🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

google/cloud/aiplatform_v1beta1/__init__.py

@@ -534,6 +534,7 @@
 from .types.study import Study
 from .types.study import StudySpec
 from .types.study import Trial
+from .types.study import TrialContext
 from .types.tensorboard import Tensorboard
 from .types.tensorboard_data import Scalar
 from .types.tensorboard_data import TensorboardBlob
@@ -1164,6 +1165,7 @@
     "TrainingConfig",
     "TrainingPipeline",
     "Trial",
+    "TrialContext",
     "UndeployIndexOperationMetadata",
     "UndeployIndexRequest",
     "UndeployIndexResponse",

google/cloud/aiplatform_v1beta1/services/index_endpoint_service/async_client.py

@@ -45,6 +45,7 @@
 from google.api_core import operation as gac_operation  # type: ignore
 from google.api_core import operation_async  # type: ignore
 from google.cloud.aiplatform_v1beta1.services.index_endpoint_service import pagers
+from google.cloud.aiplatform_v1beta1.types import encryption_spec
 from google.cloud.aiplatform_v1beta1.types import index_endpoint
 from google.cloud.aiplatform_v1beta1.types import index_endpoint as gca_index_endpoint
 from google.cloud.aiplatform_v1beta1.types import index_endpoint_service

google/cloud/aiplatform_v1beta1/services/index_endpoint_service/client.py

@@ -49,6 +49,7 @@
 from google.api_core import operation as gac_operation  # type: ignore
 from google.api_core import operation_async  # type: ignore
 from google.cloud.aiplatform_v1beta1.services.index_endpoint_service import pagers
+from google.cloud.aiplatform_v1beta1.types import encryption_spec
 from google.cloud.aiplatform_v1beta1.types import index_endpoint
 from google.cloud.aiplatform_v1beta1.types import index_endpoint as gca_index_endpoint
 from google.cloud.aiplatform_v1beta1.types import index_endpoint_service

google/cloud/aiplatform_v1beta1/services/index_service/async_client.py

@@ -46,6 +46,7 @@
 from google.api_core import operation_async  # type: ignore
 from google.cloud.aiplatform_v1beta1.services.index_service import pagers
 from google.cloud.aiplatform_v1beta1.types import deployed_index_ref
+from google.cloud.aiplatform_v1beta1.types import encryption_spec
 from google.cloud.aiplatform_v1beta1.types import index
 from google.cloud.aiplatform_v1beta1.types import index as gca_index
 from google.cloud.aiplatform_v1beta1.types import index_service

google/cloud/aiplatform_v1beta1/services/index_service/client.py

@@ -50,6 +50,7 @@
 from google.api_core import operation_async  # type: ignore
 from google.cloud.aiplatform_v1beta1.services.index_service import pagers
 from google.cloud.aiplatform_v1beta1.types import deployed_index_ref
+from google.cloud.aiplatform_v1beta1.types import encryption_spec
 from google.cloud.aiplatform_v1beta1.types import index
 from google.cloud.aiplatform_v1beta1.types import index as gca_index
 from google.cloud.aiplatform_v1beta1.types import index_service

google/cloud/aiplatform_v1beta1/services/migration_service/client.py

@@ -208,40 +208,40 @@ def parse_annotated_dataset_path(path: str) -> Dict[str, str]:
     @staticmethod
     def dataset_path(
         project: str,
-        location: str,
         dataset: str,
     ) -> str:
         """Returns a fully-qualified dataset string."""
-        return "projects/{project}/locations/{location}/datasets/{dataset}".format(
+        return "projects/{project}/datasets/{dataset}".format(
             project=project,
-            location=location,
             dataset=dataset,
         )
 
     @staticmethod
     def parse_dataset_path(path: str) -> Dict[str, str]:
         """Parses a dataset path into its component segments."""
-        m = re.match(
-            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/datasets/(?P<dataset>.+?)$",
-            path,
-        )
+        m = re.match(r"^projects/(?P<project>.+?)/datasets/(?P<dataset>.+?)$", path)
         return m.groupdict() if m else {}
 
