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CHANGELOG.md

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Changelog

Unreleased

Added

  • Add dataset MlflowMetricsDataSet for metrics logging (#9) and update documentation for metrics.

Fixed

  • Versioned datasets artifacts logging are handled correctly (#41)
  • MlflowDataSet handles correctly datasets which are inherited from AbstractDataSet (#45)
  • Change the test in _generate_kedro_command to accept both empty Iterables(default in CLI mode) and None values (default in interactive mode) (#50)
  • Force to close all mlflow runs when a pipeline fails. It prevents further execution of the pipeline to be logged within the same mlflow run_id as the failing pipeline. (#10)
  • Fix various documentation typos (#34, #35, #36 and more)

Changed

  • Remove conda_env and model_name arguments from MlflowPipelineHook and add them to PipelineML and pipeline_ml. This is necessary for incoming hook auto-discovery in future release and it enables having multiple PipelineML in the same project. #58
  • flatten_dict_params, recursive and sep arguments of the MlflowNodeHook are moved to the mlflow.yml config file to prepare plugin auto registration. This also modifies the run.py template (to remove the args) and the mlflow.yml keys to add a hooks entry. (#59)

0.2.1 - 2018-08-06

Added

Many documentation improvements:

  • Add a Code of conduct
  • Add a Contributing guide
  • Refactor README.md to separate clearly from documentation
  • Fix broken links
  • Fix bad markdown rendering
  • Split old README.md information in dedicated sections

Changed

  • Enable pipeline_ml to accept artifacts (encoder, binarizer...) to be "intermediary" outputs of the pipeline and not only "terminal" outputs (i.e. node outputs which are not re-used as another node input). This closes a bug discovered in a more general discussion in #16.
  • Only non-empty CLI arguments and options are logged as tags in MLflow (#32)

0.2.0 - 2020-07-18

Added

  • Bump the codebase test coverage to 100% to improve stability
  • Improve rendering of template with a trailing newline to make them black-valid
  • Add a PipelineML.extract_pipeline_artifacts methods to make artifacts retrieving easier for a given pipeline
  • Use an official kedro release (>0.16.0, <0.17.0) instead of the development branch

Changed

  • hooks, context and cli folders are moved to framework to fit kedro new folder architecture
  • Rename get_mlflow_conf in get_mlflow_config for consistency (with ConfigLoader, KedroMlflowConfig...)
  • Rename keys of KedroMlflowConfig.to_dict() to remove the "_opts" suffix for consistency with the KedroMlflowConfig.from_dict method

Fixed

  • Add debug folder to gitignore for to avoid involuntary data leakage
  • Remove the inadequate warning "You have not initialized your project yet" when calling kedro mlflow init
  • Remove useless check to see if the commands are called inside a Kedro project since the commands are dynamically displayed based on whether the call is made inside a kedro project or not
  • Fix typos in error messages
  • Fix hardcoded path to the run.py template
  • Make not implemented function raise a NotImplementError instead of failing silently
  • Fix wrong parsing when the mlflow_tracking_uri key of the mlflow.yml configuration file was an absolute local path
  • Remove unused KedroMlflowContextClass
  • Force the MlflowPipelineHook.before_pipeline_run method to set the mlflow_tracking_uri to the one from the configuration to enforce configuration file to be prevalent on environment variables or current active tracking uri in interactive mode
  • Fix wrong environment parsing case when passing a conda environment as a python dictionary in MlflowPipelineHook
  • Fix wrong artifact logging of MlflowDataSet when a run was already active and the save method was called in an interactive python session.
  • Force the user to declare an input_name for a PipelineMl object to fix difficult inference of what is the pipeline input
  • Update run.py template to fit kedro new one.
  • Force _generate_kedro_commands to separate an option and its arguments with a "=" sign for readibility

0.1.0 - 2020-04-18

Added

  • Add cli kedro mlflow init to udpdate the template and kedro mlflow ui to open mlflow user interface with your project configuration
  • Add hooks MlflowNodeHook and MlflowPipelineHook for parameters autologging and model autologging
  • Add MlflowDataSet for artifacts autologging
  • Add PipelineMl class and its pipeline_ml factory for pipeline packaging and service