def test_success(self, mock_hook):
task = MLEngineDeleteVersionOperator(
task_id="task-id",
project_id=TEST_PROJECT_ID,
model_name=TEST_MODEL_NAME,
version_name=TEST_VERSION_NAME,
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.delete_version.assert_called_once_with(
project_id=TEST_PROJECT_ID,
model_name=TEST_MODEL_NAME,
version_name=TEST_VERSION_NAME)
def test_missing_model_name(self):
with self.assertRaises(AirflowException):
MLEngineDeleteVersionOperator(
task_id="task-id",
project_id=TEST_PROJECT_ID,
model_name=None,
version_name=TEST_VERSION_NAME,
gcp_conn_id=TEST_GCP_CONN_ID,
delegate_to=TEST_DELEGATE_TO,
)
task_id="list-version-result",
)
prediction = MLEngineBatchPredictionOperator(
task_id="prediction",
project_id="polidea-airflow",
job_id="prediciton-{{ ts_nodash }}-{{ params.model_name }}",
region="us-central1",
model_name=MODEL_NAME,
data_format="TEXT",
input_paths=[PREDICTION_INPUT],
output_path=PREDICTION_OUTPUT,
)
delete_version = MLEngineDeleteVersionOperator(task_id="delete-version",
project_id=PROJECT_ID,
model_name=MODEL_NAME,
version_name="v1")
delete_model = MLEngineDeleteModelOperator(task_id="delete-model",
project_id=PROJECT_ID,
model_name=MODEL_NAME,
delete_contents=True)
training >> create_version
training >> create_version_2
create_model >> get_model >> get_model_result
create_model >> create_version >> create_version_2 >> set_defaults_version >> list_version
create_version >> prediction
create_version_2 >> prediction
prediction >> delete_version
list_version >> list_version_result