I run into this error while using MLFlow:
AttributeError: 'NoneType' object has no attribute 'enum_types_by_name'
Here is the relevant stack trace:
/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/mlflow/tracking/fluent.py in log_artifacts(local_dir, artifact_path)
724 """
725 run_id = _get_or_start_run().info.run_id
--> 726 MlflowClient().log_artifacts(run_id, local_dir, artifact_path)
727
728
/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/mlflow/tracking/client.py in log_artifacts(self, run_id, local_dir, artifact_path)
999 is_dir: True
1000 """
-> 1001 self._tracking_client.log_artifacts(run_id, local_dir, artifact_path)
1002
1003 @contextlib.contextmanager
/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/mlflow/tracking/_tracking_service/client.py in log_artifacts(self, run_id, local_dir, artifact_path)
344 :param artifact_path: If provided, the directory in ``artifact_uri`` to write to.
345 """
--> 346 self._get_artifact_repo(run_id).log_artifacts(local_dir, artifact_path)
347
348 def list_artifacts(self, run_id, path=None):
/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/mlflow/tracking/_tracking_service/client.py in _get_artifact_repo(self, run_id)
312 run.info.artifact_uri, self.tracking_uri
313 )
--> 314 artifact_repo = get_artifact_repository(artifact_uri)
315 # Cache the artifact repo to avoid a future network call, removing the oldest
316 # entry in the cache if there are too many elements
/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/mlflow/store/artifact/artifact_repository_registry.py in get_artifact_repository(artifact_uri)
105 requirements.
106 """
--> 107 return _artifact_repository_registry.get_artifact_repository(artifact_uri)
/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/mlflow/store/artifact/artifact_repository_registry.py in get_artifact_repository(self, artifact_uri)
71 )
72 )
---> 73 return repository(artifact_uri)
74
75
/databricks/python/lib/python3.9/site-packages/mlflow_databricks_artifacts/store/entrypoint.py in dbfs_artifact_repo_factory(artifact_uri)
52 # entrypoint function rather than the top-level module. Otherwise, entrypoint
53 # registration fails with import errors
---> 54 from mlflow_databricks_artifacts.store.artifact_repo import (
55 DatabricksArtifactRepository,
56 )
/databricks/python_shell/dbruntime/PythonPackageImportsInstrumentation/__init__.py in import_patch(name, globals, locals, fromlist, level)
169 # Import the desired module. If you're seeing this while debugging a failed import,
170 # look at preceding stack frames for relevant error information.
--> 171 original_result = python_builtin_import(name, globals, locals, fromlist, level)
172
173 is_root_import = thread_local._nest_level == 1
/databricks/python/lib/python3.9/site-packages/mlflow_databricks_artifacts/store/artifact_repo.py in <module>
23 )
24
---> 25 from mlflow_databricks_artifacts.protos.patched_databricks_artifacts_pb2 import (
26 DatabricksMlflowArtifactsService,
27 GetCredentialsForWrite,
/databricks/python_shell/dbruntime/PythonPackageImportsInstrumentation/__init__.py in import_patch(name, globals, locals, fromlist, level)
169 # Import the desired module. If you're seeing this while debugging a failed import,
170 # look at preceding stack frames for relevant error information.
