def create_and_execute_static_pipeline(sagemaker_session):
# start the execution and wait for success
print(f"Starting static execution of pipeline '{STATIC_PIPELINE_NAME}'")
try:
execution_arn = test_end_to_end_pipeline_successful_execution(
sagemaker_session=sagemaker_session,
region_name=sagemaker_session.boto_session.region_name,
role=get_execution_role(sagemaker_session),
pipeline_name=STATIC_PIPELINE_NAME,
wait=True,
)
# now deploy the model package to an endpoint
_deploy_static_endpoint(
execution_arn=execution_arn,
sagemaker_session=sagemaker_session,
)
return execution_arn
except Exception:
# Pipeline already exists, meaning an execution was started by
# tests in a different thread
execution_arn = _get_static_pipeline_execution_arn(sagemaker_session)
_deploy_static_endpoint(
execution_arn=execution_arn,
sagemaker_session=sagemaker_session,
)
return execution_arn
def _deploy_static_endpoint(execution_arn, sagemaker_session):
try:
model_package_arn = get_model_package_arn_from_static_pipeline(
execution_arn, sagemaker_session)
model_package = ModelPackage(
role=get_execution_role(sagemaker_session),
model_package_arn=model_package_arn,
sagemaker_session=sagemaker_session,
)
model_package.deploy(1,
"ml.t2.medium",
endpoint_name=STATIC_ENDPOINT_NAME)
time.sleep(120)
except ClientError as e:
if e.response["Error"]["Code"] == "ValidationException":
print(
f"Endpoint {STATIC_ENDPOINT_NAME} already exists. Continuing.")
pass
else:
raise (e)
def role(feature_store_session):
return get_execution_role(feature_store_session)
def role(sagemaker_session):
return get_execution_role(sagemaker_session)
