifier', 'type': 'str'}, + 'identity_client_id': {'key': 'identityClientId', 'type': 'str'}, + } + + def __init__( + self, + *, + key_vault_arm_id: str, + key_identifier: str, + identity_client_id: Optional[str] = None, + **kwargs + ): + super(KeyVaultProperties, self).__init__(**kwargs) + self.key_vault_arm_id = key_vault_arm_id + self.key_identifier = key_identifier + self.identity_client_id = identity_client_id + + +class ListAmlUserFeatureResult(msrest.serialization.Model): + """The List Aml user feature operation response. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The list of AML user facing features. + :vartype value: list[~azure_machine_learning_workspaces.models.AmlUserFeature] + :ivar next_link: The URI to fetch the next page of AML user features information. Call + ListNext() with this to fetch the next page of AML user features information. + :vartype next_link: str + """ + + _validation = { + 'value': {'readonly': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': '[AmlUserFeature]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ListAmlUserFeatureResult, self).__init__(**kwargs) + self.value = None + self.next_link = None + + +class ListUsagesResult(msrest.serialization.Model): + """The List Usages operation response. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The list of AML resource usages. + :vartype value: list[~azure_machine_learning_workspaces.models.Usage] + :ivar next_link: The URI to fetch the next page of AML resource usage information. Call + ListNext() with this to fetch the next page of AML resource usage information. + :vartype next_link: str + """ + + _validation = { + 'value': {'readonly': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': '[Usage]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ListUsagesResult, self).__init__(**kwargs) + self.value = None + self.next_link = None + + +class ListWorkspaceKeysResult(msrest.serialization.Model): + """ListWorkspaceKeysResult. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar user_storage_key: + :vartype user_storage_key: str + :ivar user_storage_resource_id: + :vartype user_storage_resource_id: str + :ivar app_insights_instrumentation_key: + :vartype app_insights_instrumentation_key: str + :ivar container_registry_credentials: + :vartype container_registry_credentials: + ~azure_machine_learning_workspaces.models.RegistryListCredentialsResult + :param notebook_access_keys: + :type notebook_access_keys: + ~azure_machine_learning_workspaces.models.NotebookListCredentialsResult + """ + + _validation = { + 'user_storage_key': {'readonly': True}, + 'user_storage_resource_id': {'readonly': True}, + 'app_insights_instrumentation_key': {'readonly': True}, + 'container_registry_credentials': {'readonly': True}, + } + + _attribute_map = { + 'user_storage_key': {'key': 'userStorageKey', 'type': 'str'}, + 'user_storage_resource_id': {'key': 'userStorageResourceId', 'type': 'str'}, + 'app_insights_instrumentation_key': {'key': 'appInsightsInstrumentationKey', 'type': 'str'}, + 'container_registry_credentials': {'key': 'containerRegistryCredentials', 'type': 'RegistryListCredentialsResult'}, + 'notebook_access_keys': {'key': 'notebookAccessKeys', 'type': 'NotebookListCredentialsResult'}, + } + + def __init__( + self, + *, + notebook_access_keys: Optional["NotebookListCredentialsResult"] = None, + **kwargs + ): + super(ListWorkspaceKeysResult, self).__init__(**kwargs) + self.user_storage_key = None + self.user_storage_resource_id = None + self.app_insights_instrumentation_key = None + self.container_registry_credentials = None + self.notebook_access_keys = notebook_access_keys + + +class ListWorkspaceQuotas(msrest.serialization.Model): + """The List WorkspaceQuotasByVMFamily operation response. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The list of Workspace Quotas by VM Family. + :vartype value: list[~azure_machine_learning_workspaces.models.ResourceQuota] + :ivar next_link: The URI to fetch the next page of workspace quota information by VM Family. + Call ListNext() with this to fetch the next page of Workspace Quota information. + :vartype next_link: str + """ + + _validation = { + 'value': {'readonly': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': '[ResourceQuota]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ListWorkspaceQuotas, self).__init__(**kwargs) + self.value = None + self.next_link = None + + +class MachineLearningServiceError(msrest.serialization.Model): + """Wrapper for error response to follow ARM guidelines. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar error: The error response. + :vartype error: ~azure_machine_learning_workspaces.models.ErrorResponse + """ + + _validation = { + 'error': {'readonly': True}, + } + + _attribute_map = { + 'error': {'key': 'error', 'type': 'ErrorResponse'}, + } + + def __init__( + self, + **kwargs + ): + super(MachineLearningServiceError, self).__init__(**kwargs) + self.error = None + + +class NodeStateCounts(msrest.serialization.Model): + """Counts of various compute node states on the amlCompute. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar idle_node_count: Number of compute nodes in idle state. + :vartype idle_node_count: int + :ivar running_node_count: Number of compute nodes which are running jobs. + :vartype running_node_count: int + :ivar preparing_node_count: Number of compute nodes which are being prepared. + :vartype preparing_node_count: int + :ivar unusable_node_count: Number of compute nodes which are in unusable state. + :vartype unusable_node_count: int + :ivar leaving_node_count: Number of compute nodes which are leaving the amlCompute. + :vartype leaving_node_count: int + :ivar preempted_node_count: Number of compute nodes which are in preempted state. + :vartype preempted_node_count: int + """ + + _validation = { + 'idle_node_count': {'readonly': True}, + 'running_node_count': {'readonly': True}, + 'preparing_node_count': {'readonly': True}, + 'unusable_node_count': {'readonly': True}, + 'leaving_node_count': {'readonly': True}, + 'preempted_node_count': {'readonly': True}, + } + + _attribute_map = { + 'idle_node_count': {'key': 'idleNodeCount', 'type': 'int'}, + 'running_node_count': {'key': 'runningNodeCount', 'type': 'int'}, + 'preparing_node_count': {'key': 'preparingNodeCount', 'type': 'int'}, + 'unusable_node_count': {'key': 'unusableNodeCount', 'type': 'int'}, + 'leaving_node_count': {'key': 'leavingNodeCount', 'type': 'int'}, + 'preempted_node_count': {'key': 'preemptedNodeCount', 'type': 'int'}, + } + + def __init__( + self, + **kwargs + ): + super(NodeStateCounts, self).__init__(**kwargs) + self.idle_node_count = None + self.running_node_count = None + self.preparing_node_count = None + self.unusable_node_count = None + self.leaving_node_count = None + self.preempted_node_count = None + + +class NotebookListCredentialsResult(msrest.serialization.Model): + """NotebookListCredentialsResult. + + :param primary_access_key: + :type primary_access_key: str + :param secondary_access_key: + :type secondary_access_key: str + """ + + _attribute_map = { + 'primary_access_key': {'key': 'primaryAccessKey', 'type': 'str'}, + 'secondary_access_key': {'key': 'secondaryAccessKey', 'type': 'str'}, + } + + def __init__( + self, + *, + primary_access_key: Optional[str] = None, + secondary_access_key: Optional[str] = None, + **kwargs + ): + super(NotebookListCredentialsResult, self).__init__(**kwargs) + self.primary_access_key = primary_access_key + self.secondary_access_key = secondary_access_key + + +class NotebookPreparationError(msrest.serialization.Model): + """NotebookPreparationError. + + :param error_message: + :type error_message: str + :param status_code: + :type status_code: int + """ + + _attribute_map = { + 'error_message': {'key': 'errorMessage', 'type': 'str'}, + 'status_code': {'key': 'statusCode', 'type': 'int'}, + } + + def __init__( + self, + *, + error_message: Optional[str] = None, + status_code: Optional[int] = None, + **kwargs + ): + super(NotebookPreparationError, self).__init__(**kwargs) + self.error_message = error_message + self.status_code = status_code + + +class NotebookResourceInfo(msrest.serialization.Model): + """NotebookResourceInfo. + + :param fqdn: + :type fqdn: str + :param resource_id: the data plane resourceId that used to initialize notebook component. + :type resource_id: str + :param notebook_preparation_error: The error that occurs when preparing notebook. + :type notebook_preparation_error: + ~azure_machine_learning_workspaces.models.NotebookPreparationError + """ + + _attribute_map = { + 'fqdn': {'key': 'fqdn', 'type': 'str'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'notebook_preparation_error': {'key': 'notebookPreparationError', 'type': 'NotebookPreparationError'}, + } + + def __init__( + self, + *, + fqdn: Optional[str] = None, + resource_id: Optional[str] = None, + notebook_preparation_error: Optional["NotebookPreparationError"] = None, + **kwargs + ): + super(NotebookResourceInfo, self).__init__(**kwargs) + self.fqdn = fqdn + self.resource_id = resource_id + self.notebook_preparation_error = notebook_preparation_error + + +class Operation(msrest.serialization.Model): + """Azure Machine Learning workspace REST API operation. + + :param name: Operation name: {provider}/{resource}/{operation}. + :type name: str + :param display: Display name of operation. + :type display: ~azure_machine_learning_workspaces.models.OperationDisplay + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'display': {'key': 'display', 'type': 'OperationDisplay'}, + } + + def __init__( + self, + *, + name: Optional[str] = None, + display: Optional["OperationDisplay"] = None, + **kwargs + ): + super(Operation, self).__init__(**kwargs) + self.name = name + self.display = display + + +class OperationDisplay(msrest.serialization.Model): + """Display name of operation. + + :param provider: The resource provider name: Microsoft.MachineLearningExperimentation. + :type provider: str + :param resource: The resource on which the operation is performed. + :type resource: str + :param operation: The operation that users can perform. + :type operation: str + :param description: The description for the operation. + :type description: str + """ + + _attribute_map = { + 'provider': {'key': 'provider', 'type': 'str'}, + 'resource': {'key': 'resource', 'type': 'str'}, + 'operation': {'key': 'operation', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + } + + def __init__( + self, + *, + provider: Optional[str] = None, + resource: Optional[str] = None, + operation: Optional[str] = None, + description: Optional[str] = None, + **kwargs + ): + super(OperationDisplay, self).__init__(**kwargs) + self.provider = provider + self.resource = resource + self.operation = operation + self.description = description + + +class OperationListResult(msrest.serialization.Model): + """An array of operations supported by the resource provider. + + :param value: List of AML workspace operations supported by the AML workspace resource + provider. + :type value: list[~azure_machine_learning_workspaces.models.Operation] + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[Operation]'}, + } + + def __init__( + self, + *, + value: Optional[List["Operation"]] = None, + **kwargs + ): + super(OperationListResult, self).__init__(**kwargs) + self.value = value + + +class PaginatedComputeResourcesList(msrest.serialization.Model): + """Paginated list of Machine Learning compute objects wrapped in ARM resource envelope. + + :param value: An array of Machine Learning compute objects wrapped in ARM resource envelope. + :type value: list[~azure_machine_learning_workspaces.models.ComputeResource] + :param next_link: A continuation link (absolute URI) to the next page of results in the list. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[ComputeResource]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + *, + value: Optional[List["ComputeResource"]] = None, + next_link: Optional[str] = None, + **kwargs + ): + super(PaginatedComputeResourcesList, self).__init__(**kwargs) + self.value = value + self.next_link = next_link + + +class PaginatedWorkspaceConnectionsList(msrest.serialization.Model): + """Paginated list of Workspace connection objects. + + :param value: An array of Workspace connection objects. + :type value: list[~azure_machine_learning_workspaces.models.WorkspaceConnection] + :param next_link: A continuation link (absolute URI) to the next page of results in the list. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[WorkspaceConnection]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + *, + value: Optional[List["WorkspaceConnection"]] = None, + next_link: Optional[str] = None, + **kwargs + ): + super(PaginatedWorkspaceConnectionsList, self).__init__(**kwargs) + self.value = value + self.next_link = next_link + + +class Password(msrest.serialization.Model): + """Password. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar name: + :vartype name: str + :ivar value: + :vartype value: str + """ + + _validation = { + 'name': {'readonly': True}, + 'value': {'readonly': True}, + } + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'value': {'key': 'value', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(Password, self).__init__(**kwargs) + self.name = None + self.value = None + + +class PersonalComputeInstanceSettings(msrest.serialization.Model): + """Settings for a personal compute instance. + + :param assigned_user: A user explicitly assigned to a personal compute instance. + :type assigned_user: ~azure_machine_learning_workspaces.models.AssignedUser + """ + + _attribute_map = { + 'assigned_user': {'key': 'assignedUser', 'type': 'AssignedUser'}, + } + + def __init__( + self, + *, + assigned_user: Optional["AssignedUser"] = None, + **kwargs + ): + super(PersonalComputeInstanceSettings, self).__init__(**kwargs) + self.assigned_user = assigned_user + + +class PrivateEndpoint(msrest.serialization.Model): + """The Private Endpoint resource. + + 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 + """ + + _validation = { + 'id': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(PrivateEndpoint, self).__init__(**kwargs) + self.id = None + + +class PrivateEndpointConnection(msrest.serialization.Model): + """The Private Endpoint Connection resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: ResourceId of the private endpoint connection. + :vartype id: str + :ivar name: Friendly name of the private endpoint connection. + :vartype name: str + :ivar type: Resource type of private endpoint connection. + :vartype type: str + :param private_endpoint: The resource of private end point. + :type private_endpoint: ~azure_machine_learning_workspaces.models.PrivateEndpoint + :param private_link_service_connection_state: A collection of information about the state of + the connection between service consumer and provider. + :type private_link_service_connection_state: + ~azure_machine_learning_workspaces.models.PrivateLinkServiceConnectionState + :ivar provisioning_state: The provisioning state of the private endpoint connection resource. + Possible values include: "Succeeded", "Creating", "Deleting", "Failed". + :vartype provisioning_state: str or + ~azure_machine_learning_workspaces.models.PrivateEndpointConnectionProvisioningState + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + 'provisioning_state': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'private_endpoint': {'key': 'properties.privateEndpoint', 'type': 'PrivateEndpoint'}, + 'private_link_service_connection_state': {'key': 'properties.privateLinkServiceConnectionState', 'type': 'PrivateLinkServiceConnectionState'}, + 'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'}, + } + + def __init__( + self, + *, + private_endpoint: Optional["PrivateEndpoint"] = None, + private_link_service_connection_state: Optional["PrivateLinkServiceConnectionState"] = None, + **kwargs + ): + super(PrivateEndpointConnection, self).__init__(**kwargs) + self.id = None + self.name = None + self.type = None + self.private_endpoint = private_endpoint + self.private_link_service_connection_state = private_link_service_connection_state + self.provisioning_state = None + + +class PrivateLinkResource(Resource): + """A private link resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param identity: The identity of the resource. + :type identity: ~azure_machine_learning_workspaces.models.Identity + :param location: Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + :ivar group_id: The private link resource group id. + :vartype group_id: str + :ivar required_members: The private link resource required member names. + :vartype required_members: list[str] + :param required_zone_names: The private link resource Private link DNS zone name. + :type required_zone_names: list[str] + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + 'group_id': {'readonly': True}, + 'required_members': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'identity': {'key': 'identity', 'type': 'Identity'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + 'group_id': {'key': 'properties.groupId', 'type': 'str'}, + 'required_members': {'key': 'properties.requiredMembers', 'type': '[str]'}, + 'required_zone_names': {'key': 'properties.requiredZoneNames', 'type': '[str]'}, + } + + def __init__( + self, + *, + identity: Optional["Identity"] = None, + location: Optional[str] = None, + tags: Optional[Dict[str, str]] = None, + sku: Optional["Sku"] = None, + required_zone_names: Optional[List[str]] = None, + **kwargs + ): + super(PrivateLinkResource, self).__init__(identity=identity, location=location, tags=tags, sku=sku, **kwargs) + self.group_id = None + self.required_members = None + self.required_zone_names = required_zone_names + + +class PrivateLinkResourceListResult(msrest.serialization.Model): + """A list of private link resources. + + :param value: Array of private link resources. + :type value: list[~azure_machine_learning_workspaces.models.PrivateLinkResource] + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[PrivateLinkResource]'}, + } + + def __init__( + self, + *, + value: Optional[List["PrivateLinkResource"]] = None, + **kwargs + ): + super(PrivateLinkResourceListResult, self).