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PipelineServiceAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport] = 'grpc_asyncio', client_options: <module 'google.api_core.client_options' from '/workspace/python-aiplatform/.nox/docfx/lib/python3.8/site-packages/google/api_core/client_options.py'> = 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 > PipelineServiceAsyncClientProperties
transport
Returns the transport used by the client instance.
Type | Description |
PipelineServiceTransport | The transport used by the client instance. |
Methods
PipelineServiceAsyncClient
PipelineServiceAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport] = 'grpc_asyncio', client_options: <module 'google.api_core.client_options' from '/workspace/python-aiplatform/.nox/docfx/lib/python3.8/site-packages/google/api_core/client_options.py'> = 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.
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 |
ClientOptions
Custom options for the client. It won't take effect if a |
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
.
Name | Description |
request |
CancelTrainingPipelineRequest
The request object. Request message for PipelineService.CancelTrainingPipeline. |
name |
`str`
Required. The name of the TrainingPipeline to cancel. Format: |
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.
Name | Description |
request |
CreateTrainingPipelineRequest
The request object. Request message for PipelineService.CreateTrainingPipeline. |
parent |
`str`
Required. The resource name of the Location to create the TrainingPipeline in. Format: |
training_pipeline |
TrainingPipeline
Required. The TrainingPipeline to create. This corresponds to the |
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. |
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.
Name | Description |
request |
DeleteTrainingPipelineRequest
The request object. Request message for PipelineService.DeleteTrainingPipeline. |
name |
`str`
Required. The name of the TrainingPipeline resource to be deleted. Format: |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | 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.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
PipelineServiceAsyncClient | 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.
Name | Description |
info |
dict
The service account private key info. |
Type | Description |
PipelineServiceAsyncClient | 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.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
PipelineServiceAsyncClient | 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.
Name | Description |
request |
GetTrainingPipelineRequest
The request object. Request message for PipelineService.GetTrainingPipeline. |
name |
`str`
Required. The name of the TrainingPipeline resource. Format: |
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. |
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. |
get_transport_class
get_transport_class()
Returns an appropriate transport class.
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.
Name | Description |
request |
ListTrainingPipelinesRequest
The request object. Request message for PipelineService.ListTrainingPipelines. |
parent |
`str`
Required. The resource name of the Location to list the TrainingPipelines from. Format: |
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. |
Type | Description |
google.cloud.aiplatform_v1.services.pipeline_service.pagers.ListTrainingPipelinesAsyncPager | 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.