feat: Removes AcceleratorType.TPU_V2 and TPU_V3 constants

google/cloud/aiplatform/v1/schema/predict/instance_v1/types/image_classification.py

@@ -26,8 +26,8 @@ class ImageClassificationPredictionInstance(proto.Message):
     r"""Prediction input format for Image Classification.
     Attributes:
         content (str):
-            The image bytes or GCS URI to make the
-            prediction on.
+            The image bytes or Cloud Storage URI to make
+            the prediction on.
         mime_type (str):
             The MIME type of the content of the image.
             Only the images in below listed MIME types are

google/cloud/aiplatform/v1/schema/predict/instance_v1/types/image_object_detection.py

@@ -26,8 +26,8 @@ class ImageObjectDetectionPredictionInstance(proto.Message):
     r"""Prediction input format for Image Object Detection.
     Attributes:
         content (str):
-            The image bytes or GCS URI to make the
-            prediction on.
+            The image bytes or Cloud Storage URI to make
+            the prediction on.
         mime_type (str):
             The MIME type of the content of the image.
             Only the images in below listed MIME types are

google/cloud/aiplatform/v1/schema/predict/instance_v1/types/text_extraction.py

@@ -36,7 +36,7 @@ class TextExtractionPredictionInstance(proto.Message):
             If a key is provided, the batch prediction
             result will by mapped to this key. If omitted,
             then the batch prediction result will contain
-            the entire input instance. AI Platform will not
+            the entire input instance. Vertex AI will not
             check if keys in the request are duplicates, so
             it is up to the caller to ensure the keys are
             unique.

google/cloud/aiplatform/v1/schema/predict/params_v1/types/video_classification.py

@@ -37,16 +37,16 @@ class VideoClassificationPredictionParams(proto.Message):
             10,000.
         segment_classification (bool):
             Set to true to request segment-level
-            classification. AI Platform returns labels and
+            classification. Vertex AI returns labels and
             their confidence scores for the entire time
             segment of the video that user specified in the
             input instance. Default value is true
         shot_classification (bool):
             Set to true to request shot-level
-            classification. AI Platform determines the
+            classification. Vertex AI determines the
             boundaries for each camera shot in the entire
             time segment of the video that user specified in
-            the input instance. AI Platform then returns
+            the input instance. Vertex AI then returns
             labels and their confidence scores for each
             detected shot, along with the start and end time
             of the shot.
@@ -57,15 +57,14 @@ class VideoClassificationPredictionParams(proto.Message):
             Default value is false
         one_sec_interval_classification (bool):
             Set to true to request classification for a
-            video at one-second intervals. AI Platform
-            returns labels and their confidence scores for
-            each second of the entire time segment of the
-            video that user specified in the input WARNING:
-            Model evaluation is not done for this
-            classification type, the quality of it depends
-            on the training data, but there are no metrics
-            provided to describe that quality. Default value
-            is false
+            video at one-second intervals. Vertex AI returns
+            labels and their confidence scores for each
+            second of the entire time segment of the video
+            that user specified in the input WARNING: Model
+            evaluation is not done for this classification
+            type, the quality of it depends on the training
+            data, but there are no metrics provided to
+            describe that quality. Default value is false
     """
 
     confidence_threshold = proto.Field(proto.FLOAT, number=1,)

google/cloud/aiplatform/v1/schema/predict/prediction_v1/types/classification.py

@@ -27,8 +27,7 @@ class ClassificationPredictionResult(proto.Message):
     Attributes:
         ids (Sequence[int]):
             The resource IDs of the AnnotationSpecs that
-            had been identified, ordered by the confidence
-            score descendingly.
+            had been identified.
         display_names (Sequence[str]):
             The display names of the AnnotationSpecs that
             had been identified, order matches the IDs.

google/cloud/aiplatform/v1/schema/trainingjob/definition_v1/types/automl_tables.py

@@ -139,6 +139,9 @@ class AutoMlTablesInputs(proto.Message):
             predictions to a BigQuery table. If this
             configuration is absent, then the export is not
             performed.
+        additional_experiments (Sequence[str]):
+            Additional experiment flags for the Tables
+            training pipeline.
     """
 
     class Transformation(proto.Message):
@@ -401,6 +404,7 @@ class TextArrayTransformation(proto.Message):
         number=10,
         message=gcastd_export_evaluated_data_items_config.ExportEvaluatedDataItemsConfig,
     )
+    additional_experiments = proto.RepeatedField(proto.STRING, number=11,)
 
 
 class AutoMlTablesMetadata(proto.Message):

google/cloud/aiplatform/v1/schema/trainingjob/definition_v1/types/automl_video_action_recognition.py

@@ -48,6 +48,8 @@ class ModelType(proto.Enum):
         MODEL_TYPE_UNSPECIFIED = 0
         CLOUD = 1
         MOBILE_VERSATILE_1 = 2
+        MOBILE_JETSON_VERSATILE_1 = 3
+        MOBILE_CORAL_VERSATILE_1 = 4
 
     model_type = proto.Field(proto.ENUM, number=1, enum=ModelType,)
 

google/cloud/aiplatform/v1/schema/trainingjob/definition_v1/types/export_evaluated_data_items_config.py