__init__(**kwargs) + self.value = value + + +class PrivateLinkServiceConnectionState(msrest.serialization.Model): + """A collection of information about the state of the connection between service consumer and provider. + + :param status: Indicates whether the connection has been Approved/Rejected/Removed by the owner + of the service. Possible values include: "Pending", "Approved", "Rejected", "Disconnected", + "Timeout". + :type status: str or + ~azure_machine_learning_workspaces.models.PrivateEndpointServiceConnectionStatus + :param description: The reason for approval/rejection of the connection. + :type description: str + :param actions_required: A message indicating if changes on the service provider require any + updates on the consumer. + :type actions_required: str + """ + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'actions_required': {'key': 'actionsRequired', 'type': 'str'}, + } + + def __init__( + self, + *, + status: Optional[Union[str, "PrivateEndpointServiceConnectionStatus"]] = None, + description: Optional[str] = None, + actions_required: Optional[str] = None, + **kwargs + ): + super(PrivateLinkServiceConnectionState, self).__init__(**kwargs) + self.status = status + self.description = description + self.actions_required = actions_required + + +class QuotaBaseProperties(msrest.serialization.Model): + """The properties for Quota update or retrieval. + + :param id: Specifies the resource ID. + :type id: str + :param type: Specifies the resource type. + :type type: str + :param limit: The maximum permitted quota of the resource. + :type limit: long + :param unit: An enum describing the unit of quota measurement. Possible values include: + "Count". + :type unit: str or ~azure_machine_learning_workspaces.models.QuotaUnit + """ + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'limit': {'key': 'limit', 'type': 'long'}, + 'unit': {'key': 'unit', 'type': 'str'}, + } + + def __init__( + self, + *, + id: Optional[str] = None, + type: Optional[str] = None, + limit: Optional[int] = None, + unit: Optional[Union[str, "QuotaUnit"]] = None, + **kwargs + ): + super(QuotaBaseProperties, self).__init__(**kwargs) + self.id = id + self.type = type + self.limit = limit + self.unit = unit + + +class QuotaUpdateParameters(msrest.serialization.Model): + """Quota update parameters. + + :param value: The list for update quota. + :type value: list[~azure_machine_learning_workspaces.models.QuotaBaseProperties] + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[QuotaBaseProperties]'}, + } + + def __init__( + self, + *, + value: Optional[List["QuotaBaseProperties"]] = None, + **kwargs + ): + super(QuotaUpdateParameters, self).__init__(**kwargs) + self.value = value + + +class RegistryListCredentialsResult(msrest.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 + :param passwords: + :type passwords: list[~azure_machine_learning_workspaces.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["Password"]] = None, + **kwargs + ): + super(RegistryListCredentialsResult, self).__init__(**kwargs) + self.location = None + self.username = None + self.passwords = passwords + + +class ResourceId(msrest.serialization.Model): + """Represents a resource ID. For example, for a subnet, it is the resource URL for the subnet. + + All required parameters must be populated in order to send to Azure. + + :param id: Required. The ID of the resource. + :type id: str + """ + + _validation = { + 'id': {'required': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + } + + def __init__( + self, + *, + id: str, + **kwargs + ): + super(ResourceId, self).__init__(**kwargs) + self.id = id + + +class ResourceName(msrest.serialization.Model): + """The Resource Name. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The name of the resource. + :vartype value: str + :ivar localized_value: The localized name of the resource. + :vartype localized_value: str + """ + + _validation = { + 'value': {'readonly': True}, + 'localized_value': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': 'str'}, + 'localized_value': {'key': 'localizedValue', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceName, self).__init__(**kwargs) + self.value = None + self.localized_value = None + + +class ResourceQuota(msrest.serialization.Model): + """The quota assigned to a resource. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar type: Specifies the resource type. + :vartype type: str + :ivar name: Name of the resource. + :vartype name: ~azure_machine_learning_workspaces.models.ResourceName + :ivar limit: The maximum permitted quota of the resource. + :vartype limit: long + :ivar unit: An enum describing the unit of quota measurement. Possible values include: "Count". + :vartype unit: str or ~azure_machine_learning_workspaces.models.QuotaUnit + """ + + _validation = { + 'id': {'readonly': True}, + 'type': {'readonly': True}, + 'name': {'readonly': True}, + 'limit': {'readonly': True}, + 'unit': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'ResourceName'}, + 'limit': {'key': 'limit', 'type': 'long'}, + 'unit': {'key': 'unit', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceQuota, self).__init__(**kwargs) + self.id = None + self.type = None + self.name = None + self.limit = None + self.unit = None + + +class ResourceSkuLocationInfo(msrest.serialization.Model): + """ResourceSkuLocationInfo. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar location: Location of the SKU. + :vartype location: str + :ivar zones: List of availability zones where the SKU is supported. + :vartype zones: list[str] + :ivar zone_details: Details of capabilities available to a SKU in specific zones. + :vartype zone_details: list[~azure_machine_learning_workspaces.models.ResourceSkuZoneDetails] + """ + + _validation = { + 'location': {'readonly': True}, + 'zones': {'readonly': True}, + 'zone_details': {'readonly': True}, + } + + _attribute_map = { + 'location': {'key': 'location', 'type': 'str'}, + 'zones': {'key': 'zones', 'type': '[str]'}, + 'zone_details': {'key': 'zoneDetails', 'type': '[ResourceSkuZoneDetails]'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceSkuLocationInfo, self).__init__(**kwargs) + self.location = None + self.zones = None + self.zone_details = None + + +class ResourceSkuZoneDetails(msrest.serialization.Model): + """Describes The zonal capabilities of a SKU. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar name: The set of zones that the SKU is available in with the specified capabilities. + :vartype name: list[str] + :ivar capabilities: A list of capabilities that are available for the SKU in the specified list + of zones. + :vartype capabilities: list[~azure_machine_learning_workspaces.models.SkuCapability] + """ + + _validation = { + 'name': {'readonly': True}, + 'capabilities': {'readonly': True}, + } + + _attribute_map = { + 'name': {'key': 'name', 'type': '[str]'}, + 'capabilities': {'key': 'capabilities', 'type': '[SkuCapability]'}, + } + + def __init__( + self, + **kwargs + ): + super(ResourceSkuZoneDetails, self).__init__(**kwargs) + self.name = None + self.capabilities = None + + +class Restriction(msrest.serialization.Model): + """The restriction because of which SKU cannot be used. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar type: The type of restrictions. As of now only possible value for this is location. + :vartype type: str + :ivar values: The value of restrictions. If the restriction type is set to location. This would + be different locations where the SKU is restricted. + :vartype values: list[str] + :param reason_code: The reason for the restriction. Possible values include: "NotSpecified", + "NotAvailableForRegion", "NotAvailableForSubscription". + :type reason_code: str or ~azure_machine_learning_workspaces.models.ReasonCode + """ + + _validation = { + 'type': {'readonly': True}, + 'values': {'readonly': True}, + } + + _attribute_map = { + 'type': {'key': 'type', 'type': 'str'}, + 'values': {'key': 'values', 'type': '[str]'}, + 'reason_code': {'key': 'reasonCode', 'type': 'str'}, + } + + def __init__( + self, + *, + reason_code: Optional[Union[str, "ReasonCode"]] = None, + **kwargs + ): + super(Restriction, self).__init__(**kwargs) + self.type = None + self.values = None + self.reason_code = reason_code + + +class ScaleSettings(msrest.serialization.Model): + """scale settings for AML Compute. + + All required parameters must be populated in order to send to Azure. + + :param max_node_count: Required. Max number of nodes to use. + :type max_node_count: int + :param min_node_count: Min number of nodes to use. + :type min_node_count: int + :param node_idle_time_before_scale_down: Node Idle Time before scaling down amlCompute. This + string needs to be in the RFC Format. + :type node_idle_time_before_scale_down: ~datetime.timedelta + """ + + _validation = { + 'max_node_count': {'required': True}, + } + + _attribute_map = { + 'max_node_count': {'key': 'maxNodeCount', 'type': 'int'}, + 'min_node_count': {'key': 'minNodeCount', 'type': 'int'}, + 'node_idle_time_before_scale_down': {'key': 'nodeIdleTimeBeforeScaleDown', 'type': 'duration'}, + } + + def __init__( + self, + *, + max_node_count: int, + min_node_count: Optional[int] = 0, + node_idle_time_before_scale_down: Optional[datetime.timedelta] = None, + **kwargs + ): + super(ScaleSettings, self).__init__(**kwargs) + self.max_node_count = max_node_count + self.min_node_count = min_node_count + self.node_idle_time_before_scale_down = node_idle_time_before_scale_down + + +class ServicePrincipalCredentials(msrest.serialization.Model): + """Service principal credentials. + + All required parameters must be populated in order to send to Azure. + + :param client_id: Required. Client Id. + :type client_id: str + :param client_secret: Required. Client secret. + :type client_secret: str + """ + + _validation = { + 'client_id': {'required': True}, + 'client_secret': {'required': True}, + } + + _attribute_map = { + 'client_id': {'key': 'clientId', 'type': 'str'}, + 'client_secret': {'key': 'clientSecret', 'type': 'str'}, + } + + def __init__( + self, + *, + client_id: str, + client_secret: str, + **kwargs + ): + super(ServicePrincipalCredentials, self).__init__(**kwargs) + self.client_id = client_id + self.client_secret = client_secret + + +class SharedPrivateLinkResource(msrest.serialization.Model): + """SharedPrivateLinkResource. + + :param name: Unique name of the private link. + :type name: str + :param private_link_resource_id: The resource id that private link links to. + :type private_link_resource_id: str + :param group_id: The private link resource group id. + :type group_id: str + :param request_message: Request message. + :type request_message: str + :param status: Indicates whether the connection has been Approved/Rejected/Removed by the owner + of the service. Possible values include: "Pending", "Approved", "Rejected", "Disconnected", + "Timeout". + :type status: str or + ~azure_machine_learning_workspaces.models.PrivateEndpointServiceConnectionStatus + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'private_link_resource_id': {'key': 'properties.privateLinkResourceId', 'type': 'str'}, + 'group_id': {'key': 'properties.groupId', 'type': 'str'}, + 'request_message': {'key': 'properties.requestMessage', 'type': 'str'}, + 'status': {'key': 'properties.status', 'type': 'str'}, + } + + def __init__( + self, + *, + name: Optional[str] = None, + private_link_resource_id: Optional[str] = None, + group_id: Optional[str] = None, + request_message: Optional[str] = None, + status: Optional[Union[str, "PrivateEndpointServiceConnectionStatus"]] = None, + **kwargs + ): + super(SharedPrivateLinkResource, self).__init__(**kwargs) + self.name = name + self.private_link_resource_id = private_link_resource_id + self.group_id = group_id + self.request_message = request_message + self.status = status + + +class Sku(msrest.serialization.Model): + """Sku of the resource. + + :param name: Name of the sku. + :type name: str + :param tier: Tier of the sku like Basic or Enterprise. + :type tier: str + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'tier': {'key': 'tier', 'type': 'str'}, + } + + def __init__( + self, + *, + name: Optional[str] = None, + tier: Optional[str] = None, + **kwargs + ): + super(Sku, self).__init__(**kwargs) + self.name = name + self.tier = tier + + +class SkuCapability(msrest.serialization.Model): + """Features/user capabilities associated with the sku. + + :param name: Capability/Feature ID. + :type name: str + :param value: Details about the feature/capability. + :type value: str + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'value': {'key': 'value', 'type': 'str'}, + } + + def __init__( + self, + *, + name: Optional[str] = None, + value: Optional[str] = None, + **kwargs + ): + super(SkuCapability, self).__init__(**kwargs) + self.name = name + self.value = value + + +class SkuListResult(msrest.serialization.Model): + """List of skus with features. + + :param value: + :type value: list[~azure_machine_learning_workspaces.models.WorkspaceSku] + :param next_link: The URI to fetch the next page of Workspace Skus. Call ListNext() with this + URI to fetch the next page of Workspace Skus. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[WorkspaceSku]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + *, + value: Optional[List["WorkspaceSku"]] = None, + next_link: Optional[str] = None, + **kwargs + ): + super(SkuListResult, self).__init__(**kwargs) + self.value = value + self.next_link = next_link + + +class SkuSettings(msrest.serialization.Model): + """Describes Workspace Sku details and features. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar locations: The set of locations that the SKU is available. This will be supported and + registered Azure Geo Regions (e.g. West US, East US, Southeast Asia, etc.). + :vartype locations: list[str] + :ivar location_info: A list of locations and availability zones in those locations where the + SKU is available. + :vartype location_info: list[~azure_machine_learning_workspaces.models.ResourceSkuLocationInfo] + :ivar tier: Sku Tier like Basic or Enterprise. + :vartype tier: str + :ivar resource_type: + :vartype resource_type: str + :ivar name: + :vartype name: str + :ivar capabilities: List of features/user capabilities associated with the sku. + :vartype capabilities: list[~azure_machine_learning_workspaces.models.SkuCapability] + :param restrictions: The restrictions because of which SKU cannot be used. This is empty if + there are no restrictions. + :type restrictions: list[~azure_machine_learning_workspaces.models.Restriction] + """ + + _validation = { + 'locations': {'readonly': True}, + 'location_info': {'readonly': True}, + 'tier': {'readonly': True}, + 'resource_type': {'readonly': True}, + 'name': {'readonly': True}, + 'capabilities': {'readonly': True}, + } + + _attribute_map = { + 'locations': {'key': 'locations', 'type': '[str]'}, + 'location_info': {'key': 'locationInfo', 'type': '[ResourceSkuLocationInfo]'}, + 'tier': {'key': 'tier', 'type': 'str'}, + 'resource_type': {'key': 'resourceType', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'capabilities': {'key': 'capabilities', 'type': '[SkuCapability]'}, + 'restrictions': {'key': 'restrictions', 'type': '[Restriction]'}, + } + + def __init__( + self, + *, + restrictions: Optional[List["Restriction"]] = None, + **kwargs + ): + super(SkuSettings, self).__init__(**kwargs) + self.locations = None + self.location_info = None + self.tier = None + self.resource_type = None + self.name = None + self.capabilities = None + self.restrictions = restrictions + + +class SslConfiguration(msrest.serialization.Model): + """The ssl configuration for scoring. + + :param status: Enable or disable ssl for scoring. Possible values include: "Disabled", + "Enabled", "Auto". + :type status: str or ~azure_machine_learning_workspaces.models.SslConfigurationStatus + :param cert: Cert data. + :type cert: str + :param key: Key data. + :type key: str + :param cname: CNAME of the cert. + :type cname: str + """ + + _attribute_map = { + 'status': {'key': 'status', 'type': 'str'}, + 'cert': {'key': 'cert', 'type': 'str'}, + 'key': {'key': 'key', 'type': 'str'}, + 'cname': {'key': 'cname', 'type': 'str'}, + } + + def __init__( + self, + *, + status: Optional[Union[str, "SslConfigurationStatus"]] = None, + cert: Optional[str] = None, + key: Optional[str] = None, + cname: Optional[str] = None, + **kwargs + ): + super(SslConfiguration, self).__init__(**kwargs) + self.status = status + self.cert = cert + self.key = key + self.cname = cname + + +class SystemService(msrest.serialization.Model): + """A system service running on a compute. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar system_service_type: The type of this system service. + :vartype system_service_type: str + :ivar public_ip_address: Public IP address. + :vartype public_ip_address: str + :ivar version: The version for this type. + :vartype version: str + """ + + _validation = { + 'system_service_type': {'readonly': True}, + 'public_ip_address': {'readonly': True}, + 'version': {'readonly': True}, + } + + _attribute_map = { + 'system_service_type': {'key': 'systemServiceType', 'type': 'str'}, + 'public_ip_address': {'key': 'publicIpAddress', 'type': 'str'}, + 'version': {'key': 'version', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(SystemService, self).__init__(**kwargs) + self.system_service_type = None + self.public_ip_address = None + self.version = None + + +class UpdateWorkspaceQuotas(msrest.serialization.Model): + """The properties for update Quota response. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar type: Specifies the resource type. + :vartype type: str + :param limit: The maximum permitted quota of the resource. + :type limit: long + :ivar unit: An enum describing the unit of quota measurement. Possible values include: "Count". + :vartype unit: str or ~azure_machine_learning_workspaces.models.QuotaUnit + :param status: Status of update workspace quota. Possible values include: "Undefined", + "Success", "Failure", "InvalidQuotaBelowClusterMinimum", + "InvalidQuotaExceedsSubscriptionLimit", "InvalidVMFamilyName", "OperationNotSupportedForSku", + "OperationNotEnabledForRegion". + :type status: str or ~azure_machine_learning_workspaces.models.Status + """ + + _validation = { + 'id': {'readonly': True}, + 'type': {'readonly': True}, + 'unit': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'limit': {'key': 'limit', 'type': 'long'}, + 'unit': {'key': 'unit', 'type': 'str'}, + 'status': {'key': 'status', 'type': 'str'}, + } + + def __init__( + self, + *, + limit: Optional[int] = None, + status: Optional[Union[str, "Status"]] = None, + **kwargs + ): + super(UpdateWorkspaceQuotas, self).__init__(**kwargs) + self.id = None + self.type = None + self.limit = limit + self.unit = None + self.status = status + + +class UpdateWorkspaceQuotasResult(msrest.serialization.Model): + """The result of update workspace quota. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The list of workspace quota update result. + :vartype value: list[~azure_machine_learning_workspaces.models.UpdateWorkspaceQuotas] + :ivar next_link: The URI to fetch the next page of workspace quota update result. Call + ListNext() with this to fetch the next page of Workspace Quota update result. + :vartype next_link: str + """ + + _validation = { + 'value': {'readonly': True}, + 'next_link': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': '[UpdateWorkspaceQuotas]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(UpdateWorkspaceQuotasResult, self).__init__(**kwargs) + self.value = None + self.next_link = None + + +class Usage(msrest.serialization.Model): + """Describes AML Resource Usage. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar type: Specifies the resource type. + :vartype type: str + :ivar unit: An enum describing the unit of usage measurement. Possible values include: "Count". + :vartype unit: str or ~azure_machine_learning_workspaces.models.UsageUnit + :ivar current_value: The current usage of the resource. + :vartype current_value: long + :ivar limit: The maximum permitted usage of the resource. + :vartype limit: long + :ivar name: The name of the type of usage. + :vartype name: ~azure_machine_learning_workspaces.models.UsageName + """ + + _validation = { + 'id': {'readonly': True}, + 'type': {'readonly': True}, + 'unit': {'readonly': True}, + 'current_value': {'readonly': True}, + 'limit': {'readonly': True}, + 'name': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'unit': {'key': 'unit', 'type': 'str'}, + 'current_value': {'key': 'currentValue', 'type': 'long'}, + 'limit': {'key': 'limit', 'type': 'long'}, + 'name': {'key': 'name', 'type': 'UsageName'}, + } + + def __init__( + self, + **kwargs + ): + super(Usage, self).__init__(**kwargs) + self.id = None + self.type = None + self.unit = None + self.current_value = None + self.limit = None + self.name = None + + +class UsageName(msrest.serialization.Model): + """The Usage Names. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar value: The name of the resource. + :vartype value: str + :ivar localized_value: The localized name of the resource. + :vartype localized_value: str + """ + + _validation = { + 'value': {'readonly': True}, + 'localized_value': {'readonly': True}, + } + + _attribute_map = { + 'value': {'key': 'value', 'type': 'str'}, + 'localized_value': {'key': 'localizedValue', 'type': 'str'}, + } + + def __init__( + self, + **kwargs + ): + super(UsageName, self).__init__(**kwargs) + self.value = None + self.localized_value = None + + +class UserAccountCredentials(msrest.serialization.Model): + """Settings for user account that gets created on each on the nodes of a compute. + + All required parameters must be populated in order to send to Azure. + + :param admin_user_name: Required. Name of the administrator user account which can be used to + SSH to nodes. + :type admin_user_name: str + :param admin_user_ssh_public_key: SSH public key of the administrator user account. + :type admin_user_ssh_public_key: str + :param admin_user_password: Password of the administrator user account. + :type admin_user_password: str + """ + + _validation = { + 'admin_user_name': {'required': True}, + } + + _attribute_map = { + 'admin_user_name': {'key': 'adminUserName', 'type': 'str'}, + 'admin_user_ssh_public_key': {'key': 'adminUserSshPublicKey', 'type': 'str'}, + 'admin_user_password': {'key': 'adminUserPassword', 'type': 'str'}, + } + + def __init__( + self, + *, + admin_user_name: str, + admin_user_ssh_public_key: Optional[str] = None, + admin_user_password: Optional[str] = None, + **kwargs + ): + super(UserAccountCredentials, self).__init__(**kwargs) + self.admin_user_name = admin_user_name + self.admin_user_ssh_public_key = admin_user_ssh_public_key + self.admin_user_password = admin_user_password + + +class VirtualMachine(Compute): + """A Machine Learning compute based on Azure Virtual Machines. + + 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. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param compute_location: Location for the underlying compute. + :type compute_location: str + :ivar provisioning_state: The provision state of the cluster. Valid values are Unknown, + Updating, Provisioning, Succeeded, and Failed. Possible values include: "Unknown", "Updating", + "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param description: The description of the Machine Learning compute. + :type description: str + :ivar created_on: The date and time when the compute was created. + :vartype created_on: ~datetime.datetime + :ivar modified_on: The date and time when the compute was last modified. + :vartype modified_on: ~datetime.datetime + :param resource_id: ARM resource id of the underlying compute. + :type resource_id: str + :ivar provisioning_errors: Errors during provisioning. + :vartype provisioning_errors: + list[~azure_machine_learning_workspaces.models.MachineLearningServiceError] + :ivar is_attached_compute: Indicating whether the compute was provisioned by user and brought + from outside if true, or machine learning service provisioned it if false. + :vartype is_attached_compute: bool + :param properties: + :type properties: ~azure_machine_learning_workspaces.models.VirtualMachineProperties + """ + + _validation = { + 'compute_type': {'required': True}, + 'provisioning_state': {'readonly': True}, + 'created_on': {'readonly': True}, + 'modified_on': {'readonly': True}, + 'provisioning_errors': {'readonly': True}, + 'is_attached_compute': {'readonly': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'compute_location': {'key': 'computeLocation', 'type': 'str'}, + 'provisioning_state': {'key': 'provisioningState', 'type': 'str'}, + 'description': {'key': 'description', 'type': 'str'}, + 'created_on': {'key': 'createdOn', 'type': 'iso-8601'}, + 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'}, + 'resource_id': {'key': 'resourceId', 'type': 'str'}, + 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'}, + 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'}, + 'properties': {'key': 'properties', 'type': 'VirtualMachineProperties'}, + } + + def __init__( + self, + *, + compute_location: Optional[str] = None, + description: Optional[str] = None, + resource_id: Optional[str] = None, + properties: Optional["VirtualMachineProperties"] = None, + **kwargs + ): + super(VirtualMachine, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs) + self.compute_type = 'VirtualMachine' # type: str + self.properties = properties + + +class VirtualMachineProperties(msrest.serialization.Model): + """VirtualMachineProperties. + + :param virtual_machine_size: Virtual Machine size. + :type virtual_machine_size: str + :param ssh_port: Port open for ssh connections. + :type ssh_port: int + :param address: Public IP address of the virtual machine. + :type address: str + :param administrator_account: Admin credentials for virtual machine. + :type administrator_account: + ~azure_machine_learning_workspaces.models.VirtualMachineSshCredentials + """ + + _attribute_map = { + 'virtual_machine_size': {'key': 'virtualMachineSize', 'type': 'str'}, + 'ssh_port': {'key': 'sshPort', 'type': 'int'}, + 'address': {'key': 'address', 'type': 'str'}, + 'administrator_account': {'key': 'administratorAccount', 'type': 'VirtualMachineSshCredentials'}, + } + + def __init__( + self, + *, + virtual_machine_size: Optional[str] = None, + ssh_port: Optional[int] = None, + address: Optional[str] = None, + administrator_account: Optional["VirtualMachineSshCredentials"] = None, + **kwargs + ): + super(VirtualMachineProperties, self).__init__(**kwargs) + self.virtual_machine_size = virtual_machine_size + self.ssh_port = ssh_port + self.address = address + self.administrator_account = administrator_account + + +class VirtualMachineSecrets(ComputeSecrets): + """Secrets related to a Machine Learning compute based on AKS. + + All required parameters must be populated in order to send to Azure. + + :param compute_type: Required. The type of compute.Constant filled by server. Possible values + include: "AKS", "AmlCompute", "ComputeInstance", "DataFactory", "VirtualMachine", "HDInsight", + "Databricks", "DataLakeAnalytics". + :type compute_type: str or ~azure_machine_learning_workspaces.models.ComputeType + :param administrator_account: Admin credentials for virtual machine. + :type administrator_account: + ~azure_machine_learning_workspaces.models.VirtualMachineSshCredentials + """ + + _validation = { + 'compute_type': {'required': True}, + } + + _attribute_map = { + 'compute_type': {'key': 'computeType', 'type': 'str'}, + 'administrator_account': {'key': 'administratorAccount', 'type': 'VirtualMachineSshCredentials'}, + } + + def __init__( + self, + *, + administrator_account: Optional["VirtualMachineSshCredentials"] = None, + **kwargs + ): + super(VirtualMachineSecrets, self).__init__(**kwargs) + self.compute_type = 'VirtualMachine' # type: str + self.administrator_account = administrator_account + + +class VirtualMachineSize(msrest.serialization.Model): + """Describes the properties of a VM size. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar name: The name of the virtual machine size. + :vartype name: str + :ivar family: The family name of the virtual machine size. + :vartype family: str + :ivar v_cp_us: The number of vCPUs supported by the virtual machine size. + :vartype v_cp_us: int + :ivar gpus: The number of gPUs supported by the virtual machine size. + :vartype gpus: int + :ivar os_vhd_size_mb: The OS VHD disk size, in MB, allowed by the virtual machine size. + :vartype os_vhd_size_mb: int + :ivar max_resource_volume_mb: The resource volume size, in MB, allowed by the virtual machine + size. + :vartype max_resource_volume_mb: int + :ivar memory_gb: The amount of memory, in GB, supported by the virtual machine size. + :vartype memory_gb: float + :ivar low_priority_capable: Specifies if the virtual machine size supports low priority VMs. + :vartype low_priority_capable: bool + :ivar premium_io: Specifies if the virtual machine size supports premium IO. + :vartype premium_io: bool + :param estimated_vm_prices: The estimated price information for using a VM. + :type estimated_vm_prices: ~azure_machine_learning_workspaces.models.EstimatedVmPrices + :param supported_compute_types: Specifies the compute types supported by the virtual machine + size. + :type supported_compute_types: list[str] + """ + + _validation = { + 'name': {'readonly': True}, + 'family': {'readonly': True}, + 'v_cp_us': {'readonly': True}, + 'gpus': {'readonly': True}, + 'os_vhd_size_mb': {'readonly': True}, + 'max_resource_volume_mb': {'readonly': True}, + 'memory_gb': {'readonly': True}, + 'low_priority_capable': {'readonly': True}, + 'premium_io': {'readonly': True}, + } + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'family': {'key': 'family', 'type': 'str'}, + 'v_cp_us': {'key': 'vCPUs', 'type': 'int'}, + 'gpus': {'key': 'gpus', 'type': 'int'}, + 'os_vhd_size_mb': {'key': 'osVhdSizeMB', 'type': 'int'}, + 'max_resource_volume_mb': {'key': 'maxResourceVolumeMB', 'type': 'int'}, + 'memory_gb': {'key': 'memoryGB', 'type': 'float'}, + 'low_priority_capable': {'key': 'lowPriorityCapable', 'type': 'bool'}, + 'premium_io': {'key': 'premiumIO', 'type': 'bool'}, + 'estimated_vm_prices': {'key': 'estimatedVMPrices', 'type': 'EstimatedVmPrices'}, + 'supported_compute_types': {'key': 'supportedComputeTypes', 'type': '[str]'}, + } + + def __init__( + self, + *, + estimated_vm_prices: Optional["EstimatedVmPrices"] = None, + supported_compute_types: Optional[List[str]] = None, + **kwargs + ): + super(VirtualMachineSize, self).__init__(**kwargs) + self.name = None + self.family = None + self.v_cp_us = None + self.gpus = None + self.os_vhd_size_mb = None + self.max_resource_volume_mb = None + self.memory_gb = None + self.low_priority_capable = None + self.premium_io = None + self.estimated_vm_prices = estimated_vm_prices + self.supported_compute_types = supported_compute_types + + +class VirtualMachineSizeListResult(msrest.serialization.Model): + """The List Virtual Machine size operation response. + + :param aml_compute: The list of virtual machine sizes supported by AmlCompute. + :type aml_compute: list[~azure_machine_learning_workspaces.models.VirtualMachineSize] + """ + + _attribute_map = { + 'aml_compute': {'key': 'amlCompute', 'type': '[VirtualMachineSize]'}, + } + + def __init__( + self, + *, + aml_compute: Optional[List["VirtualMachineSize"]] = None, + **kwargs + ): + super(VirtualMachineSizeListResult, self).__init__(**kwargs) + self.aml_compute = aml_compute + + +class VirtualMachineSshCredentials(msrest.serialization.Model): + """Admin credentials for virtual machine. + + :param username: Username of admin account. + :type username: str + :param password: Password of admin account. + :type password: str + :param public_key_data: Public key data. + :type public_key_data: str + :param private_key_data: Private key data. + :type private_key_data: str + """ + + _attribute_map = { + 'username': {'key': 'username', 'type': 'str'}, + 'password': {'key': 'password', 'type': 'str'}, + 'public_key_data': {'key': 'publicKeyData', 'type': 'str'}, + 'private_key_data': {'key': 'privateKeyData', 'type': 'str'}, + } + + def __init__( + self, + *, + username: Optional[str] = None, + password: Optional[str] = None, + public_key_data: Optional[str] = None, + private_key_data: Optional[str] = None, + **kwargs + ): + super(VirtualMachineSshCredentials, self).__init__(**kwargs) + self.username = username + self.password = password + self.public_key_data = public_key_data + self.private_key_data = private_key_data + + +class Workspace(Resource): + """An object that represents a machine learning workspace. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: Specifies the resource ID. + :vartype id: str + :ivar name: Specifies the name of the resource. + :vartype name: str + :param identity: The identity of the resource. + :type identity: ~azure_machine_learning_workspaces.models.Identity + :param location: Specifies the location of the resource. + :type location: str + :ivar type: Specifies the type of the resource. + :vartype type: str + :param tags: A set of tags. Contains resource tags defined as key/value pairs. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + :ivar workspace_id: The immutable id associated with this workspace. + :vartype workspace_id: str + :param description: The description of this workspace. + :type description: str + :param friendly_name: The friendly name for this workspace. This name in mutable. + :type friendly_name: str + :ivar creation_time: The creation time of the machine learning workspace in ISO8601 format. + :vartype creation_time: ~datetime.datetime + :param key_vault: ARM id of the key vault associated with this workspace. This cannot be + changed once the workspace has been created. + :type key_vault: str + :param application_insights: ARM id of the application insights associated with this workspace. + This cannot be changed once the workspace has been created. + :type application_insights: str + :param container_registry: ARM id of the container registry associated with this workspace. + This cannot be changed once the workspace has been created. + :type container_registry: str + :param storage_account: ARM id of the storage account associated with this workspace. This + cannot be changed once the workspace has been created. + :type storage_account: str + :param discovery_url: Url for the discovery service to identify regional endpoints for machine + learning experimentation services. + :type discovery_url: str + :ivar provisioning_state: The current deployment state of workspace resource. The + provisioningState is to indicate states for resource provisioning. Possible values include: + "Unknown", "Updating", "Creating", "Deleting", "Succeeded", "Failed", "Canceled". + :vartype provisioning_state: str or ~azure_machine_learning_workspaces.models.ProvisioningState + :param encryption: The encryption settings of Azure ML workspace. + :type encryption: ~azure_machine_learning_workspaces.models.EncryptionProperty + :param hbi_workspace: The flag to signal HBI data in the workspace and reduce diagnostic data + collected by the service. + :type hbi_workspace: bool + :ivar service_provisioned_resource_group: The name of the managed resource group created by + workspace RP in customer subscription if the workspace is CMK workspace. + :vartype service_provisioned_resource_group: str + :ivar private_link_count: Count of private connections in the workspace. + :vartype private_link_count: int + :param image_build_compute: The compute name for image build. + :type image_build_compute: str + :param allow_public_access_when_behind_vnet: The flag to indicate whether to allow public + access when behind VNet. + :type allow_public_access_when_behind_vnet: bool + :ivar private_endpoint_connections: The list of private endpoint connections in the workspace. + :vartype private_endpoint_connections: + list[~azure_machine_learning_workspaces.models.PrivateEndpointConnection] + :param shared_private_link_resources: The list of shared private link resources in this + workspace. + :type shared_private_link_resources: + list[~azure_machine_learning_workspaces.models.SharedPrivateLinkResource] + :ivar notebook_info: The notebook info of Azure ML workspace. + :vartype notebook_info: ~azure_machine_learning_workspaces.models.NotebookResourceInfo + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + 'workspace_id': {'readonly': True}, + 'creation_time': {'readonly': True}, + 'provisioning_state': {'readonly': True}, + 'service_provisioned_resource_group': {'readonly': True}, + 'private_link_count': {'readonly': True}, + 'private_endpoint_connections': {'readonly': True}, + 'notebook_info': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'identity': {'key': 'identity', 'type': 'Identity'}, + 'location': {'key': 'location', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + 'workspace_id': {'key': 'properties.workspaceId', 'type': 'str'}, + 'description': {'key': 'properties.description', 'type': 'str'}, + 'friendly_name': {'key': 'properties.friendlyName', 'type': 'str'}, + 'creation_time': {'key': 'properties.creationTime', 'type': 'iso-8601'}, + 'key_vault': {'key': 'properties.keyVault', 'type': 'str'}, + 'application_insights': {'key': 'properties.applicationInsights', 'type': 'str'}, + 'container_registry': {'key': 'properties.containerRegistry', 'type': 'str'}, + 'storage_account': {'key': 'properties.storageAccount', 'type': 'str'}, + 'discovery_url': {'key': 'properties.discoveryUrl', 'type': 'str'}, + 'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'}, + 'encryption': {'key': 'properties.encryption', 'type': 'EncryptionProperty'}, + 'hbi_workspace': {'key': 'properties.hbiWorkspace', 'type': 'bool'}, + 'service_provisioned_resource_group': {'key': 'properties.serviceProvisionedResourceGroup', 'type': 'str'}, + 'private_link_count': {'key': 'properties.privateLinkCount', 'type': 'int'}, + 'image_build_compute': {'key': 'properties.imageBuildCompute', 'type': 'str'}, + 'allow_public_access_when_behind_vnet': {'key': 'properties.allowPublicAccessWhenBehindVnet', 'type': 'bool'}, + 'private_endpoint_connections': {'key': 'properties.privateEndpointConnections', 'type': '[PrivateEndpointConnection]'}, + 'shared_private_link_resources': {'key': 'properties.sharedPrivateLinkResources', 'type': '[SharedPrivateLinkResource]'}, + 'notebook_info': {'key': 'properties.notebookInfo', 'type': 'NotebookResourceInfo'}, + } + + def __init__( + self, + *, + identity: Optional["Identity"] = None, + location: Optional[str] = None, + tags: Optional[Dict[str, str]] = None, + sku: Optional["Sku"] = None, + description: Optional[str] = None, + friendly_name: Optional[str] = None, + key_vault: Optional[str] = None, + application_insights: Optional[str] = None, + container_registry: Optional[str] = None, + storage_account: Optional[str] = None, + discovery_url: Optional[str] = None, + encryption: Optional["EncryptionProperty"] = None, + hbi_workspace: Optional[bool] = False, + image_build_compute: Optional[str] = None, + allow_public_access_when_behind_vnet: Optional[bool] = False, + shared_private_link_resources: Optional[List["SharedPrivateLinkResource"]] = None, + **kwargs + ): + super(Workspace, self).