def test_fail(self, mock_hook):
task = MLEngineManageModelOperator(task_id="task-id",
project_id=TEST_PROJECT_ID,
model=TEST_MODEL,
operation="invalid",
gcp_conn_id=TEST_GCP_CONN_ID,
delegate_to=TEST_DELEGATE_TO)
with self.assertRaises(ValueError):
task.execute(None)
def test_success_create_model(self, mock_hook):
task = MLEngineManageModelOperator(task_id="task-id",
project_id=TEST_PROJECT_ID,
model=TEST_MODEL,
operation="create",
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)
def test_success_get_model(self, mock_hook):
task = MLEngineManageModelOperator(task_id="task-id",
project_id=TEST_PROJECT_ID,
model=TEST_MODEL,
operation="get",
gcp_conn_id=TEST_GCP_CONN_ID,
delegate_to=TEST_DELEGATE_TO)
result = 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.get_model.assert_called_once_with(
project_id=TEST_PROJECT_ID, model_name=TEST_MODEL_NAME)
self.assertEqual(mock_hook.return_value.get_model.return_value, result)
def test_success_get_model(self, mock_hook):
task = MLEngineManageModelOperator(
task_id="task-id",
project_id=TEST_PROJECT_ID,
model=TEST_MODEL,
operation="get",
gcp_conn_id=TEST_GCP_CONN_ID,
delegate_to=TEST_DELEGATE_TO,
impersonation_chain=TEST_IMPERSONATION_CHAIN,
)
result = task.execute(None)
mock_hook.assert_called_once_with(
delegate_to=TEST_DELEGATE_TO,
gcp_conn_id=TEST_GCP_CONN_ID,
impersonation_chain=TEST_IMPERSONATION_CHAIN,
)
mock_hook.return_value.get_model.assert_called_once_with(
project_id=TEST_PROJECT_ID, model_name=TEST_MODEL_NAME)
assert mock_hook.return_value.get_model.return_value == result
task_id="training",
project_id=PROJECT_ID,
region="us-central1",
job_id="training-job-{{ ts_nodash }}-{{ params.model_name }}",
runtime_version="1.14",
python_version="3.5",
job_dir=JOB_DIR,
package_uris=[TRAINER_URI],
training_python_module=TRAINER_PY_MODULE,
training_args=[],
)
create_model = MLEngineManageModelOperator(
task_id="create-model",
project_id=PROJECT_ID,
operation='create',
model={
"name": MODEL_NAME,
},
)
get_model = MLEngineManageModelOperator(task_id="get-model",
project_id=PROJECT_ID,
operation="get",
model={
"name": MODEL_NAME,
})
get_model_result = BashOperator(
bash_command="echo \"{{ task_instance.xcom_pull('get-model') }}\"",
task_id="get-model-result",
)