@@ -33,7 +33,6 @@ class ExportEvaluatedDataItemsConfig(proto.Message):
 
             If not specified, then results are exported to the following
             auto-created BigQuery table:
-
             <project_id>:export_evaluated_examples_<model_name>_<yyyy_MM_dd'T'HH_mm_ss_SSS'Z'>.evaluated_examples
         override_existing_table (bool):
             If true and an export destination is

google/cloud/aiplatform_v1/__init__.py

@@ -34,8 +34,10 @@
 from .types.accelerator_type import AcceleratorType
 from .types.annotation import Annotation
 from .types.annotation_spec import AnnotationSpec
+from .types.artifact import Artifact
 from .types.batch_prediction_job import BatchPredictionJob
 from .types.completion_stats import CompletionStats
+from .types.context import Context
 from .types.custom_job import ContainerSpec
 from .types.custom_job import CustomJob
 from .types.custom_job import CustomJobSpec
@@ -86,6 +88,7 @@
 from .types.endpoint_service import UndeployModelResponse
 from .types.endpoint_service import UpdateEndpointRequest
 from .types.env_var import EnvVar
+from .types.execution import Execution
 from .types.hyperparameter_tuning_job import HyperparameterTuningJob
 from .types.io import BigQueryDestination
 from .types.io import BigQuerySource
@@ -118,6 +121,7 @@
 from .types.job_service import ListHyperparameterTuningJobsResponse
 from .types.job_state import JobState
 from .types.machine_resources import AutomaticResources
+from .types.machine_resources import AutoscalingMetricSpec
 from .types.machine_resources import BatchDedicatedResources
 from .types.machine_resources import DedicatedResources
 from .types.machine_resources import DiskSpec
@@ -157,10 +161,20 @@
 from .types.model_service import UploadModelResponse
 from .types.operation import DeleteOperationMetadata
 from .types.operation import GenericOperationMetadata
+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_service import CancelPipelineJobRequest
 from .types.pipeline_service import CancelTrainingPipelineRequest
+from .types.pipeline_service import CreatePipelineJobRequest
 from .types.pipeline_service import CreateTrainingPipelineRequest
+from .types.pipeline_service import DeletePipelineJobRequest
 from .types.pipeline_service import DeleteTrainingPipelineRequest
+from .types.pipeline_service import GetPipelineJobRequest
 from .types.pipeline_service import GetTrainingPipelineRequest
+from .types.pipeline_service import ListPipelineJobsRequest
+from .types.pipeline_service import ListPipelineJobsResponse
 from .types.pipeline_service import ListTrainingPipelinesRequest
 from .types.pipeline_service import ListTrainingPipelinesResponse
 from .types.pipeline_state import PipelineState
@@ -185,6 +199,7 @@
 from .types.training_pipeline import TimestampSplit
 from .types.training_pipeline import TrainingPipeline
 from .types.user_action_reference import UserActionReference
+from .types.value import Value
 
 __all__ = (
     "DatasetServiceAsyncClient",
@@ -199,7 +214,9 @@
     "ActiveLearningConfig",
     "Annotation",
     "AnnotationSpec",
+    "Artifact",
     "AutomaticResources",
+    "AutoscalingMetricSpec",
     "BatchDedicatedResources",
     "BatchMigrateResourcesOperationMetadata",
     "BatchMigrateResourcesRequest",
@@ -211,10 +228,12 @@
     "CancelCustomJobRequest",
     "CancelDataLabelingJobRequest",
     "CancelHyperparameterTuningJobRequest",
+    "CancelPipelineJobRequest",
     "CancelTrainingPipelineRequest",
     "CompletionStats",
     "ContainerRegistryDestination",
     "ContainerSpec",
+    "Context",
     "CreateBatchPredictionJobRequest",
     "CreateCustomJobRequest",
     "CreateDataLabelingJobRequest",
@@ -223,6 +242,7 @@
     "CreateEndpointOperationMetadata",
     "CreateEndpointRequest",
     "CreateHyperparameterTuningJobRequest",
+    "CreatePipelineJobRequest",
     "CreateSpecialistPoolOperationMetadata",
     "CreateSpecialistPoolRequest",
     "CreateTrainingPipelineRequest",
@@ -241,6 +261,7 @@
     "DeleteHyperparameterTuningJobRequest",
     "DeleteModelRequest",
     "DeleteOperationMetadata",
+    "DeletePipelineJobRequest",
     "DeleteSpecialistPoolRequest",
     "DeleteTrainingPipelineRequest",
     "DeployModelOperationMetadata",
@@ -253,6 +274,7 @@
     "Endpoint",
     "EndpointServiceClient",
     "EnvVar",
+    "Execution",
     "ExportDataConfig",
     "ExportDataOperationMetadata",
     "ExportDataRequest",
@@ -275,6 +297,7 @@
     "GetModelEvaluationRequest",
     "GetModelEvaluationSliceRequest",
     "GetModelRequest",
+    "GetPipelineJobRequest",
     "GetSpecialistPoolRequest",
     "GetTrainingPipelineRequest",
     "HyperparameterTuningJob",
@@ -307,6 +330,8 @@
     "ListModelEvaluationsResponse",
     "ListModelsRequest",
     "ListModelsResponse",
+    "ListPipelineJobsRequest",
+    "ListPipelineJobsResponse",
     "ListSpecialistPoolsRequest",
     "ListSpecialistPoolsResponse",
     "ListTrainingPipelinesRequest",
@@ -323,8 +348,12 @@
     "ModelEvaluation",
     "ModelEvaluationSlice",
     "ModelServiceClient",
+    "PipelineJob",
+    "PipelineJobDetail",
     "PipelineServiceClient",
     "PipelineState",
+    "PipelineTaskDetail",
+    "PipelineTaskExecutorDetail",
     "Port",
     "PredefinedSplit",
     "PredictRequest",
@@ -356,5 +385,6 @@
     "UploadModelRequest",
     "UploadModelResponse",
     "UserActionReference",
+    "Value",
     "WorkerPoolSpec",
 )