__init__(identity=identity, location=location, tags=tags, sku=sku, **kwargs) + self.workspace_id = None + self.description = description + self.friendly_name = friendly_name + self.creation_time = None + self.key_vault = key_vault + self.application_insights = application_insights + self.container_registry = container_registry + self.storage_account = storage_account + self.discovery_url = discovery_url + self.provisioning_state = None + self.encryption = encryption + self.hbi_workspace = hbi_workspace + self.service_provisioned_resource_group = None + self.private_link_count = None + self.image_build_compute = image_build_compute + self.allow_public_access_when_behind_vnet = allow_public_access_when_behind_vnet + self.private_endpoint_connections = None + self.shared_private_link_resources = shared_private_link_resources + self.notebook_info = None + + +class WorkspaceConnection(msrest.serialization.Model): + """Workspace connection. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar id: ResourceId of the workspace connection. + :vartype id: str + :ivar name: Friendly name of the workspace connection. + :vartype name: str + :ivar type: Resource type of workspace connection. + :vartype type: str + :param category: Category of the workspace connection. + :type category: str + :param target: Target of the workspace connection. + :type target: str + :param auth_type: Authorization type of the workspace connection. + :type auth_type: str + :param value: Value details of the workspace connection. + :type value: str + """ + + _validation = { + 'id': {'readonly': True}, + 'name': {'readonly': True}, + 'type': {'readonly': True}, + } + + _attribute_map = { + 'id': {'key': 'id', 'type': 'str'}, + 'name': {'key': 'name', 'type': 'str'}, + 'type': {'key': 'type', 'type': 'str'}, + 'category': {'key': 'properties.category', 'type': 'str'}, + 'target': {'key': 'properties.target', 'type': 'str'}, + 'auth_type': {'key': 'properties.authType', 'type': 'str'}, + 'value': {'key': 'properties.value', 'type': 'str'}, + } + + def __init__( + self, + *, + category: Optional[str] = None, + target: Optional[str] = None, + auth_type: Optional[str] = None, + value: Optional[str] = None, + **kwargs + ): + super(WorkspaceConnection, self).__init__(**kwargs) + self.id = None + self.name = None + self.type = None + self.category = category + self.target = target + self.auth_type = auth_type + self.value = value + + +class WorkspaceConnectionDto(msrest.serialization.Model): + """object used for creating workspace connection. + + :param name: Friendly name of the workspace connection. + :type name: str + :param category: Category of the workspace connection. + :type category: str + :param target: Target of the workspace connection. + :type target: str + :param auth_type: Authorization type of the workspace connection. + :type auth_type: str + :param value: Value details of the workspace connection. + :type value: str + """ + + _attribute_map = { + 'name': {'key': 'name', 'type': 'str'}, + 'category': {'key': 'properties.category', 'type': 'str'}, + 'target': {'key': 'properties.target', 'type': 'str'}, + 'auth_type': {'key': 'properties.authType', 'type': 'str'}, + 'value': {'key': 'properties.value', 'type': 'str'}, + } + + def __init__( + self, + *, + name: Optional[str] = None, + category: Optional[str] = None, + target: Optional[str] = None, + auth_type: Optional[str] = None, + value: Optional[str] = None, + **kwargs + ): + super(WorkspaceConnectionDto, self).__init__(**kwargs) + self.name = name + self.category = category + self.target = target + self.auth_type = auth_type + self.value = value + + +class WorkspaceListResult(msrest.serialization.Model): + """The result of a request to list machine learning workspaces. + + :param 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. + :type value: list[~azure_machine_learning_workspaces.models.Workspace] + :param next_link: The URI that can be used to request the next list of machine learning + workspaces. + :type next_link: str + """ + + _attribute_map = { + 'value': {'key': 'value', 'type': '[Workspace]'}, + 'next_link': {'key': 'nextLink', 'type': 'str'}, + } + + def __init__( + self, + *, + value: Optional[List["Workspace"]] = None, + next_link: Optional[str] = None, + **kwargs + ): + super(WorkspaceListResult, self).__init__(**kwargs) + self.value = value + self.next_link = next_link + + +class WorkspaceSku(msrest.serialization.Model): + """AML workspace sku information. + + Variables are only populated by the server, and will be ignored when sending a request. + + :ivar resource_type: + :vartype resource_type: str + :ivar skus: The list of workspace sku settings. + :vartype skus: list[~azure_machine_learning_workspaces.models.SkuSettings] + """ + + _validation = { + 'resource_type': {'readonly': True}, + 'skus': {'readonly': True}, + } + + _attribute_map = { + 'resource_type': {'key': 'resourceType', 'type': 'str'}, + 'skus': {'key': 'skus', 'type': '[SkuSettings]'}, + } + + def __init__( + self, + **kwargs + ): + super(WorkspaceSku, self).__init__(**kwargs) + self.resource_type = None + self.skus = None + + +class WorkspaceUpdateParameters(msrest.serialization.Model): + """The parameters for updating a machine learning workspace. + + :param tags: A set of tags. The resource tags for the machine learning workspace. + :type tags: dict[str, str] + :param sku: The sku of the workspace. + :type sku: ~azure_machine_learning_workspaces.models.Sku + :param description: The description of this workspace. + :type description: str + :param friendly_name: The friendly name for this workspace. + :type friendly_name: str + """ + + _attribute_map = { + 'tags': {'key': 'tags', 'type': '{str}'}, + 'sku': {'key': 'sku', 'type': 'Sku'}, + 'description': {'key': 'properties.description', 'type': 'str'}, + 'friendly_name': {'key': 'properties.friendlyName', 'type': 'str'}, + } + + def __init__( + self, + *, + tags: Optional[Dict[str, str]] = None, + sku: Optional["Sku"] = None, + description: Optional[str] = None, + friendly_name: Optional[str] = None, + **kwargs + ): + super(WorkspaceUpdateParameters, self).__init__(**kwargs) + self.tags = tags + self.sku = sku + self.description = description + self.friendly_name = friendly_name diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/__init__.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/__init__.py new file mode 100644 index 00000000000..516999b100d --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/__init__.py @@ -0,0 +1,35 @@ +# 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 ._operations import Operations +from ._workspaces_operations import WorkspacesOperations +from ._workspace_features_operations import WorkspaceFeaturesOperations +from ._notebooks_operations import NotebooksOperations +from ._usages_operations import UsagesOperations +from ._virtual_machine_sizes_operations import VirtualMachineSizesOperations +from ._quotas_operations import QuotasOperations +from ._workspace_connections_operations import WorkspaceConnectionsOperations +from ._machine_learning_compute_operations import MachineLearningComputeOperations +from ._azure_machine_learning_workspaces_operations import AzureMachineLearningWorkspacesOperationsMixin +from ._private_endpoint_connections_operations import PrivateEndpointConnectionsOperations +from ._private_link_resources_operations import PrivateLinkResourcesOperations + +__all__ = [ + 'Operations', + 'WorkspacesOperations', + 'WorkspaceFeaturesOperations', + 'NotebooksOperations', + 'UsagesOperations', + 'VirtualMachineSizesOperations', + 'QuotasOperations', + 'WorkspaceConnectionsOperations', + 'MachineLearningComputeOperations', + 'AzureMachineLearningWorkspacesOperationsMixin', + 'PrivateEndpointConnectionsOperations', + 'PrivateLinkResourcesOperations', +] diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_azure_machine_learning_workspaces_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_azure_machine_learning_workspaces_operations.py new file mode 100644 index 00000000000..cca7b84e78d --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_azure_machine_learning_workspaces_operations.py @@ -0,0 +1,94 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class AzureMachineLearningWorkspacesOperationsMixin(object): + + def list_skus( + self, + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.SkuListResult"] + """Lists all skus with associated features. + + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either SkuListResult or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.SkuListResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.SkuListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_skus.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('SkuListResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list_skus.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/workspaces/skus'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_machine_learning_compute_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_machine_learning_compute_operations.py new file mode 100644 index 00000000000..6d20047572a --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_machine_learning_compute_operations.py @@ -0,0 +1,931 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.core.polling import LROPoller, NoPolling, PollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.arm_polling import ARMPolling + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar, Union + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class MachineLearningComputeOperations(object): + """MachineLearningComputeOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list_by_workspace( + self, + resource_group_name, # type: str + workspace_name, # type: str + skiptoken=None, # type: Optional[str] + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.PaginatedComputeResourcesList"] + """Gets computes in specified workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedComputeResourcesList or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.PaginatedComputeResourcesList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PaginatedComputeResourcesList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_workspace.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('PaginatedComputeResourcesList', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list_by_workspace.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes'} # type: ignore + + def get( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "models.ComputeResource" + """Gets compute definition by its name. Any secrets (storage keys, service credentials, etc) are + not returned - use 'keys' nested resource to get them. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: ComputeResource, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.ComputeResource + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + def _create_or_update_initial( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + parameters, # type: "models.ComputeResource" + **kwargs # type: Any + ): + # type: (...) -> "models.ComputeResource" + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self._create_or_update_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'ComputeResource') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + response_headers = {} + if response.status_code == 200: + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if response.status_code == 201: + response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation')) + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, response_headers) + + return deserialized + _create_or_update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + def begin_create_or_update( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + parameters, # type: "models.ComputeResource" + **kwargs # type: Any + ): + # type: (...) -> LROPoller["models.ComputeResource"] + """Creates or updates compute. This call will overwrite a compute if it exists. This is a + nonrecoverable operation. If your intent is to create a new compute, do a GET first to verify + that it does not exist yet. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :param parameters: Payload with Machine Learning compute definition. + :type parameters: ~azure_machine_learning_workspaces.models.ComputeResource + :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: True for ARMPolling, False for no polling, or a + polling object for 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 ComputeResource or the result of cls(response) + :rtype: ~azure.core.polling.LROPoller[~azure_machine_learning_workspaces.models.ComputeResource] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._create_or_update_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + response_headers = {} + response = pipeline_response.http_response + response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation')) + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, response_headers) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + def _update_initial( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + parameters, # type: "models.ClusterUpdateParameters" + **kwargs # type: Any + ): + # type: (...) -> "models.ComputeResource" + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self._update_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'ClusterUpdateParameters') + body_content_kwargs['content'] = body_content + request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + _update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + def begin_update( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + parameters, # type: "models.ClusterUpdateParameters" + **kwargs # type: Any + ): + # type: (...) -> LROPoller["models.ComputeResource"] + """Updates properties of a compute. This call will overwrite a compute if it exists. This is a + nonrecoverable operation. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :param parameters: Additional parameters for cluster update. + :type parameters: ~azure_machine_learning_workspaces.models.ClusterUpdateParameters + :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: True for ARMPolling, False for no polling, or a + polling object for 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 ComputeResource or the result of cls(response) + :rtype: ~azure.core.polling.LROPoller[~azure_machine_learning_workspaces.models.ComputeResource] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeResource"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._update_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + parameters=parameters, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('ComputeResource', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + def _delete_initial( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + underlying_resource_action, # type: Union[str, "models.UnderlyingResourceAction"] + **kwargs # type: Any + ): + # type: (...) -> None + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self._delete_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + query_parameters['underlyingResourceAction'] = self._serialize.query("underlying_resource_action", underlying_resource_action, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + response_headers = {} + if response.status_code == 202: + response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation')) + response_headers['Location']=self._deserialize('str', response.headers.get('Location')) + + if cls: + return cls(pipeline_response, None, response_headers) + + _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + def begin_delete( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + underlying_resource_action, # type: Union[str, "models.UnderlyingResourceAction"] + **kwargs # type: Any + ): + # type: (...) -> LROPoller[None] + """Deletes specified Machine Learning compute. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :param underlying_resource_action: Delete the underlying compute if 'Delete', or detach the + underlying compute from workspace if 'Detach'. + :type underlying_resource_action: str or ~azure_machine_learning_workspaces.models.UnderlyingResourceAction + :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: True for ARMPolling, False for no polling, or a + polling object for 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: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[None] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._delete_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + compute_name=compute_name, + underlying_resource_action=underlying_resource_action, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + if cls: + return cls(pipeline_response, None, {}) + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'} # type: ignore + + def list_nodes( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.AmlComputeNodesInformation"] + """Get the details (e.g IP address, port etc) of all the compute nodes in the compute. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either AmlComputeNodesInformation or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.AmlComputeNodesInformation] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.AmlComputeNodesInformation"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_nodes.