     @staticmethod
     def dataset_path(
         project: str,
+        location: str,
         dataset: str,
     ) -> str:
         """Returns a fully-qualified dataset string."""
-        return "projects/{project}/datasets/{dataset}".format(
+        return "projects/{project}/locations/{location}/datasets/{dataset}".format(
             project=project,
+            location=location,
             dataset=dataset,
         )
 
     @staticmethod
     def parse_dataset_path(path: str) -> Dict[str, str]:
         """Parses a dataset path into its component segments."""
-        m = re.match(r"^projects/(?P<project>.+?)/datasets/(?P<dataset>.+?)$", path)
+        m = re.match(
+            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/datasets/(?P<dataset>.+?)$",
+            path,
+        )
         return m.groupdict() if m else {}
 
     @staticmethod

google/cloud/aiplatform_v1beta1/types/__init__.py

@@ -603,6 +603,7 @@
     Study,
     StudySpec,
     Trial,
+    TrialContext,
 )
 from .tensorboard import (
     Tensorboard,
@@ -1178,6 +1179,7 @@
     "Study",
     "StudySpec",
     "Trial",
+    "TrialContext",
     "Tensorboard",
     "Scalar",
     "TensorboardBlob",

google/cloud/aiplatform_v1beta1/types/index.py

@@ -20,6 +20,7 @@
 import proto  # type: ignore
 
 from google.cloud.aiplatform_v1beta1.types import deployed_index_ref
+from google.cloud.aiplatform_v1beta1.types import encryption_spec as gca_encryption_spec
 from google.protobuf import struct_pb2  # type: ignore
 from google.protobuf import timestamp_pb2  # type: ignore
 
@@ -101,6 +102,11 @@ class Index(proto.Message):
         index_update_method (google.cloud.aiplatform_v1beta1.types.Index.IndexUpdateMethod):
             Immutable. The update method to use with this Index. If not
             set, BATCH_UPDATE will be used by default.
+        encryption_spec (google.cloud.aiplatform_v1beta1.types.EncryptionSpec):
+            Immutable. Customer-managed encryption key
+            spec for an Index. If set, this Index and all
+            sub-resources of this Index will be secured by
+            this key.
     """
 
     class IndexUpdateMethod(proto.Enum):
@@ -181,6 +187,11 @@ class IndexUpdateMethod(proto.Enum):
         number=16,
         enum=IndexUpdateMethod,
     )
+    encryption_spec: gca_encryption_spec.EncryptionSpec = proto.Field(
+        proto.MESSAGE,
+        number=17,
+        message=gca_encryption_spec.EncryptionSpec,
+    )
 
 
 class IndexDatapoint(proto.Message):

google/cloud/aiplatform_v1beta1/types/index_endpoint.py

@@ -19,6 +19,7 @@
 
 import proto  # type: ignore
 
+from google.cloud.aiplatform_v1beta1.types import encryption_spec as gca_encryption_spec
 from google.cloud.aiplatform_v1beta1.types import machine_resources
 from google.cloud.aiplatform_v1beta1.types import service_networking
 from google.protobuf import timestamp_pb2  # type: ignore
@@ -119,6 +120,11 @@ class IndexEndpoint(proto.Message):
             [public_endpoint_enabled][google.cloud.aiplatform.v1beta1.IndexEndpoint.public_endpoint_enabled]
             is true, this field will be populated with the domain name
             to use for this index endpoint.
+        encryption_spec (google.cloud.aiplatform_v1beta1.types.EncryptionSpec):
+            Immutable. Customer-managed encryption key
+            spec for an IndexEndpoint. If set, this
+            IndexEndpoint and all sub-resources of this
+            IndexEndpoint will be secured by this key.
     """
 
     name: str = proto.Field(
@@ -180,6 +186,11 @@ class IndexEndpoint(proto.Message):
         proto.STRING,
         number=14,
     )
+    encryption_spec: gca_encryption_spec.EncryptionSpec = proto.Field(
+        proto.MESSAGE,
+        number=15,
+        message=gca_encryption_spec.EncryptionSpec,
+    )
 
 
 class DeployedIndex(proto.Message):

google/cloud/aiplatform_v1beta1/types/study.py

@@ -29,6 +29,7 @@
     manifest={
         "Study",
         "Trial",
+        "TrialContext",
         "StudySpec",
         "Measurement",
     },
@@ -288,6 +289,38 @@ class Parameter(proto.Message):
     )
 
