async def sample_cancel_pipeline_job(): # Create a client client = aiplatform_v1beta1.PipelineServiceAsyncClient() # Initialize request argument(s) request = aiplatform_v1beta1.CancelPipelineJobRequest(name="name_value", ) # Make the request await client.cancel_pipeline_job(request=request)
async def sample_get_pipeline_job(): # Create a client client = aiplatform_v1beta1.PipelineServiceAsyncClient() # Initialize request argument(s) request = aiplatform_v1beta1.GetPipelineJobRequest(name="name_value", ) # Make the request response = await client.get_pipeline_job(request=request) # Handle the response print(response)
async def sample_create_pipeline_job(): # Create a client client = aiplatform_v1beta1.PipelineServiceAsyncClient() # Initialize request argument(s) request = aiplatform_v1beta1.CreatePipelineJobRequest( parent="parent_value", ) # Make the request response = await client.create_pipeline_job(request=request) # Handle the response print(response)
async def sample_list_training_pipelines(): # Create a client client = aiplatform_v1beta1.PipelineServiceAsyncClient() # 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 async for response in page_result: print(response)
async def sample_delete_pipeline_job(): # Create a client client = aiplatform_v1beta1.PipelineServiceAsyncClient() # 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 = await operation.result() # Handle the response print(response)
async def sample_create_training_pipeline(): # Create a client client = aiplatform_v1beta1.PipelineServiceAsyncClient() # 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 = await client.create_training_pipeline(request=request) # Handle the response print(response)