diff --git a/google/cloud/aiplatform_v1beta1/services/vizier_service/async_client.py b/google/cloud/aiplatform_v1beta1/services/vizier_service/async_client.py index 4f4ff19fb1..c55267c36f 100644 --- a/google/cloud/aiplatform_v1beta1/services/vizier_service/async_client.py +++ b/google/cloud/aiplatform_v1beta1/services/vizier_service/async_client.py @@ -255,9 +255,7 @@ async def create_study( Returns: google.cloud.aiplatform_v1beta1.types.Study: - LINT.IfChange A message representing a Study. - """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have @@ -328,9 +326,7 @@ async def get_study( Returns: google.cloud.aiplatform_v1beta1.types.Study: - LINT.IfChange A message representing a Study. - """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have @@ -548,9 +544,7 @@ async def lookup_study( Returns: google.cloud.aiplatform_v1beta1.types.Study: - LINT.IfChange A message representing a Study. - """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have diff --git a/google/cloud/aiplatform_v1beta1/services/vizier_service/client.py b/google/cloud/aiplatform_v1beta1/services/vizier_service/client.py index f4b0dc1504..0d8d1b9700 100644 --- a/google/cloud/aiplatform_v1beta1/services/vizier_service/client.py +++ b/google/cloud/aiplatform_v1beta1/services/vizier_service/client.py @@ -478,9 +478,7 @@ def create_study( Returns: google.cloud.aiplatform_v1beta1.types.Study: - LINT.IfChange A message representing a Study. - """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have @@ -551,9 +549,7 @@ def get_study( Returns: google.cloud.aiplatform_v1beta1.types.Study: - LINT.IfChange A message representing a Study. - """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have @@ -771,9 +767,7 @@ def lookup_study( Returns: google.cloud.aiplatform_v1beta1.types.Study: - LINT.IfChange A message representing a Study. - """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have diff --git a/google/cloud/aiplatform_v1beta1/types/custom_job.py b/google/cloud/aiplatform_v1beta1/types/custom_job.py index 7ec2a92c03..7d7edd9e37 100644 --- a/google/cloud/aiplatform_v1beta1/types/custom_job.py +++ b/google/cloud/aiplatform_v1beta1/types/custom_job.py @@ -120,6 +120,7 @@ class CustomJob(proto.Message): class CustomJobSpec(proto.Message): r"""Represents the spec of a CustomJob. + Next Id: 14 Attributes: worker_pool_specs (Sequence[google.cloud.aiplatform_v1beta1.types.WorkerPoolSpec]): diff --git a/google/cloud/aiplatform_v1beta1/types/featurestore.py b/google/cloud/aiplatform_v1beta1/types/featurestore.py index 5d19c1dee7..f28059c6e9 100644 --- a/google/cloud/aiplatform_v1beta1/types/featurestore.py +++ b/google/cloud/aiplatform_v1beta1/types/featurestore.py @@ -81,13 +81,39 @@ class OnlineServingConfig(proto.Message): Attributes: fixed_node_count (int): - The number of nodes for each cluster. The - number of nodes will not scale automatically but - can be scaled manually by providing different - values when updating. + The number of nodes for each cluster. The number of nodes + will not scale automatically but can be scaled manually by + providing different values when updating. Only one of + ``fixed_node_count`` and ``scaling`` can be set. Setting one + will reset the other. + scaling (google.cloud.aiplatform_v1beta1.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 + or equal to 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, number=1,) create_time = proto.Field(proto.MESSAGE, number=3, message=timestamp_pb2.Timestamp,) diff --git a/google/cloud/aiplatform_v1beta1/types/index_endpoint.py b/google/cloud/aiplatform_v1beta1/types/index_endpoint.py index c423957375..4bb17029db 100644 --- a/google/cloud/aiplatform_v1beta1/types/index_endpoint.py +++ b/google/cloud/aiplatform_v1beta1/types/index_endpoint.py @@ -171,6 +171,15 @@ class DeployedIndex(proto.Message): don't provide SLA when min_replica_count=1). If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. + dedicated_resources (google.cloud.aiplatform_v1beta1.types.DedicatedResources): + Optional. A description of resources that are dedicated to + the DeployedIndex, and that need a higher degree of manual + configuration. If min_replica_count is not set, the default + value is 2 (we don't provide SLA when min_replica_count=1). + If max_replica_count is not set, the default