def test_success_create_model(self, mock_hook):
task = MLEngineCreateModelOperator(task_id="task-id",
project_id=TEST_PROJECT_ID,
model=TEST_MODEL,
gcp_conn_id=TEST_GCP_CONN_ID,
delegate_to=TEST_DELEGATE_TO)
task.execute(None)
mock_hook.assert_called_once_with(delegate_to=TEST_DELEGATE_TO,
gcp_conn_id=TEST_GCP_CONN_ID)
mock_hook.return_value.create_model.assert_called_once_with(
project_id=TEST_PROJECT_ID, model=TEST_MODEL)
runtime_version="1.15",
python_version="3.7",
job_dir=JOB_DIR,
package_uris=[TRAINER_URI],
training_python_module=TRAINER_PY_MODULE,
training_args=[],
labels={"job_type": "training"},
hyperparameters=hyperparams,
)
# [END howto_operator_gcp_mlengine_training]
# [START howto_operator_gcp_mlengine_create_model]
create_model = MLEngineCreateModelOperator(
task_id="create-model",
project_id=PROJECT_ID,
model={
"name": MODEL_NAME,
},
)
# [END howto_operator_gcp_mlengine_create_model]
# [START howto_operator_gcp_mlengine_get_model]
get_model = MLEngineGetModelOperator(
task_id="get-model",
project_id=PROJECT_ID,
model_name=MODEL_NAME,
)
# [END howto_operator_gcp_mlengine_get_model]
# [START howto_operator_gcp_mlengine_print_model]
get_model_result = BashOperator(
