googleapis · dizcology · Jun 2, 2022 · May 11, 2022 · May 11, 2022 · May 12, 2022
diff --git a/docs/definition_v1/types.rst b/docs/definition_v1/types.rst
@@ -0,0 +1,7 @@
+Types for Google Cloud Aiplatform V1 Schema Trainingjob Definition v1 API
+=========================================================================
+
+.. automodule:: google.cloud.aiplatform.v1.schema.trainingjob.definition_v1.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/definition_v1beta1/types.rst b/docs/definition_v1beta1/types.rst
@@ -0,0 +1,7 @@
+Types for Google Cloud Aiplatform V1beta1 Schema Trainingjob Definition v1beta1 API
+===================================================================================
+
+.. automodule:: google.cloud.aiplatform.v1beta1.schema.trainingjob.definition_v1beta1.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/instance_v1/types.rst b/docs/instance_v1/types.rst
@@ -0,0 +1,7 @@
+Types for Google Cloud Aiplatform V1 Schema Predict Instance v1 API
+===================================================================
+
+.. automodule:: google.cloud.aiplatform.v1.schema.predict.instance_v1.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/instance_v1beta1/types.rst b/docs/instance_v1beta1/types.rst
@@ -0,0 +1,7 @@
+Types for Google Cloud Aiplatform V1beta1 Schema Predict Instance v1beta1 API
+=============================================================================
+
+.. automodule:: google.cloud.aiplatform.v1beta1.schema.predict.instance_v1beta1.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/params_v1/types.rst b/docs/params_v1/types.rst
@@ -0,0 +1,7 @@
+Types for Google Cloud Aiplatform V1 Schema Predict Params v1 API
+=================================================================
+
+.. automodule:: google.cloud.aiplatform.v1.schema.predict.params_v1.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/params_v1beta1/types.rst b/docs/params_v1beta1/types.rst
@@ -0,0 +1,7 @@
+Types for Google Cloud Aiplatform V1beta1 Schema Predict Params v1beta1 API
+===========================================================================
+
+.. automodule:: google.cloud.aiplatform.v1beta1.schema.predict.params_v1beta1.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/prediction_v1/types.rst b/docs/prediction_v1/types.rst
@@ -0,0 +1,7 @@
+Types for Google Cloud Aiplatform V1 Schema Predict Prediction v1 API
+=====================================================================
+
+.. automodule:: google.cloud.aiplatform.v1.schema.predict.prediction_v1.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/prediction_v1beta1/types.rst b/docs/prediction_v1beta1/types.rst
@@ -0,0 +1,7 @@
+Types for Google Cloud Aiplatform V1beta1 Schema Predict Prediction v1beta1 API
+===============================================================================
+
+.. automodule:: google.cloud.aiplatform.v1beta1.schema.predict.prediction_v1beta1.types
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/google/cloud/aiplatform_v1/__init__.py b/google/cloud/aiplatform_v1/__init__.py
@@ -362,10 +362,12 @@
 from .types.model_service import UploadModelResponse
 from .types.operation import DeleteOperationMetadata
 from .types.operation import GenericOperationMetadata
+from .types.pipeline_failure_policy import PipelineFailurePolicy
 from .types.pipeline_job import PipelineJob
 from .types.pipeline_job import PipelineJobDetail
 from .types.pipeline_job import PipelineTaskDetail
 from .types.pipeline_job import PipelineTaskExecutorDetail
+from .types.pipeline_job import PipelineTemplateMetadata
 from .types.pipeline_service import CancelPipelineJobRequest
 from .types.pipeline_service import CancelTrainingPipelineRequest
 from .types.pipeline_service import CreatePipelineJobRequest
@@ -829,12 +831,14 @@
     "NearestNeighborSearchOperationMetadata",
     "NfsMount",
     "PauseModelDeploymentMonitoringJobRequest",
+    "PipelineFailurePolicy",
     "PipelineJob",
     "PipelineJobDetail",
     "PipelineServiceClient",
     "PipelineState",
     "PipelineTaskDetail",
     "PipelineTaskExecutorDetail",
+    "PipelineTemplateMetadata",
     "Port",
     "PredefinedSplit",
     "PredictRequest",

