Class PipelineServiceClient (1.1.1)

Version 1.1.1

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PipelineServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

A service for creating and managing Vertex AI's pipelines. This includes both TrainingPipeline resources (used for AutoML and custom training) and PipelineJob resources (used for Vertex Pipelines).

Inheritance

builtins.object > PipelineServiceClient

Properties

transport

Returns the transport used by the client instance.

Returns

Type	Description
PipelineServiceTransport	The transport used by the client instance.

Methods

PipelineServiceClient

PipelineServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the pipeline service client.

Parameters

Name	Description
credentials	Optional[google.auth.credentials.Credentials] The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport	Union[str, PipelineServiceTransport] The transport to use. If set to None, a transport is chosen automatically.
client_options	google.api_core.client_options.ClientOptions Custom options for the client. It won't take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.
client_info	google.api_core.gapic_v1.client_info.ClientInfo The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own client library.

Exceptions

Type	Description
google.auth.exceptions.MutualTLSChannelError	If mutual TLS transport creation failed for any reason.

cancel_training_pipeline

cancel_training_pipeline(request: Optional[google.cloud.aiplatform_v1.types.pipeline_service.CancelTrainingPipelineRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use xref_PipelineService.GetTrainingPipeline or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a xref_TrainingPipeline.error value with a google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to Code.CANCELLED, and xref_TrainingPipeline.state is set to CANCELLED.

Parameters

Name	Description
request	google.cloud.aiplatform_v1.types.CancelTrainingPipelineRequest The request object. Request message for PipelineService.CancelTrainingPipeline.
name	str Required. The name of the TrainingPipeline to cancel. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

common_billing_account_path

common_billing_account_path(billing_account: str)

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str)

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str)

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str)

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str)

Returns a fully-qualified project string.

create_training_pipeline

create_training_pipeline(request: Optional[google.cloud.aiplatform_v1.types.pipeline_service.CreateTrainingPipelineRequest] = None, *, parent: Optional[str] = None, training_pipeline: Optional[google.cloud.aiplatform_v1.types.training_pipeline.TrainingPipeline] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.

Parameters

Name	Description
request	google.cloud.aiplatform_v1.types.CreateTrainingPipelineRequest The request object. Request message for PipelineService.CreateTrainingPipeline.
parent	str Required. The resource name of the Location to create the TrainingPipeline in. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
training_pipeline	google.cloud.aiplatform_v1.types.TrainingPipeline Required. The TrainingPipeline to create. This corresponds to the training_pipeline field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.cloud.aiplatform_v1.types.TrainingPipeline	The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.

delete_training_pipeline

delete_training_pipeline(request: Optional[google.cloud.aiplatform_v1.types.pipeline_service.DeleteTrainingPipelineRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes a TrainingPipeline.

Parameters

Name	Description
request	google.cloud.aiplatform_v1.types.DeleteTrainingPipelineRequest The request object. Request message for PipelineService.DeleteTrainingPipeline.
name	str Required. The name of the TrainingPipeline resource to be deleted. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns

Type

Description

google.api_core.operation.Operation

An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

endpoint_path

endpoint_path(project: str, location: str, endpoint: str)

Returns a fully-qualified endpoint string.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter

Name	Description
filename	str The path to the service account private key json file.

Returns

Type	Description
PipelineServiceClient	The constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

Creates an instance of this client using the provided credentials info.

Parameter

Name	Description
info	dict The service account private key info.

Returns

Type	Description
PipelineServiceClient	The constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter

Name	Description
filename	str The path to the service account private key json file.

Returns

Type	Description
PipelineServiceClient	The constructed client.

get_training_pipeline

get_training_pipeline(request: Optional[google.cloud.aiplatform_v1.types.pipeline_service.GetTrainingPipelineRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a TrainingPipeline.

Parameters

Name	Description
request	google.cloud.aiplatform_v1.types.GetTrainingPipelineRequest The request object. Request message for PipelineService.GetTrainingPipeline.
name	str Required. The name of the TrainingPipeline resource. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.cloud.aiplatform_v1.types.TrainingPipeline	The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.

list_training_pipelines

list_training_pipelines(request: Optional[google.cloud.aiplatform_v1.types.pipeline_service.ListTrainingPipelinesRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists TrainingPipelines in a Location.

Parameters

Name	Description
request	google.cloud.aiplatform_v1.types.ListTrainingPipelinesRequest The request object. Request message for PipelineService.ListTrainingPipelines.
parent	str Required. The resource name of the Location to list the TrainingPipelines from. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.cloud.aiplatform_v1.services.pipeline_service.pagers.ListTrainingPipelinesPager	Response message for PipelineService.ListTrainingPipelines Iterating over this object will yield results and resolve additional pages automatically.

model_path

model_path(project: str, location: str, model: str)

Returns a fully-qualified model string.

parse_common_billing_account_path

parse_common_billing_account_path(path: str)

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str)

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str)

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str)

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str)

Parse a project path into its component segments.

parse_endpoint_path

parse_endpoint_path(path: str)

Parses a endpoint path into its component segments.

parse_model_path

parse_model_path(path: str)

Parses a model path into its component segments.

parse_training_pipeline_path

parse_training_pipeline_path(path: str)

Parses a training_pipeline path into its component segments.

training_pipeline_path

training_pipeline_path(project: str, location: str, training_pipeline: str)

Returns a fully-qualified training_pipeline string.