google/cloud/aiplatform_v1/gapic_metadata.json

@@ -570,26 +570,51 @@
         "grpc": {
           "libraryClient": "PipelineServiceClient",
           "rpcs": {
+            "CancelPipelineJob": {
+              "methods": [
+                "cancel_pipeline_job"
+              ]
+            },
             "CancelTrainingPipeline": {
               "methods": [
                 "cancel_training_pipeline"
               ]
             },
+            "CreatePipelineJob": {
+              "methods": [
+                "create_pipeline_job"
+              ]
+            },
             "CreateTrainingPipeline": {
               "methods": [
                 "create_training_pipeline"
               ]
             },
+            "DeletePipelineJob": {
+              "methods": [
+                "delete_pipeline_job"
+              ]
+            },
             "DeleteTrainingPipeline": {
               "methods": [
                 "delete_training_pipeline"
               ]
             },
+            "GetPipelineJob": {
+              "methods": [
+                "get_pipeline_job"
+              ]
+            },
             "GetTrainingPipeline": {
               "methods": [
                 "get_training_pipeline"
               ]
             },
+            "ListPipelineJobs": {
+              "methods": [
+                "list_pipeline_jobs"
+              ]
+            },
             "ListTrainingPipelines": {
               "methods": [
                 "list_training_pipelines"
@@ -600,26 +625,51 @@
         "grpc-async": {
           "libraryClient": "PipelineServiceAsyncClient",
           "rpcs": {
+            "CancelPipelineJob": {
+              "methods": [
+                "cancel_pipeline_job"
+              ]
+            },
             "CancelTrainingPipeline": {
               "methods": [
                 "cancel_training_pipeline"
               ]
             },
+            "CreatePipelineJob": {
+              "methods": [
+                "create_pipeline_job"
+              ]
+            },
             "CreateTrainingPipeline": {
               "methods": [
                 "create_training_pipeline"
               ]
             },
+            "DeletePipelineJob": {
+              "methods": [
+                "delete_pipeline_job"
+              ]
+            },
             "DeleteTrainingPipeline": {
               "methods": [
                 "delete_training_pipeline"
               ]
             },
+            "GetPipelineJob": {
+              "methods": [
+                "get_pipeline_job"
+              ]
+            },
             "GetTrainingPipeline": {
               "methods": [
                 "get_training_pipeline"
               ]
             },
+            "ListPipelineJobs": {
+              "methods": [
+                "list_pipeline_jobs"
+              ]
+            },
             "ListTrainingPipelines": {
               "methods": [
                 "list_training_pipelines"

google/cloud/aiplatform_v1/services/job_service/async_client.py

@@ -87,6 +87,8 @@ class JobServiceAsyncClient:
     )
     model_path = staticmethod(JobServiceClient.model_path)
     parse_model_path = staticmethod(JobServiceClient.parse_model_path)
+    network_path = staticmethod(JobServiceClient.network_path)
+    parse_network_path = staticmethod(JobServiceClient.parse_network_path)
     trial_path = staticmethod(JobServiceClient.trial_path)
     parse_trial_path = staticmethod(JobServiceClient.parse_trial_path)
     common_billing_account_path = staticmethod(

google/cloud/aiplatform_v1/services/job_service/client.py

@@ -285,6 +285,21 @@ def parse_model_path(path: str) -> Dict[str, str]:
         )
         return m.groupdict() if m else {}
 
+    @staticmethod
+    def network_path(project: str, network: str,) -> str:
+        """Returns a fully-qualified network string."""
+        return "projects/{project}/global/networks/{network}".format(
+            project=project, network=network,
+        )
+
+    @staticmethod
+    def parse_network_path(path: str) -> Dict[str, str]:
+        """Parses a network path into its component segments."""
+        m = re.match(
+            r"^projects/(?P<project>.+?)/global/networks/(?P<network>.+?)$", path
+        )
+        return m.groupdict() if m else {}
+
     @staticmethod
     def trial_path(project: str, location: str, study: str, trial: str,) -> str:
         """Returns a fully-qualified trial string."""