diff --git a/google/cloud/aiplatform_v1/services/migration_service/client.py b/google/cloud/aiplatform_v1/services/migration_service/client.py
@@ -192,40 +192,40 @@ 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}/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
     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

diff --git a/google/cloud/aiplatform_v1/types/__init__.py b/google/cloud/aiplatform_v1/types/__init__.py
@@ -423,6 +423,7 @@
     PipelineJobDetail,
     PipelineTaskDetail,
     PipelineTaskExecutorDetail,
+    PipelineTemplateMetadata,
 )
 from .pipeline_service import (
     CancelPipelineJobRequest,
@@ -883,10 +884,12 @@
     "UploadModelResponse",
     "DeleteOperationMetadata",
     "GenericOperationMetadata",
+    "PipelineFailurePolicy",
     "PipelineJob",
     "PipelineJobDetail",
     "PipelineTaskDetail",
     "PipelineTaskExecutorDetail",
+    "PipelineTemplateMetadata",
     "CancelPipelineJobRequest",
     "CancelTrainingPipelineRequest",
     "CreatePipelineJobRequest",

diff --git a/google/cloud/aiplatform_v1/types/endpoint.py b/google/cloud/aiplatform_v1/types/endpoint.py
@@ -221,10 +221,10 @@ class DeployedModel(proto.Message):
             This value should be 1-10 characters, and valid characters
             are /[0-9]/.
         model (str):
-            Required. The name of the Model that this is
-            the deployment of. Note that the Model may be in
-            a different location than the DeployedModel's
-            Endpoint.
+            Required. The resource name of the Model that
+            this is the deployment of. Note that the Model
+            may be in a different location than the
+            DeployedModel's Endpoint.
         display_name (str):
             The display name of the DeployedModel. If not provided upon
             creation, the Model's display_name is used.

diff --git a/google/cloud/aiplatform_v1/types/explanation_metadata.py b/google/cloud/aiplatform_v1/types/explanation_metadata.py
@@ -69,6 +69,9 @@ class ExplanationMetadata(proto.Message):
             including the URI scheme, than the one given on input. The
             output URI will point to a location where the user only has
             a read access.
+        latent_space_source (str):
+            Name of the source to generate embeddings for
+            example based explanations.
     """
 
     class InputMetadata(proto.Message):
@@ -457,6 +460,10 @@ class OutputMetadata(proto.Message):
         proto.STRING,
         number=3,
     )
+    latent_space_source = proto.Field(
+        proto.STRING,
+        number=5,
+    )
 
 
 __all__ = tuple(sorted(__protobuf__.manifest))
diff --git a/google/cloud/aiplatform_v1/types/featurestore.py b/google/cloud/aiplatform_v1/types/featurestore.py
@@ -92,12 +92,46 @@ class OnlineServingConfig(proto.Message):
                 set to 0, the featurestore will not have an
                 online store and cannot be used for online
                 serving.
+            scaling (google.cloud.aiplatform_v1.types.Featurestore.OnlineServingConfig.Scaling):
+                Online serving scaling configuration. Only one of
+                ``fixed_node_count`` and ``scaling`` can be set. Setting one
+                will reset the other.
         """
 
+        class Scaling(proto.Message):
+            r"""Online serving scaling configuration. If min_node_count and
+            max_node_count are set to the same value, the cluster will be
+            configured with the fixed number of node (no auto-scaling).
+
+            Attributes:
+                min_node_count (int):
+                    Required. The minimum number of nodes to
+                    scale down to. Must be greater than or equal to
+                    1.
+                max_node_count (int):
+                    The maximum number of nodes to scale up to. Must be greater
+                    than min_node_count, and less than or equal to 10 times of
+                    'min_node_count'.
+            """
+
+            min_node_count = proto.Field(
+                proto.INT32,
+                number=1,
+            )
+            max_node_count = proto.Field(
+                proto.INT32,
+                number=2,
+            )
+
         fixed_node_count = proto.Field(
             proto.INT32,
             number=2,
         )
+        scaling = proto.Field(
+            proto.MESSAGE,
+            number=4,
+            message="Featurestore.OnlineServingConfig.Scaling",
+        )
 
     name = proto.Field(
         proto.STRING,

diff --git a/google/cloud/aiplatform_v1/types/featurestore_online_service.py b/google/cloud/aiplatform_v1/types/featurestore_online_service.py
@@ -236,7 +236,7 @@ class StreamingReadFeatureValuesRequest(proto.Message):
 
 class FeatureValue(proto.Message):
     r"""Value for a feature.
-    NEXT ID: 15
+    (-- NEXT ID: 15 --)
 