--> 171 original_result = python_builtin_import(name, globals, locals, fromlist, level)
172
173 is_root_import = thread_local._nest_level == 1
/databricks/python/lib/python3.9/site-packages/mlflow_databricks_artifacts/protos/patched_databricks_artifacts_pb2.py in <module>
22 DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\"patched_databricks_artifacts.proto\x12\x1bmlflow_databricks_artifacts\x1a\x15scalapb/scalapb.proto\x1a\x10\x64\x61tabricks.proto\"\x89\x02\n\x16\x41rtifactCredentialInfo\x12\x0e\n\x06run_id\x18\x01 \x01(\t\x12\x0c\n\x04path\x18\x02 \x01(\t\x12\x12\n\nsigned_uri\x18\x03 \x01(\t\x12O\n\x07headers\x18\x04 \x03(\x0b\x32>.mlflow_databricks_artifacts.ArtifactCredentialInfo.HttpHeader\x12\x41\n\x04type\x18\x05 \x01(\x0e\x32\x33.mlflow_databricks_artifacts.ArtifactCredentialType\x1a)\n\nHttpHeader\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t\"\xaa\x02\n\x15GetCredentialsForRead\x12\x14\n\x06run_id\x18\x01 \x01(\tB\x04\xf8\x86\x19\x01\x12\x0c\n\x04path\x18\x02 \x03(\t\x12\x12\n\npage_token\x18\x03 \x01(\t\x1ax\n\x08Response\x12M\n\x10\x63redential_infos\x18\x02 \x03(\x0b\x32\x33.mlflow_databricks_artifacts.ArtifactCredentialInfo\x12\x17\n\x0fnext_page_token\x18\x03 \x01(\tJ\x04\x08\x01\x10\x02:_\xe2?(\n&com.databricks.rpc.RPC[$this.Response]\xe2?1\n/com.databricks.mlflow.api.MlflowTrackingMessage\"\xab\x02\n\x16GetCredentialsForWrite\x12\x14\n\x06run_id\x18\x01 \x01(\tB\x04\xf8\x86\x19\x01\x12\x0c\n\x04path\x18\x02 \x03(\t\x12\x12\n\npage_token\x18\x03 \x01(\t\x1ax\n\x08Response\x12M\n\x10\x63redential_infos\x18\x02 \x03(\x0b\x32\x33.mlflow_databricks_artifacts.ArtifactCredentialInfo\x12\x17\n\x0fnext_page_token\x18\x03 \x01(\tJ\x04\x08\x01\x10\x02:_\xe2?(\n&com.databricks.rpc.RPC[$this.Response]\xe2?1\n/com.databricks.mlflow.api.MlflowTrackingMessage*s\n\x16\x41rtifactCredentialType\x12\x11\n\rAZURE_SAS_URI\x10\x01\x12\x15\n\x11\x41WS_PRESIGNED_URL\x10\x02\x12\x12\n\x0eGCP_SIGNED_URL\x10\x03\x12\x1b\n\x17\x41ZURE_ADLS_GEN2_SAS_URI\x10\x04\x32\xb8\x03\n DatabricksMlflowArtifactsService\x12\xc6\x01\n\x15getCredentialsForRead\x12\x32.mlflow_databricks_artifacts.GetCredentialsForRead\x1a;.mlflow_databricks_artifacts.GetCredentialsForRead.Response\"<\xf2\x86\x19\x38\n4\n\x04POST\x12&/mlflow/artifacts/credentials-for-read\x1a\x04\x08\x02\x10\x00\x10\x03\x12\xca\x01\n\x16getCredentialsForWrite\x12\x33.mlflow_databricks_artifacts.GetCredentialsForWrite\x1a<.mlflow_databricks_artifacts.GetCredentialsForWrite.Response\"=\xf2\x86\x19\x39\n5\n\x04POST\x12\'/mlflow/artifacts/credentials-for-write\x1a\x04\x08\x02\x10\x00\x10\x03\x42,\n\x1f\x63om.databricks.api.proto.mlflow\x90\x01\x01\xa0\x01\x01\xe2?\x02\x10\x01')
23
---> 24 _ARTIFACTCREDENTIALTYPE = DESCRIPTOR.enum_types_by_name['ArtifactCredentialType']
25 ArtifactCredentialType = enum_type_wrapper.EnumTypeWrapper(_ARTIFACTCREDENTIALTYPE)
26 AZURE_SAS_URI = 1
I originally thought the issue was in a dependency of some ML library I'm using and pip installed that library to a certain version, but I'm still running into this issue. I have been using the code (not shown) to train some ML models for the last few months but have been running into this error since the end of last week. My code hasn't changed within the last few months, so I'm sure it's something on the Databricks side. I tried to find this bug online but was unsuccessful. Any thoughts or fixes planned for the future?