 
+class TrialContext(proto.Message):
+    r"""Next ID: 3
+
+    Attributes:
+        description (str):
+            A human-readable field which can store a
+            description of this context. This will become
+            part of the resulting Trial's description field.
+        parameters (MutableSequence[google.cloud.aiplatform_v1beta1.types.Trial.Parameter]):
+            If/when a Trial is generated or selected from this Context,
+            its Parameters will match any parameters specified here.
+            (I.e. if this context specifies parameter name:'a'
+            int_value:3, then a resulting Trial will have int_value:3
+            for its parameter named 'a'.) Note that we first attempt to
+            match existing REQUESTED Trials with contexts, and if there
+            are no matches, we generate suggestions in the subspace
+            defined by the parameters specified here. NOTE: a Context
+            without any Parameters matches the entire feasible search
+            space.
+    """
+
+    description: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    parameters: MutableSequence["Trial.Parameter"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=2,
+        message="Trial.Parameter",
+    )
+
+
 class StudySpec(proto.Message):
     r"""Represents specification of a Study.
 

google/cloud/aiplatform_v1beta1/types/vizier_service.py

@@ -215,6 +215,48 @@ class SuggestTrialsRequest(proto.Message):
             ``client_id``, the service will return the identical
             suggested Trial if the Trial is pending, and provide a new
             Trial if the last suggested Trial was completed.
+        contexts (MutableSequence[google.cloud.aiplatform_v1beta1.types.TrialContext]):
+            Optional. This allows you to specify the "context" for a
+            Trial; a context is a slice (a subspace) of the search
+            space.
+
+            Typical uses for contexts:
+
+            1) You are using Vizier to tune a server for best
+               performance, but there's a strong weekly cycle. The
+               context specifies the day-of-week. This allows Tuesday to
+               generalize from Wednesday without assuming that
+               everything is identical.
+            2) Imagine you're optimizing some medical treatment for
+               people. As they walk in the door, you know certain facts
+               about them (e.g. sex, weight, height, blood-pressure).
+               Put that information in the context, and Vizier will
+               adapt its suggestions to the patient.
+            3) You want to do a fair A/B test efficiently. Specify the
+               "A" and "B" conditions as contexts, and Vizier will
+               generalize between "A" and "B" conditions. If they are
+               similar, this will allow Vizier to converge to the
+               optimum faster than if "A" and "B" were separate Studies.
+               NOTE: You can also enter contexts as REQUESTED Trials,
+               e.g. via the CreateTrial() RPC; that's the asynchronous
+               option where you don't need a close association between
+               contexts and suggestions.
+
+            NOTE: All the Parameters you set in a context MUST be
+            defined in the Study. NOTE: You must supply 0 or
+            $suggestion_count contexts. If you don't supply any
+            contexts, Vizier will make suggestions from the full search
+            space specified in the StudySpec; if you supply a full set
+            of context, each suggestion will match the corresponding
+            context. NOTE: A Context with no features set matches
+            anything, and allows suggestions from the full search space.
+            NOTE: Contexts MUST lie within the search space specified in
+            the StudySpec. It's an error if they don't. NOTE: Contexts
+            preferentially match ACTIVE then REQUESTED trials before new
+            suggestions are generated. NOTE: Generation of suggestions
+            involves a match between a Context and (optionally) a
+            REQUESTED trial; if that match is not fully specified, a
+            suggestion will be geneated in the merged subspace.
     """
 
     parent: str = proto.Field(
@@ -229,6 +271,11 @@ class SuggestTrialsRequest(proto.Message):
         proto.STRING,
         number=3,
     )
+    contexts: MutableSequence[gca_study.TrialContext] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=4,
+        message=gca_study.TrialContext,
+    )
 
 
 class SuggestTrialsResponse(proto.Message):