     This message has `oneof`_ fields (mutually exclusive fields).
     For each oneof, at most one member field can be set at the same time.

diff --git a/google/cloud/aiplatform_v1/types/manual_batch_tuning_parameters.py b/google/cloud/aiplatform_v1/types/manual_batch_tuning_parameters.py
@@ -38,7 +38,7 @@ class ManualBatchTuningParameters(proto.Message):
             value will result in a whole batch not fitting
             in a machine's memory, and the whole operation
             will fail.
-            The default value is 4.
+            The default value is 64.
     """
 
     batch_size = proto.Field(

diff --git a/google/cloud/aiplatform_v1/types/model_evaluation.py b/google/cloud/aiplatform_v1/types/model_evaluation.py
@@ -37,6 +37,8 @@ class ModelEvaluation(proto.Message):
         name (str):
             Output only. The resource name of the
             ModelEvaluation.
+        display_name (str):
+            The display name of the ModelEvaluation.
         metrics_schema_uri (str):
             Points to a YAML file stored on Google Cloud Storage
             describing the
@@ -92,6 +94,11 @@ class ModelEvaluation(proto.Message):
             [ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec]
             that are used for explaining the predicted values on the
             evaluated data.
+        metadata (google.protobuf.struct_pb2.Value):
+            The metadata of the ModelEvaluation. For the ModelEvaluation
+            uploaded from Managed Pipeline, metadata contains a
+            structured value with keys of "pipeline_job_id",
+            "evaluation_dataset_type", "evaluation_dataset_path".
     """
 
     class ModelEvaluationExplanationSpec(proto.Message):
@@ -123,6 +130,10 @@ class ModelEvaluationExplanationSpec(proto.Message):
         proto.STRING,
         number=1,
     )
+    display_name = proto.Field(
+        proto.STRING,
+        number=10,
+    )
     metrics_schema_uri = proto.Field(
         proto.STRING,
         number=2,
@@ -159,6 +170,11 @@ class ModelEvaluationExplanationSpec(proto.Message):
         number=9,
         message=ModelEvaluationExplanationSpec,
     )
+    metadata = proto.Field(
+        proto.MESSAGE,
+        number=11,
+        message=struct_pb2.Value,
+    )
 
 
 __all__ = tuple(sorted(__protobuf__.manifest))
diff --git a/google/cloud/aiplatform_v1/types/model_monitoring.py b/google/cloud/aiplatform_v1/types/model_monitoring.py
@@ -84,6 +84,8 @@ class TrainingDataset(proto.Message):
 
                 "csv"
                 The source file is a CSV file.
+                "jsonl"
+                The source file is a JSONL file.
             target_field (str):
                 The target field name the model is to
                 predict. This field will be excluded when doing

diff --git a/google/cloud/aiplatform_v1/types/pipeline_failure_policy.py b/google/cloud/aiplatform_v1/types/pipeline_failure_policy.py
@@ -0,0 +1,41 @@
+# -*- coding: utf-8 -*-
+# Copyright 2022 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import proto  # type: ignore
+
+
+__protobuf__ = proto.module(
+    package="google.cloud.aiplatform.v1",
+    manifest={
+        "PipelineFailurePolicy",
+    },
+)
+
+
+class PipelineFailurePolicy(proto.Enum):
+    r"""Represents the failure policy of a pipeline. Currently, the default
+    of a pipeline is that the pipeline will continue to run until no
+    more tasks can be executed, also known as
+    PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to
+    PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new
+    tasks when a task has failed. Any scheduled tasks will continue to
+    completion.
+    """
+    PIPELINE_FAILURE_POLICY_UNSPECIFIED = 0
+    PIPELINE_FAILURE_POLICY_FAIL_SLOW = 1
+    PIPELINE_FAILURE_POLICY_FAIL_FAST = 2
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))