value is + min_replica_count. The max allowed replica count is 1000. + + Available machine types: n1-standard-16 n1-standard-32 enable_access_logging (bool): Optional. If true, private endpoint's access logs are sent to StackDriver Logging. @@ -227,6 +236,9 @@ class DeployedIndex(proto.Message): automatic_resources = proto.Field( proto.MESSAGE, number=7, message=machine_resources.AutomaticResources, ) + dedicated_resources = proto.Field( + proto.MESSAGE, number=16, message=machine_resources.DedicatedResources, + ) enable_access_logging = proto.Field(proto.BOOL, number=8,) deployed_index_auth_config = proto.Field( proto.MESSAGE, number=9, message="DeployedIndexAuthConfig", diff --git a/google/cloud/aiplatform_v1beta1/types/model.py b/google/cloud/aiplatform_v1beta1/types/model.py index 4120486a5e..f40e74a3b2 100644 --- a/google/cloud/aiplatform_v1beta1/types/model.py +++ b/google/cloud/aiplatform_v1beta1/types/model.py @@ -397,7 +397,7 @@ class ModelContainerSpec(proto.Message): r"""Specification of a container for serving predictions. Some fields in this message correspond to fields in the `Kubernetes Container v1 core - specification `__. + specification `__. Attributes: image_uri (str): @@ -463,7 +463,7 @@ class ModelContainerSpec(proto.Message): this syntax with ``$$``; for example: $$(VARIABLE_NAME) This field corresponds to the ``command`` field of the Kubernetes Containers `v1 core - API `__. + API `__. args (Sequence[str]): Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's @@ -502,7 +502,7 @@ class ModelContainerSpec(proto.Message): this syntax with ``$$``; for example: $$(VARIABLE_NAME) This field corresponds to the ``args`` field of the Kubernetes Containers `v1 core - API `__. + API `__. env (Sequence[google.cloud.aiplatform_v1beta1.types.EnvVar]): Immutable. List of environment variables to set in the container. After the container starts running, code running @@ -535,7 +535,7 @@ class ModelContainerSpec(proto.Message): This field corresponds to the ``env`` field of the Kubernetes Containers `v1 core - API `__. + API `__. ports (Sequence[google.cloud.aiplatform_v1beta1.types.Port]): Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to @@ -558,7 +558,7 @@ class ModelContainerSpec(proto.Message): Vertex AI does not use ports other than the first one listed. This field corresponds to the ``ports`` field of the Kubernetes Containers `v1 core - API `__. + API `__. predict_route (str): Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using diff --git a/google/cloud/aiplatform_v1beta1/types/model_deployment_monitoring_job.py b/google/cloud/aiplatform_v1beta1/types/model_deployment_monitoring_job.py index 146fba7fd6..7fa47a9c66 100644 --- a/google/cloud/aiplatform_v1beta1/types/model_deployment_monitoring_job.py +++ b/google/cloud/aiplatform_v1beta1/types/model_deployment_monitoring_job.py @@ -284,9 +284,10 @@ class ModelDeploymentMonitoringScheduleConfig(proto.Message): Attributes: monitor_interval (google.protobuf.duration_pb2.Duration): - Required. The model monitoring job running + Required. The model monitoring job scheduling interval. It will be rounded up to next full - hour. + hour. This defines how often the monitoring jobs + are triggered. """ monitor_interval = proto.Field( diff --git a/google/cloud/aiplatform_v1beta1/types/study.py b/google/cloud/aiplatform_v1beta1/types/study.py index 77032803f9..beccba62e9 100644 --- a/google/cloud/aiplatform_v1beta1/types/study.py +++ b/google/cloud/aiplatform_v1beta1/types/study.py @@ -27,8 +27,7 @@ class Study(proto.Message): - r"""LINT.IfChange - A message representing a Study. + r"""A message representing a Study. Attributes: name (str): diff --git a/tests/unit/gapic/aiplatform_v1beta1/test_index_endpoint_service.py b/tests/unit/gapic/aiplatform_v1beta1/test_index_endpoint_service.py index b8abbab31d..c90d804f64 100644 --- a/tests/unit/gapic/aiplatform_v1beta1/test_index_endpoint_service.py +++ b/tests/unit/gapic/aiplatform_v1beta1/test_index_endpoint_service.py @@ -43,6 +43,7 @@ ) from google.cloud.aiplatform_v1beta1.services.index_endpoint_service import pagers from google.cloud.aiplatform_v1beta1.services.index_endpoint_service import transports +from google.cloud.aiplatform_v1beta1.types import accelerator_type 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