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('AmlComputeNodesInformation', pipeline_response) + list_of_elem = deserialized.nodes + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list_nodes.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listNodes'} # type: ignore + + def list_keys( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "models.ComputeSecrets" + """Gets secrets related to Machine Learning compute (storage keys, service credentials, etc). + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: ComputeSecrets, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.ComputeSecrets + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ComputeSecrets"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.list_keys.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ComputeSecrets', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listKeys'} # type: ignore + + def start( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + """Posts a start action to a compute instance. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.start.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + start.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/start'} # type: ignore + + def stop( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + """Posts a stop action to a compute instance. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.stop.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + stop.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/stop'} # type: ignore + + def restart( + self, + resource_group_name, # type: str + workspace_name, # type: str + compute_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + """Posts a restart action to a compute instance. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param compute_name: Name of the Azure Machine Learning compute. + :type compute_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.restart.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'computeName': self._serialize.url("compute_name", compute_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + restart.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/restart'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_notebooks_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_notebooks_operations.py new file mode 100644 index 00000000000..9e541bca756 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_notebooks_operations.py @@ -0,0 +1,166 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.core.polling import LROPoller, NoPolling, PollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.arm_polling import ARMPolling + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Optional, TypeVar, Union + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class NotebooksOperations(object): + """NotebooksOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def _prepare_initial( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> Optional["models.NotebookResourceInfo"] + cls = kwargs.pop('cls', None) # type: ClsType[Optional["models.NotebookResourceInfo"]] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self._prepare_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('NotebookResourceInfo', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + _prepare_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/prepareNotebook'} # type: ignore + + def begin_prepare( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> LROPoller["models.NotebookResourceInfo"] + """prepare. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_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: True for ARMPolling, False for no polling, or a + polling object for 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 NotebookResourceInfo or the result of cls(response) + :rtype: ~azure.core.polling.LROPoller[~azure_machine_learning_workspaces.models.NotebookResourceInfo] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["models.NotebookResourceInfo"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._prepare_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('NotebookResourceInfo', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_prepare.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/prepareNotebook'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_operations.py new file mode 100644 index 00000000000..9b568ce1c77 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_operations.py @@ -0,0 +1,110 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class Operations(object): + """Operations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.OperationListResult"] + """Lists all of the available Azure Machine Learning Workspaces REST API operations. + + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either OperationListResult or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.OperationListResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.OperationListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('OperationListResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list.metadata = {'url': '/providers/Microsoft.MachineLearningServices/operations'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_private_endpoint_connections_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_private_endpoint_connections_operations.py new file mode 100644 index 00000000000..642ba9195ff --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_private_endpoint_connections_operations.py @@ -0,0 +1,304 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.core.polling import LROPoller, NoPolling, PollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.arm_polling import ARMPolling + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Optional, TypeVar, Union + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class PrivateEndpointConnectionsOperations(object): + """PrivateEndpointConnectionsOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def get( + self, + resource_group_name, # type: str + workspace_name, # type: str + private_endpoint_connection_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "models.PrivateEndpointConnection" + """Gets the specified private endpoint connection associated with the workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param private_endpoint_connection_name: The name of the private endpoint connection associated + with the workspace. + :type private_endpoint_connection_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: PrivateEndpointConnection, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.PrivateEndpointConnection + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PrivateEndpointConnection"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'privateEndpointConnectionName': self._serialize.url("private_endpoint_connection_name", private_endpoint_connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('PrivateEndpointConnection', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateEndpointConnections/{privateEndpointConnectionName}'} # type: ignore + + def put( + self, + resource_group_name, # type: str + workspace_name, # type: str + private_endpoint_connection_name, # type: str + properties, # type: "models.PrivateEndpointConnection" + **kwargs # type: Any + ): + # type: (...) -> "models.PrivateEndpointConnection" + """Update the state of specified private endpoint connection associated with the workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param private_endpoint_connection_name: The name of the private endpoint connection associated + with the workspace. + :type private_endpoint_connection_name: str + :param properties: The private endpoint connection properties. + :type properties: ~azure_machine_learning_workspaces.models.PrivateEndpointConnection + :keyword callable cls: A custom type or function that will be passed the direct response + :return: PrivateEndpointConnection, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.PrivateEndpointConnection + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PrivateEndpointConnection"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.put.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'privateEndpointConnectionName': self._serialize.url("private_endpoint_connection_name", private_endpoint_connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(properties, 'PrivateEndpointConnection') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('PrivateEndpointConnection', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + put.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateEndpointConnections/{privateEndpointConnectionName}'} # type: ignore + + def _delete_initial( + self, + resource_group_name, # type: str + workspace_name, # type: str + private_endpoint_connection_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self._delete_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'privateEndpointConnectionName': self._serialize.url("private_endpoint_connection_name", private_endpoint_connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateEndpointConnections/{privateEndpointConnectionName}'} # type: ignore + + def begin_delete( + self, + resource_group_name, # type: str + workspace_name, # type: str + private_endpoint_connection_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> LROPoller[None] + """Deletes the specified private endpoint connection associated with the workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param private_endpoint_connection_name: The name of the private endpoint connection associated + with the workspace. + :type private_endpoint_connection_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: True for ARMPolling, False for no polling, or a + polling object for 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: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[None] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._delete_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + private_endpoint_connection_name=private_endpoint_connection_name, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + if cls: + return cls(pipeline_response, None, {}) + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'privateEndpointConnectionName': self._serialize.url("private_endpoint_connection_name", private_endpoint_connection_name, 'str'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateEndpointConnections/{privateEndpointConnectionName}'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_private_link_resources_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_private_link_resources_operations.py new file mode 100644 index 00000000000..9e2314373fc --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_private_link_resources_operations.py @@ -0,0 +1,104 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class PrivateLinkResourcesOperations(object): + """PrivateLinkResourcesOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list_by_workspace( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "models.PrivateLinkResourceListResult" + """Gets the private link resources that need to be created for a workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: PrivateLinkResourceListResult, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.PrivateLinkResourceListResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PrivateLinkResourceListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.list_by_workspace.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('PrivateLinkResourceListResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_by_workspace.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/privateLinkResources'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_quotas_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_quotas_operations.py new file mode 100644 index 00000000000..025247e1fad --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_quotas_operations.py @@ -0,0 +1,181 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class QuotasOperations(object): + """QuotasOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def update( + self, + location, # type: str + parameters, # type: "models.QuotaUpdateParameters" + **kwargs # type: Any + ): + # type: (...) -> "models.UpdateWorkspaceQuotasResult" + """Update quota for each VM family in workspace. + + :param location: The location for update quota is queried. + :type location: str + :param parameters: Quota update parameters. + :type parameters: ~azure_machine_learning_workspaces.models.QuotaUpdateParameters + :keyword callable cls: A custom type or function that will be passed the direct response + :return: UpdateWorkspaceQuotasResult, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.UpdateWorkspaceQuotasResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.UpdateWorkspaceQuotasResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.update.metadata['url'] # type: ignore + path_format_arguments = { + 'location': self._serialize.url("location", location, 'str', pattern=r'^[-\w\._]+$'), + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'QuotaUpdateParameters') + body_content_kwargs['content'] = body_content + request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('UpdateWorkspaceQuotasResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + update.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/locations/{location}/updateQuotas'} # type: ignore + + def list( + self, + location, # type: str + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.ListWorkspaceQuotas"] + """Gets the currently assigned Workspace Quotas based on VMFamily. + + :param location: The location for which resource usage is queried. + :type location: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either ListWorkspaceQuotas or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.ListWorkspaceQuotas] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ListWorkspaceQuotas"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'location': self._serialize.url("location", location, 'str', pattern=r'^[-\w\._]+$'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('ListWorkspaceQuotas', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **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) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/locations/{location}/Quotas'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_usages_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_usages_operations.py new file mode 100644 index 00000000000..fe87b53386f --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_usages_operations.py @@ -0,0 +1,118 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class UsagesOperations(object): + """UsagesOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + location, # type: str + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.ListUsagesResult"] + """Gets the current usage information as well as limits for AML resources for given subscription + and location. + + :param location: The location for which resource usage is queried. + :type location: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either ListUsagesResult or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.ListUsagesResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ListUsagesResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'location': self._serialize.url("location", location, 'str', pattern=r'^[-\w\._]+$'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('ListUsagesResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **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) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/locations/{location}/usages'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_virtual_machine_sizes_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_virtual_machine_sizes_operations.py new file mode 100644 index 00000000000..64960e85c76 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_virtual_machine_sizes_operations.py @@ -0,0 +1,110 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class VirtualMachineSizesOperations(object): + """VirtualMachineSizesOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + location, # type: str + compute_type=None, # type: Optional[str] + recommended=None, # type: Optional[bool] + **kwargs # type: Any + ): + # type: (...) -> "models.VirtualMachineSizeListResult" + """Returns supported VM Sizes in a location. + + :param location: The location upon which virtual-machine-sizes is queried. + :type location: str + :param compute_type: Type of compute to filter by. + :type compute_type: str + :param recommended: Specifies whether to return recommended vm sizes or all vm sizes. + :type recommended: bool + :keyword callable cls: A custom type or function that will be passed the direct response + :return: VirtualMachineSizeListResult, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.VirtualMachineSizeListResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.VirtualMachineSizeListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'location': self._serialize.url("location", location, 'str', pattern=r'^[-\w\._]+$'), + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if compute_type is not None: + query_parameters['compute-type'] = self._serialize.query("compute_type", compute_type, 'str') + if recommended is not None: + query_parameters['recommended'] = self._serialize.query("recommended", recommended, 'bool') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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) + raise HttpResponseError(response=response, error_format=ARMErrorFormat) + + deserialized = self._deserialize('VirtualMachineSizeListResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.MachineLearningServices/locations/{location}/vmSizes'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspace_connections_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspace_connections_operations.py new file mode 100644 index 00000000000..3489ddae6eb --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspace_connections_operations.py @@ -0,0 +1,329 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class WorkspaceConnectionsOperations(object): + """WorkspaceConnectionsOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + resource_group_name, # type: str + workspace_name, # type: str + target=None, # type: Optional[str] + category=None, # type: Optional[str] + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.PaginatedWorkspaceConnectionsList"] + """List all connections under a AML workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param target: Target of the workspace connection. + :type target: str + :param category: Category of the workspace connection. + :type category: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either PaginatedWorkspaceConnectionsList or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.PaginatedWorkspaceConnectionsList] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.PaginatedWorkspaceConnectionsList"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if target is not None: + query_parameters['target'] = self._serialize.query("target", target, 'str') + if category is not None: + query_parameters['category'] = self._serialize.query("category", category, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('PaginatedWorkspaceConnectionsList', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + 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/workspaces/{workspaceName}/connections'} # type: ignore + + def create( + self, + resource_group_name, # type: str + workspace_name, # type: str + connection_name, # type: str + parameters, # type: "models.WorkspaceConnectionDto" + **kwargs # type: Any + ): + # type: (...) -> "models.WorkspaceConnection" + """Add a new workspace connection. