MLflow 1.17.0 includes the following major features and improvements:
Features:
- Add support for hyperparameter-tuning models to mlflow.pyspark.ml.autolog() (#4270, @WeichenXu123)
Bug fixes and documentation updates:
- Fix PyTorch Lightning callback definition for compatibility with PyTorch Lightning 1.3.0 (#4333, @dbczumar)
- Fix a bug in scikit-learn autologging that omitted artifacts for unsupervised models (#4325, @dbczumar)
- Support logging datetime.date objects as part of model input examples (#4313, @vperiyasamy)
- Implement HTTP request retries in the MLflow Java client for 500-level responses (#4311, @dbczumar)
- Include a community code of conduct (#4310, @dennyglee)
Small bug fixes and doc updates (#4276, #4263, @WeichenXu123; #4289, #4302, #3599, #4287, #4284, #4265, #4266, #4275, #4268, @harupy; #4335, #4297, @dbczumar; #4324, #4320, @tleyden)