MLflow v1.13.1 Release Notes

Release Date: 2020-12-30 // about 3 years ago
  • ๐Ÿš€ MLflow 1.13.1 is a patch release containing bug fixes and small changes:

    • ๐Ÿ›  Fix bug causing Spark autologging to ignore configuration options specified by mlflow.autolog() (#3917, @dbczumar)
    • ๐Ÿ›  Fix bugs causing metrics to be dropped during TensorFlow autologging (#3913, #3914, @dbczumar)
    • ๐Ÿ›  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)
    • ๐Ÿ›  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)
    • ๐Ÿ›  Fix experiment view crash and artifact view inconsistency caused by artifact URIs with redundant slashes (#3928, @dbczumar)