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param connection_name: Friendly name of the workspace connection. + :type connection_name: str + :param parameters: The object for creating or updating a new workspace connection. + :type parameters: ~azure_machine_learning_workspaces.models.WorkspaceConnectionDto + :keyword callable cls: A custom type or function that will be passed the direct response + :return: WorkspaceConnection, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.WorkspaceConnection + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.WorkspaceConnection"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.create.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'connectionName': self._serialize.url("connection_name", connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'WorkspaceConnectionDto') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('WorkspaceConnection', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + create.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/connections/{connectionName}'} # type: ignore + + def get( + self, + resource_group_name, # type: str + workspace_name, # type: str + connection_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "models.WorkspaceConnection" + """Get the detail of a workspace connection. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param connection_name: Friendly name of the workspace connection. + :type connection_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: WorkspaceConnection, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.WorkspaceConnection + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.WorkspaceConnection"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'connectionName': self._serialize.url("connection_name", connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('WorkspaceConnection', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/connections/{connectionName}'} # type: ignore + + def delete( + self, + resource_group_name, # type: str + workspace_name, # type: str + connection_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + """Delete a workspace connection. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param connection_name: Friendly name of the workspace connection. + :type connection_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.delete.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + 'connectionName': self._serialize.url("connection_name", connection_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200, 204]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/connections/{connectionName}'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspace_features_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspace_features_operations.py new file mode 100644 index 00000000000..f28d14b7bbd --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspace_features_operations.py @@ -0,0 +1,122 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.mgmt.core.exceptions import ARMErrorFormat + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class WorkspaceFeaturesOperations(object): + """WorkspaceFeaturesOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def list( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.ListAmlUserFeatureResult"] + """Lists all enabled features for a workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either ListAmlUserFeatureResult or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.ListAmlUserFeatureResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ListAmlUserFeatureResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('ListAmlUserFeatureResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + 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/workspaces/{workspaceName}/features'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspaces_operations.py b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspaces_operations.py new file mode 100644 index 00000000000..1df9daf3a21 --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/operations/_workspaces_operations.py @@ -0,0 +1,688 @@ +# 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 TYPE_CHECKING +import warnings + +from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error +from azure.core.paging import ItemPaged +from azure.core.pipeline import PipelineResponse +from azure.core.pipeline.transport import HttpRequest, HttpResponse +from azure.core.polling import LROPoller, NoPolling, PollingMethod +from azure.mgmt.core.exceptions import ARMErrorFormat +from azure.mgmt.core.polling.arm_polling import ARMPolling + +from .. import models + +if TYPE_CHECKING: + # pylint: disable=unused-import,ungrouped-imports + from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar, Union + + T = TypeVar('T') + ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] + +class WorkspacesOperations(object): + """WorkspacesOperations operations. + + You should not instantiate this class directly. Instead, you should create a Client instance that + instantiates it for you and attaches it as an attribute. + + :ivar models: Alias to model classes used in this operation group. + :type models: ~azure_machine_learning_workspaces.models + :param client: Client for service requests. + :param config: Configuration of service client. + :param serializer: An object model serializer. + :param deserializer: An object model deserializer. + """ + + models = models + + def __init__(self, client, config, serializer, deserializer): + self._client = client + self._serialize = serializer + self._deserialize = deserializer + self._config = config + + def get( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "models.Workspace" + """Gets the properties of the specified machine learning workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Workspace, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.Workspace + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.Workspace"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.get.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Workspace', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + def _create_or_update_initial( + self, + resource_group_name, # type: str + workspace_name, # type: str + parameters, # type: "models.Workspace" + **kwargs # type: Any + ): + # type: (...) -> Optional["models.Workspace"] + cls = kwargs.pop('cls', None) # type: ClsType[Optional["models.Workspace"]] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self._create_or_update_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'Workspace') + body_content_kwargs['content'] = body_content + request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200, 201, 202]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = self._deserialize(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('Workspace', pipeline_response) + + if response.status_code == 201: + deserialized = self._deserialize('Workspace', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + _create_or_update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + def begin_create_or_update( + self, + resource_group_name, # type: str + workspace_name, # type: str + parameters, # type: "models.Workspace" + **kwargs # type: Any + ): + # type: (...) -> LROPoller["models.Workspace"] + """Creates or updates a workspace with the specified parameters. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param parameters: The parameters for creating or updating a machine learning workspace. + :type parameters: ~azure_machine_learning_workspaces.models.Workspace + :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: True for ARMPolling, False for no polling, or a + polling object for 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 Workspace or the result of cls(response) + :rtype: ~azure.core.polling.LROPoller[~azure_machine_learning_workspaces.models.Workspace] + :raises ~azure.core.exceptions.HttpResponseError: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType["models.Workspace"] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._create_or_update_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + parameters=parameters, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + deserialized = self._deserialize('Workspace', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + return deserialized + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + def _delete_initial( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self._delete_initial.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.delete(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + def begin_delete( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> LROPoller[None] + """Deletes a machine learning workspace. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_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: True for ARMPolling, False for no polling, or a + polling object for 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: + """ + polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] + cls = kwargs.pop('cls', None) # type: ClsType[None] + lro_delay = kwargs.pop( + 'polling_interval', + self._config.polling_interval + ) + cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] + if cont_token is None: + raw_result = self._delete_initial( + resource_group_name=resource_group_name, + workspace_name=workspace_name, + cls=lambda x,y,z: x, + **kwargs + ) + + kwargs.pop('error_map', None) + kwargs.pop('content_type', None) + + def get_long_running_output(pipeline_response): + if cls: + return cls(pipeline_response, None, {}) + + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + + if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + elif polling is False: polling_method = 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 + ) + else: + return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + def update( + self, + resource_group_name, # type: str + workspace_name, # type: str + parameters, # type: "models.WorkspaceUpdateParameters" + **kwargs # type: Any + ): + # type: (...) -> "models.Workspace" + """Updates a machine learning workspace with the specified parameters. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :param parameters: The parameters for updating a machine learning workspace. + :type parameters: ~azure_machine_learning_workspaces.models.WorkspaceUpdateParameters + :keyword callable cls: A custom type or function that will be passed the direct response + :return: Workspace, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.Workspace + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.Workspace"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + content_type = kwargs.pop("content_type", "application/json") + accept = "application/json" + + # Construct URL + url = self.update.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + body_content_kwargs = {} # type: Dict[str, Any] + body_content = self._serialize.body(parameters, 'WorkspaceUpdateParameters') + body_content_kwargs['content'] = body_content + request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('Workspace', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}'} # type: ignore + + def list_by_resource_group( + self, + resource_group_name, # type: str + skiptoken=None, # type: Optional[str] + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.WorkspaceListResult"] + """Lists all the available machine learning workspaces under the specified resource group. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either WorkspaceListResult or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.WorkspaceListResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.WorkspaceListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_resource_group.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('WorkspaceListResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + return pipeline_response + + return ItemPaged( + get_next, extract_data + ) + list_by_resource_group.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces'} # type: ignore + + def list_keys( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> "models.ListWorkspaceKeysResult" + """Lists all the keys associated with this workspace. This includes keys for the storage account, + app insights and password for container registry. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: ListWorkspaceKeysResult, or the result of cls(response) + :rtype: ~azure_machine_learning_workspaces.models.ListWorkspaceKeysResult + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.ListWorkspaceKeysResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.list_keys.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + deserialized = self._deserialize('ListWorkspaceKeysResult', pipeline_response) + + if cls: + return cls(pipeline_response, deserialized, {}) + + return deserialized + list_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/listKeys'} # type: ignore + + def resync_keys( + self, + resource_group_name, # type: str + workspace_name, # type: str + **kwargs # type: Any + ): + # type: (...) -> None + """Resync all the keys associated with this workspace. This includes keys for the storage account, + app insights and password for container registry. + + :param resource_group_name: Name of the resource group in which workspace is located. + :type resource_group_name: str + :param workspace_name: Name of Azure Machine Learning workspace. + :type workspace_name: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: None, or the result of cls(response) + :rtype: None + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType[None] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + # Construct URL + url = self.resync_keys.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), + 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + request = self._client.post(url, query_parameters, header_parameters) + pipeline_response = self._client._pipeline.run(request, stream=False, **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(models.MachineLearningServiceError, response) + raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) + + if cls: + return cls(pipeline_response, None, {}) + + resync_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/resyncKeys'} # type: ignore + + def list_by_subscription( + self, + skiptoken=None, # type: Optional[str] + **kwargs # type: Any + ): + # type: (...) -> Iterable["models.WorkspaceListResult"] + """Lists all the available machine learning workspaces under the specified subscription. + + :param skiptoken: Continuation token for pagination. + :type skiptoken: str + :keyword callable cls: A custom type or function that will be passed the direct response + :return: An iterator like instance of either WorkspaceListResult or the result of cls(response) + :rtype: ~azure.core.paging.ItemPaged[~azure_machine_learning_workspaces.models.WorkspaceListResult] + :raises: ~azure.core.exceptions.HttpResponseError + """ + cls = kwargs.pop('cls', None) # type: ClsType["models.WorkspaceListResult"] + error_map = { + 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError + } + error_map.update(kwargs.pop('error_map', {})) + api_version = "2020-08-01" + accept = "application/json" + + def prepare_request(next_link=None): + # Construct headers + header_parameters = {} # type: Dict[str, Any] + header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') + + if not next_link: + # Construct URL + url = self.list_by_subscription.metadata['url'] # type: ignore + path_format_arguments = { + 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), + } + url = self._client.format_url(url, **path_format_arguments) + # Construct parameters + query_parameters = {} # type: Dict[str, Any] + query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') + if skiptoken is not None: + query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str') + + request = self._client.get(url, query_parameters, header_parameters) + else: + url = next_link + query_parameters = {} # type: Dict[str, Any] + request = self._client.get(url, query_parameters, header_parameters) + return request + + def extract_data(pipeline_response): + deserialized = self._deserialize('WorkspaceListResult', pipeline_response) + list_of_elem = deserialized.value + if cls: + list_of_elem = cls(list_of_elem) + return deserialized.next_link or None, iter(list_of_elem) + + def get_next(next_link=None): + request = prepare_request(next_link) + + pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) + response = pipeline_response.http_response + + if response.status_code not in [200]: + error = self._deserialize(models.MachineLearningServiceError, response) + map_error(status_code=response.status_code, response=response, error_map=error_map) + 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/workspaces'} # type: ignore diff --git a/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/py.typed b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/py.typed new file mode 100644 index 00000000000..e5aff4f83af --- /dev/null +++ b/src/machinelearningservices/azext_machinelearningservices/vendored_sdks/machinelearningservices/py.typed @@ -0,0 +1 @@ +# Marker file for PEP 561. \ No newline at end of file diff --git a/src/machinelearningservices/report.md b/src/machinelearningservices/report.md new file mode 100644 index 00000000000..054358d8c23 --- /dev/null +++ b/src/machinelearningservices/report.md @@ -0,0 +1,969 @@ +# Azure CLI Module Creation Report + +## EXTENSION +|CLI Extension|Command Groups| +|---------|------------| +|az machinelearningservices|[groups](#CommandGroups) + +## GROUPS +### Command groups in `az machinelearningservices` extension +|CLI Command Group|Group Swagger name|Commands| +|---------|------------|--------| +|az machinelearningservices workspace|Workspaces|[commands](#CommandsInWorkspaces)| +|az machinelearningservices