def test_success(self, mock_hook):
task = MLEngineSetDefaultVersionOperator(
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.set_default_version.assert_called_once_with(
project_id=TEST_PROJECT_ID,
model_name=TEST_MODEL_NAME,
version_name=TEST_VERSION_NAME
)
def test_missing_version_name(self):
with pytest.raises(AirflowException):
MLEngineSetDefaultVersionOperator(
task_id="task-id",
project_id=TEST_PROJECT_ID,
model_name=TEST_MODEL_NAME,
version_name=None,
gcp_conn_id=TEST_GCP_CONN_ID,
delegate_to=TEST_DELEGATE_TO,
)
version={
"name": "v2",
"description": "Second version",
"deployment_uri": SAVED_MODEL_PATH,
"runtime_version": "1.15",
"machineType": "mls1-c1-m2",
"framework": "TENSORFLOW",
"pythonVersion": "3.7",
},
)
# [END howto_operator_gcp_mlengine_create_version2]
# [START howto_operator_gcp_mlengine_default_version]
set_defaults_version = MLEngineSetDefaultVersionOperator(
task_id="set-default-version",
project_id=PROJECT_ID,
model_name=MODEL_NAME,
version_name="v2",
)
# [END howto_operator_gcp_mlengine_default_version]
# [START howto_operator_gcp_mlengine_list_versions]
list_version = MLEngineListVersionsOperator(
task_id="list-version",
project_id=PROJECT_ID,
model_name=MODEL_NAME,
)
# [END howto_operator_gcp_mlengine_list_versions]
# [START howto_operator_gcp_mlengine_print_versions]
list_version_result = BashOperator(
bash_command=f"echo {list_version.output}",