MLflow v1.13.1 Release Notes
Release Date: 2020-12-30 // about 3 years ago-
๐ MLflow 1.13.1 is a patch release containing bug fixes and small changes:
- ๐ Fix bug causing Spark autologging to ignore configuration options specified by
mlflow.autolog()
(#3917, @dbczumar) - ๐ Fix bugs causing metrics to be dropped during TensorFlow autologging (#3913, #3914, @dbczumar)
- ๐ Fix incorrect value of optimizer name parameter in autologging PyTorch Lightning (#3901, @harupy)
- Fix model registry database
allow_null_for_run_id
migration failure affecting MySQL databases (#3836, @t-henri) - Fix failure in
transition_model_version_stage
when uncanonical stage name is passed (#3929, @harupy) - ๐ Fix an undefined variable error causing AzureML model deployment to fail (#3922, @eedeleon)
- Reclassify scikit-learn as a pip dependency in MLflow Model conda environments (#3896, @harupy)
- ๐ Fix experiment view crash and artifact view inconsistency caused by artifact URIs with redundant slashes (#3928, @dbczumar)
- ๐ Fix bug causing Spark autologging to ignore configuration options specified by