workspace-feature|WorkspaceFeatures|[commands](#CommandsInWorkspaceFeatures)| +|az machinelearningservices notebook|Notebooks|[commands](#CommandsInNotebooks)| +|az machinelearningservices usage|Usages|[commands](#CommandsInUsages)| +|az machinelearningservices virtual-machine-size|VirtualMachineSizes|[commands](#CommandsInVirtualMachineSizes)| +|az machinelearningservices quota|Quotas|[commands](#CommandsInQuotas)| +|az machinelearningservices workspace-connection|WorkspaceConnections|[commands](#CommandsInWorkspaceConnections)| +|az machinelearningservices machine-learning-compute|MachineLearningCompute|[commands](#CommandsInMachineLearningCompute)| +|az machinelearningservices||[commands](#CommandsIn)| +|az machinelearningservices private-endpoint-connection|PrivateEndpointConnections|[commands](#CommandsInPrivateEndpointConnections)| +|az machinelearningservices private-link-resource|PrivateLinkResources|[commands](#CommandsInPrivateLinkResources)| + +## COMMANDS +### Commands in `az machinelearningservices` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices list-sku](#ListSkus)|ListSkus|[Parameters](#ParametersListSkus)|[Example](#ExamplesListSkus)| + +### Commands in `az machinelearningservices machine-learning-compute` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices machine-learning-compute list](#MachineLearningComputeListByWorkspace)|ListByWorkspace|[Parameters](#ParametersMachineLearningComputeListByWorkspace)|[Example](#ExamplesMachineLearningComputeListByWorkspace)| +|[az machinelearningservices machine-learning-compute show](#MachineLearningComputeGet)|Get|[Parameters](#ParametersMachineLearningComputeGet)|[Example](#ExamplesMachineLearningComputeGet)| +|[az machinelearningservices machine-learning-compute aks create](#MachineLearningComputeCreateOrUpdate#Create#AKS)|CreateOrUpdate#Create#AKS|[Parameters](#ParametersMachineLearningComputeCreateOrUpdate#Create#AKS)|[Example](#ExamplesMachineLearningComputeCreateOrUpdate#Create#AKS)| +|[az machinelearningservices machine-learning-compute aml-compute create](#MachineLearningComputeCreateOrUpdate#Create#AmlCompute)|CreateOrUpdate#Create#AmlCompute|[Parameters](#ParametersMachineLearningComputeCreateOrUpdate#Create#AmlCompute)|[Example](#ExamplesMachineLearningComputeCreateOrUpdate#Create#AmlCompute)| +|[az machinelearningservices machine-learning-compute compute-instance create](#MachineLearningComputeCreateOrUpdate#Create#ComputeInstance)|CreateOrUpdate#Create#ComputeInstance|[Parameters](#ParametersMachineLearningComputeCreateOrUpdate#Create#ComputeInstance)|[Example](#ExamplesMachineLearningComputeCreateOrUpdate#Create#ComputeInstance)| +|[az machinelearningservices machine-learning-compute data-factory create](#MachineLearningComputeCreateOrUpdate#Create#DataFactory)|CreateOrUpdate#Create#DataFactory|[Parameters](#ParametersMachineLearningComputeCreateOrUpdate#Create#DataFactory)|[Example](#ExamplesMachineLearningComputeCreateOrUpdate#Create#DataFactory)| +|[az machinelearningservices machine-learning-compute data-lake-analytics create](#MachineLearningComputeCreateOrUpdate#Create#DataLakeAnalytics)|CreateOrUpdate#Create#DataLakeAnalytics|[Parameters](#ParametersMachineLearningComputeCreateOrUpdate#Create#DataLakeAnalytics)|[Example](#ExamplesMachineLearningComputeCreateOrUpdate#Create#DataLakeAnalytics)| +|[az machinelearningservices machine-learning-compute databricks create](#MachineLearningComputeCreateOrUpdate#Create#Databricks)|CreateOrUpdate#Create#Databricks|[Parameters](#ParametersMachineLearningComputeCreateOrUpdate#Create#Databricks)|[Example](#ExamplesMachineLearningComputeCreateOrUpdate#Create#Databricks)| +|[az machinelearningservices machine-learning-compute hd-insight create](#MachineLearningComputeCreateOrUpdate#Create#HDInsight)|CreateOrUpdate#Create#HDInsight|[Parameters](#ParametersMachineLearningComputeCreateOrUpdate#Create#HDInsight)|[Example](#ExamplesMachineLearningComputeCreateOrUpdate#Create#HDInsight)| +|[az machinelearningservices machine-learning-compute virtual-machine create](#MachineLearningComputeCreateOrUpdate#Create#VirtualMachine)|CreateOrUpdate#Create#VirtualMachine|[Parameters](#ParametersMachineLearningComputeCreateOrUpdate#Create#VirtualMachine)|[Example](#ExamplesMachineLearningComputeCreateOrUpdate#Create#VirtualMachine)| +|[az machinelearningservices machine-learning-compute update](#MachineLearningComputeUpdate)|Update|[Parameters](#ParametersMachineLearningComputeUpdate)|[Example](#ExamplesMachineLearningComputeUpdate)| +|[az machinelearningservices machine-learning-compute delete](#MachineLearningComputeDelete)|Delete|[Parameters](#ParametersMachineLearningComputeDelete)|[Example](#ExamplesMachineLearningComputeDelete)| +|[az machinelearningservices machine-learning-compute list-key](#MachineLearningComputeListKeys)|ListKeys|[Parameters](#ParametersMachineLearningComputeListKeys)|[Example](#ExamplesMachineLearningComputeListKeys)| +|[az machinelearningservices machine-learning-compute list-node](#MachineLearningComputeListNodes)|ListNodes|[Parameters](#ParametersMachineLearningComputeListNodes)|[Example](#ExamplesMachineLearningComputeListNodes)| +|[az machinelearningservices machine-learning-compute restart](#MachineLearningComputeRestart)|Restart|[Parameters](#ParametersMachineLearningComputeRestart)|[Example](#ExamplesMachineLearningComputeRestart)| +|[az machinelearningservices machine-learning-compute start](#MachineLearningComputeStart)|Start|[Parameters](#ParametersMachineLearningComputeStart)|[Example](#ExamplesMachineLearningComputeStart)| +|[az machinelearningservices machine-learning-compute stop](#MachineLearningComputeStop)|Stop|[Parameters](#ParametersMachineLearningComputeStop)|[Example](#ExamplesMachineLearningComputeStop)| + +### Commands in `az machinelearningservices notebook` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices notebook prepare](#NotebooksPrepare)|Prepare|[Parameters](#ParametersNotebooksPrepare)|[Example](#ExamplesNotebooksPrepare)| + +### Commands in `az machinelearningservices private-endpoint-connection` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices private-endpoint-connection show](#PrivateEndpointConnectionsGet)|Get|[Parameters](#ParametersPrivateEndpointConnectionsGet)|[Example](#ExamplesPrivateEndpointConnectionsGet)| +|[az machinelearningservices private-endpoint-connection delete](#PrivateEndpointConnectionsDelete)|Delete|[Parameters](#ParametersPrivateEndpointConnectionsDelete)|[Example](#ExamplesPrivateEndpointConnectionsDelete)| +|[az machinelearningservices private-endpoint-connection put](#PrivateEndpointConnectionsPut)|Put|[Parameters](#ParametersPrivateEndpointConnectionsPut)|[Example](#ExamplesPrivateEndpointConnectionsPut)| + +### Commands in `az machinelearningservices private-link-resource` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices private-link-resource list](#PrivateLinkResourcesListByWorkspace)|ListByWorkspace|[Parameters](#ParametersPrivateLinkResourcesListByWorkspace)|[Example](#ExamplesPrivateLinkResourcesListByWorkspace)| + +### Commands in `az machinelearningservices quota` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices quota list](#QuotasList)|List|[Parameters](#ParametersQuotasList)|[Example](#ExamplesQuotasList)| +|[az machinelearningservices quota update](#QuotasUpdate)|Update|[Parameters](#ParametersQuotasUpdate)|[Example](#ExamplesQuotasUpdate)| + +### Commands in `az machinelearningservices usage` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices usage list](#UsagesList)|List|[Parameters](#ParametersUsagesList)|[Example](#ExamplesUsagesList)| + +### Commands in `az machinelearningservices virtual-machine-size` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices virtual-machine-size list](#VirtualMachineSizesList)|List|[Parameters](#ParametersVirtualMachineSizesList)|[Example](#ExamplesVirtualMachineSizesList)| + +### Commands in `az machinelearningservices workspace` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices workspace list](#WorkspacesListByResourceGroup)|ListByResourceGroup|[Parameters](#ParametersWorkspacesListByResourceGroup)|[Example](#ExamplesWorkspacesListByResourceGroup)| +|[az machinelearningservices workspace list](#WorkspacesListBySubscription)|ListBySubscription|[Parameters](#ParametersWorkspacesListBySubscription)|[Example](#ExamplesWorkspacesListBySubscription)| +|[az machinelearningservices workspace show](#WorkspacesGet)|Get|[Parameters](#ParametersWorkspacesGet)|[Example](#ExamplesWorkspacesGet)| +|[az machinelearningservices workspace create](#WorkspacesCreateOrUpdate#Create)|CreateOrUpdate#Create|[Parameters](#ParametersWorkspacesCreateOrUpdate#Create)|[Example](#ExamplesWorkspacesCreateOrUpdate#Create)| +|[az machinelearningservices workspace update](#WorkspacesUpdate)|Update|[Parameters](#ParametersWorkspacesUpdate)|[Example](#ExamplesWorkspacesUpdate)| +|[az machinelearningservices workspace delete](#WorkspacesDelete)|Delete|[Parameters](#ParametersWorkspacesDelete)|[Example](#ExamplesWorkspacesDelete)| +|[az machinelearningservices workspace list-key](#WorkspacesListKeys)|ListKeys|[Parameters](#ParametersWorkspacesListKeys)|[Example](#ExamplesWorkspacesListKeys)| +|[az machinelearningservices workspace resync-key](#WorkspacesResyncKeys)|ResyncKeys|[Parameters](#ParametersWorkspacesResyncKeys)|[Example](#ExamplesWorkspacesResyncKeys)| + +### Commands in `az machinelearningservices workspace-connection` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices workspace-connection list](#WorkspaceConnectionsList)|List|[Parameters](#ParametersWorkspaceConnectionsList)|[Example](#ExamplesWorkspaceConnectionsList)| +|[az machinelearningservices workspace-connection show](#WorkspaceConnectionsGet)|Get|[Parameters](#ParametersWorkspaceConnectionsGet)|[Example](#ExamplesWorkspaceConnectionsGet)| +|[az machinelearningservices workspace-connection create](#WorkspaceConnectionsCreate)|Create|[Parameters](#ParametersWorkspaceConnectionsCreate)|[Example](#ExamplesWorkspaceConnectionsCreate)| +|[az machinelearningservices workspace-connection delete](#WorkspaceConnectionsDelete)|Delete|[Parameters](#ParametersWorkspaceConnectionsDelete)|[Example](#ExamplesWorkspaceConnectionsDelete)| + +### Commands in `az machinelearningservices workspace-feature` group +|CLI Command|Operation Swagger name|Parameters|Examples| +|---------|------------|--------|-----------| +|[az machinelearningservices workspace-feature list](#WorkspaceFeaturesList)|List|[Parameters](#ParametersWorkspaceFeaturesList)|[Example](#ExamplesWorkspaceFeaturesList)| + + +## COMMAND DETAILS + +### group `az machinelearningservices` +#### Command `az machinelearningservices list-sku` + +##### Example +``` +az machinelearningservices list-sku +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +### group `az machinelearningservices machine-learning-compute` +#### Command `az machinelearningservices machine-learning-compute list` + +##### Example +``` +az machinelearningservices machine-learning-compute list --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--skiptoken**|string|Continuation token for pagination.|skiptoken|$skiptoken| + +#### Command `az machinelearningservices machine-learning-compute show` + +##### Example +``` +az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute show --compute-name "compute123" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| + +#### Command `az machinelearningservices machine-learning-compute aks create` + +##### Example +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --ak-s-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\":{\\"maxNodeCount\ +\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedicated\\",\\"vmSize\\":\ +\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location "eastus" \ +--ak-s-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\"sshPublicAccess\\":\\"Disabled\ +\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location "eastus" \ +--ak-s-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute aks create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--ak-s-compute-location**|string|Location for the underlying compute|ak_s_compute_location|computeLocation| +|**--ak-s-description**|string|The description of the Machine Learning compute.|ak_s_description|description| +|**--ak-s-resource-id**|string|ARM resource id of the underlying compute|ak_s_resource_id|resourceId| +|**--ak-s-properties**|object|AKS properties|ak_s_properties|properties| + +#### Command `az machinelearningservices machine-learning-compute aml-compute create` + +##### Example +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --aml-compute-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\":{\\"maxNod\ +eCount\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedicated\\",\\"vmSi\ +ze\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --location "eastus" \ +--aml-compute-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\"sshPublicAccess\\":\\"Di\ +sabled\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --location "eastus" \ +--aml-compute-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name \ +"workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute aml-compute create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--compute-location**|string|Location for the underlying compute|aml_compute_compute_location|computeLocation| +|**--description**|string|The description of the Machine Learning compute.|aml_compute_description|description| +|**--resource-id**|string|ARM resource id of the underlying compute|aml_compute_resource_id|resourceId| +|**--aml-compute-properties**|object|AML Compute properties|aml_compute_properties|properties| + +#### Command `az machinelearningservices machine-learning-compute compute-instance create` + +##### Example +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --compute-instance-properties "{\\"remoteLoginPortPublicAccess\\":\\"NotSpecified\\",\\"scaleSettings\\":{\\"m\ +axNodeCount\\":1,\\"minNodeCount\\":0,\\"nodeIdleTimeBeforeScaleDown\\":\\"PT5M\\"},\\"vmPriority\\":\\"Dedicated\\",\\\ +"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" --location \ +"eastus" --compute-instance-properties "{\\"applicationSharingPolicy\\":\\"Personal\\",\\"sshSettings\\":{\\"sshPublicA\ +ccess\\":\\"Disabled\\"},\\"subnet\\":\\"test-subnet-resource-id\\",\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group \ +"testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" --location \ +"eastus" --compute-instance-properties "{\\"vmSize\\":\\"STANDARD_NC6\\"}" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute compute-instance create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--compute-location**|string|Location for the underlying compute|compute_instance_compute_location|computeLocation| +|**--description**|string|The description of the Machine Learning compute.|compute_instance_description|description| +|**--resource-id**|string|ARM resource id of the underlying compute|compute_instance_resource_id|resourceId| +|**--compute-instance-properties**|object|Compute Instance properties|compute_instance_properties|properties| + +#### Command `az machinelearningservices machine-learning-compute data-factory create` + +##### Example +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute data-factory create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--compute-location**|string|Location for the underlying compute|data_factory_compute_location|computeLocation| +|**--description**|string|The description of the Machine Learning compute.|data_factory_description|description| +|**--resource-id**|string|ARM resource id of the underlying compute|data_factory_resource_id|resourceId| + +#### Command `az machinelearningservices machine-learning-compute data-lake-analytics create` + +##### Example +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute data-lake-analytics create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--compute-location**|string|Location for the underlying compute|data_lake_analytics_compute_location|computeLocation| +|**--description**|string|The description of the Machine Learning compute.|data_lake_analytics_description|description| +|**--resource-id**|string|ARM resource id of the underlying compute|data_lake_analytics_resource_id|resourceId| +|**--data-lake-store-account-name**|string|DataLake Store Account Name|data_lake_analytics_data_lake_store_account_name|dataLakeStoreAccountName| + +#### Command `az machinelearningservices machine-learning-compute databricks create` + +##### Example +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute databricks create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--compute-location**|string|Location for the underlying compute|databricks_compute_location|computeLocation| +|**--description**|string|The description of the Machine Learning compute.|databricks_description|description| +|**--resource-id**|string|ARM resource id of the underlying compute|databricks_resource_id|resourceId| +|**--databricks-access-token**|string|Databricks access token|databricks_databricks_access_token|databricksAccessToken| + +#### Command `az machinelearningservices machine-learning-compute hd-insight create` + +##### Example +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute hd-insight create --compute-name "compute123" --location "eastus" \ +--resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--compute-location**|string|Location for the underlying compute|hd_insight_compute_location|computeLocation| +|**--description**|string|The description of the Machine Learning compute.|hd_insight_description|description| +|**--resource-id**|string|ARM resource id of the underlying compute|hd_insight_resource_id|resourceId| +|**--ssh-port**|integer|Port open for ssh connections on the master node of the cluster.|hd_insight_ssh_port|sshPort| +|**--address**|string|Public IP address of the master node of the cluster.|hd_insight_address|address| +|**--administrator-account**|object|Admin credentials for master node of the cluster|hd_insight_administrator_account|administratorAccount| + +#### Command `az machinelearningservices machine-learning-compute virtual-machine create` + +##### Example +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" --type \ +"SystemAssigned,UserAssigned" --user-assigned-identities "{\\"/subscriptions/00000000-0000-0000-0000-000000000000/resou\ +rceGroups/myResourceGroup/providers/Microsoft.ManagedIdentity/userAssignedIdentities/identity-name\\":{}}" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Example +``` +az machinelearningservices machine-learning-compute virtual-machine create --compute-name "compute123" --location \ +"eastus" --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--compute-location**|string|Location for the underlying compute|virtual_machine_compute_location|computeLocation| +|**--description**|string|The description of the Machine Learning compute.