def _log_model():
request_message = _get_request_message(LogModel())
try:
model = json.loads(request_message.model_json)
except: # NB: can not be more specific here due to python2 compatibility
raise MlflowException(
"Malformed model info. \n {} \n is not a valid JSON.".format(
request_message.model_json),
error_code=INVALID_PARAMETER_VALUE,
)
missing_fields = set(
("artifact_path", "flavors", "utc_time_created", "run_id")) - set(
model.keys())
if missing_fields:
raise MlflowException(
"Model json is missing mandatory fields: {}".format(
missing_fields),
error_code=INVALID_PARAMETER_VALUE,
)
_get_tracking_store().record_logged_model(
run_id=request_message.run_id, mlflow_model=Model.from_dict(model))
response_message = LogModel.Response()
response = Response(mimetype="application/json")
response.set_data(message_to_json(response_message))
return response
def test_model_uuid():
m = Model()
assert m.model_uuid is not None
assert _is_valid_uuid(m.model_uuid)
m2 = Model()
assert m.model_uuid != m2.model_uuid
m_dict = m.to_dict()
assert m_dict["model_uuid"] == m.model_uuid
m3 = Model.from_dict(m_dict)
assert m3.model_uuid == m.model_uuid
m_dict.pop("model_uuid")
m4 = Model.from_dict(m_dict)
assert m4.model_uuid is None