def sample_cancel_pipeline_job():
# Create a client
client = aiplatform_v1.PipelineServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.CancelPipelineJobRequest(name="name_value", )
# Make the request
client.cancel_pipeline_job(request=request)
def sample_cancel_training_pipeline():
# Create a client
client = aiplatform_v1.PipelineServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.CancelTrainingPipelineRequest(name="name_value", )
# Make the request
client.cancel_training_pipeline(request=request)
def sample_create_pipeline_job():
# Create a client
client = aiplatform_v1.PipelineServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.CreatePipelineJobRequest(parent="parent_value", )
# Make the request
response = client.create_pipeline_job(request=request)
# Handle the response
print(response)
def sample_get_training_pipeline():
# Create a client
client = aiplatform_v1.PipelineServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.GetTrainingPipelineRequest(name="name_value", )
# Make the request
response = client.get_training_pipeline(request=request)
# Handle the response
print(response)
def sample_list_pipeline_jobs():
# Create a client
client = aiplatform_v1.PipelineServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.ListPipelineJobsRequest(parent="parent_value", )
# Make the request
page_result = client.list_pipeline_jobs(request=request)
# Handle the response
for response in page_result:
print(response)
def sample_delete_training_pipeline():
# Create a client
client = aiplatform_v1.PipelineServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.DeleteTrainingPipelineRequest(name="name_value", )
# Make the request
operation = client.delete_training_pipeline(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
def sample_create_training_pipeline():
# Create a client
client = aiplatform_v1.PipelineServiceClient()
# Initialize request argument(s)
training_pipeline = aiplatform_v1.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_v1.CreateTrainingPipelineRequest(
parent="parent_value",
training_pipeline=training_pipeline,
)
# Make the request
response = client.create_training_pipeline(request=request)
# Handle the response
print(response)