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PipelineServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1beta1.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 AI Platform's pipelines.
Inheritance
builtins.object > PipelineServiceClientProperties
transport
Return the transport used by the client instance.
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_v1beta1.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>)
Instantiate 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 |
client_options_lib.ClientOptions
Custom options for the client. It won't take effect if a |
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 |
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_v1beta1.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
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
TrainingPipeline.error
value with a google.rpc.Status.code
of
1, corresponding to Code.CANCELLED
, and
TrainingPipeline.state
is set to CANCELLED
.
Name | Description |
request |
`.pipeline_service.CancelTrainingPipelineRequest`
The request object. Request message for |
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)
Return a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str)
Return a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str)
Return a fully-qualified location string.
common_organization_path
common_organization_path(organization: str)
Return a fully-qualified organization string.
common_project_path
common_project_path(project: str)
Return a fully-qualified project string.
create_training_pipeline
create_training_pipeline(request: Optional[google.cloud.aiplatform_v1beta1.types.pipeline_service.CreateTrainingPipelineRequest] = None, *, parent: Optional[str] = None, training_pipeline: Optional[google.cloud.aiplatform_v1beta1.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 |
`.pipeline_service.CreateTrainingPipelineRequest`
The request object. Request message for |
parent |
`str`
Required. The resource name of the Location to create the TrainingPipeline in. Format: |
training_pipeline |
`.gca_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 |
`.gca_training_pipeline.TrainingPipeline` | The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from AI Platform's Dataset which becomes the training input, ``upload`` the Model to AI Platform, and evaluate the Model. |
delete_training_pipeline
delete_training_pipeline(request: Optional[google.cloud.aiplatform_v1beta1.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 |
`.pipeline_service.DeleteTrainingPipelineRequest`
The request object. Request message for |
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 |
`.ga_operation.Operation` | An object representing a long-running operation. The result type for the operation will be `.empty.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)
Return 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 |
{@api.name} | 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 |
{@api.name} | The constructed client. |
get_training_pipeline
get_training_pipeline(request: Optional[google.cloud.aiplatform_v1beta1.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 |
`.pipeline_service.GetTrainingPipelineRequest`
The request object. Request message for |
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 |
`.training_pipeline.TrainingPipeline` | The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from AI Platform's Dataset which becomes the training input, ``upload`` the Model to AI Platform, and evaluate the Model. |
list_training_pipelines
list_training_pipelines(request: Optional[google.cloud.aiplatform_v1beta1.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 |
`.pipeline_service.ListTrainingPipelinesRequest`
The request object. Request message for |
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 |
`.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)
Return 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)
Parse a endpoint path into its component segments.
parse_model_path
parse_model_path(path: str)
Parse a model path into its component segments.
parse_training_pipeline_path
parse_training_pipeline_path(path: str)
Parse a training_pipeline path into its component segments.
training_pipeline_path
training_pipeline_path(project: str, location: str, training_pipeline: str)
Return a fully-qualified training_pipeline string.