def sample_cancel_pipeline_job():
    # Create a client
    client = aiplatform_v1beta1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CancelPipelineJobRequest(name="name_value", )

    # Make the request
    client.cancel_pipeline_job(request=request)
def sample_get_pipeline_job():
    # Create a client
    client = aiplatform_v1beta1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetPipelineJobRequest(name="name_value", )

    # Make the request
    response = client.get_pipeline_job(request=request)

    # Handle the response
    print(response)
def sample_create_pipeline_job():
    # Create a client
    client = aiplatform_v1beta1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreatePipelineJobRequest(
        parent="parent_value", )

    # Make the request
    response = client.create_pipeline_job(request=request)

    # Handle the response
    print(response)
Example #4
0
def sample_list_training_pipelines():
    # Create a client
    client = aiplatform_v1beta1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListTrainingPipelinesRequest(
        parent="parent_value", )

    # Make the request
    page_result = client.list_training_pipelines(request=request)

    # Handle the response
    for response in page_result:
        print(response)
def sample_delete_pipeline_job():
    # Create a client
    client = aiplatform_v1beta1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DeletePipelineJobRequest(name="name_value", )

    # Make the request
    operation = client.delete_pipeline_job(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Example #6
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def sample_create_training_pipeline():
    # Create a client
    client = aiplatform_v1beta1.PipelineServiceClient()

    # Initialize request argument(s)
    training_pipeline = aiplatform_v1beta1.TrainingPipeline()
    training_pipeline.display_name = "display_name_value"
    training_pipeline.training_task_definition = "training_task_definition_value"
    training_pipeline.training_task_inputs.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.CreateTrainingPipelineRequest(
        parent="parent_value",
        training_pipeline=training_pipeline,
    )

    # Make the request
    response = client.create_training_pipeline(request=request)

    # Handle the response
    print(response)