I am facing an error while stroring the ML model information in MLFLOW dagshub

Question

Error I getting

Elasticnet model (alpha=0.500000, l1_ratio=0.500000): RMSE: 0.793164022927685 MAE: 0.6271946374319586 R2: 0.10862644997792636 Traceback (most recent call last): File "example.py", line 85, in mlflow.sklearn.log_model(lr, "model", registered_model_name="ElasticnetWineModel") File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\sklearn_init_.py", line 393, in log_model return Model.log( File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\models\model.py", line 304, in log mlflow.register_model( File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\tracking_model_registry\fluent.py", line 67, in register_model raise e File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\tracking_model_registry\fluent.py", line 58, in register_model create_model_response = client.create_registered_model(name) File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\tracking\client.py", line 1658, in create_registered_model return self._get_registry_client().create_registered_model(name, tags, description) File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\tracking_model_registry\client.py", line 59, in create_registered_model return self.store.create_registered_model(name, tags, description) File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\store\model_registry\rest_store.py", line 83, in cyour textreate_registered_model response_proto = self._call_endpoint(CreateRegisteredModel, req_body) File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\store\model_registry\rest_store.py", line 64, in _call_endpoint return call_endpoint(self.get_host_creds(), endpoint, method, json_body, response_proto) File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\utils\rest_utils.py", line 256, in call_endpoint response = verify_rest_response(response, endpoint) File "D:\DeepCNNClassifier\krishna\lib\site-packages\mlflow\utils\rest_utils.py", line 185, in verify_rest_response raise RestException(json.loads(response.text)) mlflow.exceptions.RestException: INTERNAL_ERROR: Response: {'error': 'unsupported endpoint, please contact [email protected]'}

Answer 1

Use mlflow==2.2.2 version and your error will be gone.