We are happy to announce the availability of MLflow 1.13.0!

In addition to bug and documentation fixes, MLflow 1.13.0 includes the following features and improvements:

New fluent APIs for logging in-memory objects as artifacts:

  • Add mlflow.log_text which logs text as an artifact (#3678, @harupy)
  • Add mlflow.log_dict which logs a dictionary as an artifact (#3685, @harupy)
  • Add mlflow.log_figure which logs a figure object as an artifact (#3707, @harupy)
  • Add mlflow.log_image which logs an image object as an artifact (#3728, @harupy)

UI updates / fixes:

  • Add model version link in compact experiment table view
  • Add logged/registered model links in experiment runs page view
  • Enhance artifact viewer for MLflow models
  • Model registry UI settings are now persisted across browser sessions
  • Add model version description field to model version table

(#3867, @smurching)

Autologging enhancements:

  • Improve robustness of autologging integrations to exceptions (#3682, #3815, dbczumar; #3860, @mohamad-arabi; #3854, #3855, #3861, @harupy)
  • Add disable configuration option for autologging (#3682, #3815, dbczumar; #3838, @mohamad-arabi; #3854, #3855, #3861, @harupy)
  • Add exclusive configuration option for autologging (#3851, @apurva-koti; #3869, @dbczumar)
  • Add log_models configuration option for autologging (#3663, @mohamad-arabi)
  • Set tags on autologged runs for easy identification (and add tags to start_run) (#3847, @dbczumar)

More features and improvements:

  • Allow Keras models to be saved with SavedModel format (#3552, @skylarbpayne)
  • Add support for statsmodels flavor (#3304, @olbapjose)
  • Add support for nested-run in mlflow R client (#3765, @yitao-li)
  • Deploying a model using mlflow.azureml.deploy now integrates better with the AzureML tracking/registry. (#3419, @trangevi)
  • Update schema enforcement to handle integers with missing values (#3798, @tomasatdatabricks)

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.