def test_success(self, mock_hook):
task = MLEngineListVersionsOperator(
task_id="task-id",
project_id=TEST_PROJECT_ID,
model_name=TEST_MODEL_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.list_versions.assert_called_once_with(
project_id=TEST_PROJECT_ID,
model_name=TEST_MODEL_NAME,
)
def test_missing_model_name(self):
with self.assertRaises(AirflowException):
MLEngineListVersionsOperator(
task_id="task-id",
project_id=TEST_PROJECT_ID,
model_name=None,
gcp_conn_id=TEST_GCP_CONN_ID,
delegate_to=TEST_DELEGATE_TO,
)
"runtime_version": "1.14",
"machineType": "mls1-c1-m2",
"framework": "TENSORFLOW",
"pythonVersion": "3.5"
})
set_defaults_version = MLEngineSetDefaultVersionOperator(
task_id="set-default-version",
project_id=PROJECT_ID,
model_name=MODEL_NAME,
version_name="v2",
)
list_version = MLEngineListVersionsOperator(
task_id="list-version",
project_id=PROJECT_ID,
model_name=MODEL_NAME,
)
list_version_result = BashOperator(
bash_command="echo \"{{ task_instance.xcom_pull('list-version') }}\"",
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",