|virtual_machine_description|description| +|**--resource-id**|string|ARM resource id of the underlying compute|virtual_machine_resource_id|resourceId| +|**--virtual-machine-size**|string|Virtual Machine size|virtual_machine_virtual_machine_size|virtualMachineSize| +|**--ssh-port**|integer|Port open for ssh connections.|virtual_machine_ssh_port|sshPort| +|**--address**|string|Public IP address of the virtual machine.|virtual_machine_address|address| +|**--administrator-account**|object|Admin credentials for virtual machine|virtual_machine_administrator_account|administratorAccount| + +#### Command `az machinelearningservices machine-learning-compute update` + +##### Example +``` +az machinelearningservices machine-learning-compute update --compute-name "compute123" --scale-settings \ +max-node-count=4 min-node-count=4 node-idle-time-before-scale-down="PT5M" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--scale-settings**|object|Desired scale settings for the amlCompute.|scale_settings|scaleSettings| + +#### Command `az machinelearningservices machine-learning-compute delete` + +##### Example +``` +az machinelearningservices machine-learning-compute delete --compute-name "compute123" --resource-group "testrg123" \ +--underlying-resource-action "Delete" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| +|**--underlying-resource-action**|choice|Delete the underlying compute if 'Delete', or detach the underlying compute from workspace if 'Detach'.|underlying_resource_action|underlyingResourceAction| + +#### Command `az machinelearningservices machine-learning-compute list-key` + +##### Example +``` +az machinelearningservices machine-learning-compute list-key --compute-name "compute123" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| + +#### Command `az machinelearningservices machine-learning-compute list-node` + +##### Example +``` +az machinelearningservices machine-learning-compute list-node --compute-name "compute123" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| + +#### Command `az machinelearningservices machine-learning-compute restart` + +##### Example +``` +az machinelearningservices machine-learning-compute restart --compute-name "compute123" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| + +#### Command `az machinelearningservices machine-learning-compute start` + +##### Example +``` +az machinelearningservices machine-learning-compute start --compute-name "compute123" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| + +#### Command `az machinelearningservices machine-learning-compute stop` + +##### Example +``` +az machinelearningservices machine-learning-compute stop --compute-name "compute123" --resource-group "testrg123" \ +--workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--compute-name**|string|Name of the Azure Machine Learning compute.|compute_name|computeName| + +### group `az machinelearningservices notebook` +#### Command `az machinelearningservices notebook prepare` + +##### Example +``` +az machinelearningservices notebook prepare --resource-group "testrg123" --workspace-name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| + +### group `az machinelearningservices private-endpoint-connection` +#### Command `az machinelearningservices private-endpoint-connection show` + +##### Example +``` +az machinelearningservices private-endpoint-connection show --name "{privateEndpointConnectionName}" --resource-group \ +"rg-1234" --workspace-name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--private-endpoint-connection-name**|string|The name of the private endpoint connection associated with the workspace|private_endpoint_connection_name|privateEndpointConnectionName| + +#### Command `az machinelearningservices private-endpoint-connection delete` + +##### Example +``` +az machinelearningservices private-endpoint-connection delete --name "{privateEndpointConnectionName}" \ +--resource-group "rg-1234" --workspace-name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--private-endpoint-connection-name**|string|The name of the private endpoint connection associated with the workspace|private_endpoint_connection_name|privateEndpointConnectionName| + +#### Command `az machinelearningservices private-endpoint-connection put` + +##### Example +``` +az machinelearningservices private-endpoint-connection put --name "{privateEndpointConnectionName}" \ +--private-link-service-connection-state description="Auto-Approved" status="Approved" --resource-group "rg-1234" \ +--workspace-name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--private-endpoint-connection-name**|string|The name of the private endpoint connection associated with the workspace|private_endpoint_connection_name|privateEndpointConnectionName| +|**--private-link-service-connection-state**|object|A collection of information about the state of the connection between service consumer and provider.|private_link_service_connection_state|privateLinkServiceConnectionState| + +### group `az machinelearningservices private-link-resource` +#### Command `az machinelearningservices private-link-resource list` + +##### Example +``` +az machinelearningservices private-link-resource list --resource-group "rg-1234" --workspace-name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| + +### group `az machinelearningservices quota` +#### Command `az machinelearningservices quota list` + +##### Example +``` +az machinelearningservices quota list --location "eastus" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--location**|string|The location for which resource usage is queried.|location|location| + +#### Command `az machinelearningservices quota update` + +##### Example +``` +az machinelearningservices quota update --location "eastus" --value type="Microsoft.MachineLearningServices/workspaces/\ +dedicatedCores/quotas" id="/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/rg/providers/Microsoft.Ma\ +chineLearningServices/workspaces/demo_workspace1/quotas/StandardDSv2Family" limit=100 unit="Count" --value \ +type="Microsoft.MachineLearningServices/workspaces/dedicatedCores/quotas" id="/subscriptions/00000000-0000-0000-0000-00\ +0000000000/resourceGroups/rg/providers/Microsoft.MachineLearningServices/workspaces/demo_workspace2/quotas/StandardDSv2\ +Family" limit=200 unit="Count" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--location**|string|The location for update quota is queried.|location|location| +|**--value**|array|The list for update quota.|value|value| + +### group `az machinelearningservices usage` +#### Command `az machinelearningservices usage list` + +##### Example +``` +az machinelearningservices usage list --location "eastus" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--location**|string|The location for which resource usage is queried.|location|location| + +### group `az machinelearningservices virtual-machine-size` +#### Command `az machinelearningservices virtual-machine-size list` + +##### Example +``` +az machinelearningservices virtual-machine-size list --location "eastus" --recommended false +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--location**|string|The location upon which virtual-machine-sizes is queried.|location|location| +|**--compute-type**|string|Type of compute to filter by.|compute_type|compute-type| +|**--recommended**|boolean|Specifies whether to return recommended vm sizes or all vm sizes|recommended|recommended| + +### group `az machinelearningservices workspace` +#### Command `az machinelearningservices workspace list` + +##### Example +``` +az machinelearningservices workspace list --resource-group "workspace-1234" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--skiptoken**|string|Continuation token for pagination.|skiptoken|$skiptoken| + +#### Command `az machinelearningservices workspace list` + +##### Example +``` +az machinelearningservices workspace list +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +#### Command `az machinelearningservices workspace show` + +##### Example +``` +az machinelearningservices workspace show --resource-group "workspace-1234" --name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| + +#### Command `az machinelearningservices workspace create` + +##### Example +``` +az machinelearningservices workspace create --type "SystemAssigned" --location "eastus2euap" --description "test \ +description" --application-insights "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/\ +providers/microsoft.insights/components/testinsights" --container-registry "/subscriptions/00000000-1111-2222-3333-4444\ +44444444/resourceGroups/workspace-1234/providers/Microsoft.ContainerRegistry/registries/testRegistry" \ +--key-vault-properties identity-client-id="" key-identifier="https://testkv.vault.azure.net/keys/testkey/aabbccddee1122\ +33445566778899aabb" key-vault-arm-id="/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234\ +/providers/Microsoft.KeyVault/vaults/testkv" --status "Enabled" --friendly-name "HelloName" --hbi-workspace false \ +--key-vault "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/Microsoft.KeyV\ +ault/vaults/testkv" --shared-private-link-resources name="testdbresource" private-link-resource-id="/subscriptions/0000\ +0000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/Microsoft.DocumentDB/databaseAccounts/testdbre\ +source/privateLinkResources/Sql" group-id="Sql" request-message="Please approve" status="Approved" --storage-account \ +"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/accountcrud-1234/providers/Microsoft.Storage/storag\ +eAccounts/testStorageAccount" --sku name="Basic" tier="Basic" --resource-group "workspace-1234" --name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--location**|string|Specifies the location of the resource.|location|location| +|**--tags**|dictionary|Contains resource tags defined as key/value pairs.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--type**|sealed-choice|The identity type.|type|type| +|**--user-assigned-identities**|dictionary|The list of user identities associated with resource. The user identity dictionary key references will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}'.|user_assigned_identities|userAssignedIdentities| +|**--description**|string|The description of this workspace.|description|description| +|**--friendly-name**|string|The friendly name for this workspace. This name in mutable|friendly_name|friendlyName| +|**--key-vault**|string|ARM id of the key vault associated with this workspace. This cannot be changed once the workspace has been created|key_vault|keyVault| +|**--application-insights**|string|ARM id of the application insights associated with this workspace. This cannot be changed once the workspace has been created|application_insights|applicationInsights| +|**--container-registry**|string|ARM id of the container registry associated with this workspace. This cannot be changed once the workspace has been created|container_registry|containerRegistry| +|**--storage-account**|string|ARM id of the storage account associated with this workspace. This cannot be changed once the workspace has been created|storage_account|storageAccount| +|**--discovery-url**|string|Url for the discovery service to identify regional endpoints for machine learning experimentation services|discovery_url|discoveryUrl| +|**--hbi-workspace**|boolean|The flag to signal HBI data in the workspace and reduce diagnostic data collected by the service|hbi_workspace|hbiWorkspace| +|**--image-build-compute**|string|The compute name for image build|image_build_compute|imageBuildCompute| +|**--allow-public-access-when-behind-vnet**|boolean|The flag to indicate whether to allow public access when behind VNet.|allow_public_access_when_behind_vnet|allowPublicAccessWhenBehindVnet| +|**--shared-private-link-resources**|array|The list of shared private link resources in this workspace.|shared_private_link_resources|sharedPrivateLinkResources| +|**--status**|choice|Indicates whether or not the encryption is enabled for the workspace.|status|status| +|**--key-vault-properties**|object|Customer Key vault properties.|key_vault_properties|keyVaultProperties| + +#### Command `az machinelearningservices workspace update` + +##### Example +``` +az machinelearningservices workspace update --description "new description" --friendly-name "New friendly name" --sku \ +name="Enterprise" tier="Enterprise" --resource-group "workspace-1234" --name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--tags**|dictionary|The resource tags for the machine learning workspace.|tags|tags| +|**--sku**|object|The sku of the workspace.|sku|sku| +|**--description**|string|The description of this workspace.|description|description| +|**--friendly-name**|string|The friendly name for this workspace.|friendly_name|friendlyName| + +#### Command `az machinelearningservices workspace delete` + +##### Example +``` +az machinelearningservices workspace delete --resource-group "workspace-1234" --name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| + +#### Command `az machinelearningservices workspace list-key` + +##### Example +``` +az machinelearningservices workspace list-key --resource-group "testrg123" --name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| + +#### Command `az machinelearningservices workspace resync-key` + +##### Example +``` +az machinelearningservices workspace resync-key --resource-group "testrg123" --name "workspaces123" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| + +### group `az machinelearningservices workspace-connection` +#### Command `az machinelearningservices workspace-connection list` + +##### Example +``` +az machinelearningservices workspace-connection list --category "ACR" --resource-group "resourceGroup-1" --target \ +"www.facebook.com" --workspace-name "workspace-1" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--target**|string|Target of the workspace connection.|target|target| +|**--category**|string|Category of the workspace connection.|category|category| + +#### Command `az machinelearningservices workspace-connection show` + +##### Example +``` +az machinelearningservices workspace-connection show --connection-name "connection-1" --resource-group \ +"resourceGroup-1" --workspace-name "workspace-1" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--connection-name**|string|Friendly name of the workspace connection|connection_name|connectionName| + +#### Command `az machinelearningservices workspace-connection create` + +##### Example +``` +az machinelearningservices workspace-connection create --connection-name "connection-1" --name "connection-1" \ +--auth-type "PAT" --category "ACR" --target "www.facebook.com" --value "secrets" --resource-group "resourceGroup-1" \ +--workspace-name "workspace-1" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--connection-name**|string|Friendly name of the workspace connection|connection_name|connectionName| +|**--name**|string|Friendly name of the workspace connection|name|name| +|**--category**|string|Category of the workspace connection.|category|category| +|**--target**|string|Target of the workspace connection.|target|target| +|**--auth-type**|string|Authorization type of the workspace connection.|auth_type|authType| +|**--value**|string|Value details of the workspace connection.|value|value| + +#### Command `az machinelearningservices workspace-connection delete` + +##### Example +``` +az machinelearningservices workspace-connection delete --connection-name "connection-1" --resource-group \ +"resourceGroup-1" --workspace-name "workspace-1" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| +|**--connection-name**|string|Friendly name of the workspace connection|connection_name|connectionName| + +### group `az machinelearningservices workspace-feature` +#### Command `az machinelearningservices workspace-feature list` + +##### Example +``` +az machinelearningservices workspace-feature list --resource-group "myResourceGroup" --workspace-name "testworkspace" +``` +##### Parameters +|Option|Type|Description|Path (SDK)|Swagger name| +|------|----|-----------|----------|------------| +|**--resource-group-name**|string|Name of the resource group in which workspace is located.|resource_group_name|resourceGroupName| +|**--workspace-name**|string|Name of Azure Machine Learning workspace.|workspace_name|workspaceName| diff --git a/src/machinelearningservices/setup.cfg b/src/machinelearningservices/setup.cfg new file mode 100644 index 00000000000..2fdd96e5d39 --- /dev/null +++ b/src/machinelearningservices/setup.cfg @@ -0,0 +1 @@ +#setup.cfg \ No newline at end of file diff --git a/src/machinelearningservices/setup.py b/src/machinelearningservices/setup.py new file mode 100644 index 00000000000..e4ec7166802 --- /dev/null +++ b/src/machinelearningservices/setup.py @@ -0,0 +1,58 @@ +#!/usr/bin/env python + +# -------------------------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# -------------------------------------------------------------------------------------------- + + +from codecs import open +from setuptools import setup, find_packages + +# HISTORY.rst entry. +VERSION = '0.1.0' +try: + from azext_machinelearningservices.manual.version import VERSION +except ImportError: + pass + +# The full list of classifiers is available at +# https://pypi.python.org/pypi?%3Aaction=list_classifiers +CLASSIFIERS = [ + 'Development Status :: 4 - Beta', + 'Intended Audience :: Developers', + 'Intended Audience :: System Administrators', + 'Programming Language :: Python', + 'Programming Language :: Python :: 3', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: 3.8', + 'License :: OSI Approved :: MIT License', +] + +DEPENDENCIES = [] + +try: + from azext_machinelearningservices.manual.dependency import DEPENDENCIES +except ImportError: + pass + +with open('README.md', 'r', encoding='utf-8') as f: + README = f.read() +with open('HISTORY.rst', 'r', encoding='utf-8') as f: + HISTORY = f.read() + +setup( + name='machinelearningservices', + version=VERSION, + description='Microsoft Azure Command-Line Tools AzureMachineLearningWorkspaces Extension', + author='Microsoft Corporation', + author_email='azpycli@microsoft.com', + url='https://github.com/Azure/azure-cli-extensions/tree/master/src/machinelearningservices', + long_description=README + '\n\n' + HISTORY, + license='MIT', + classifiers=CLASSIFIERS, + packages=find_packages(), + install_requires=DEPENDENCIES, + package_data={'azext_machinelearningservices': ['azext_metadata.json']}, +)