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RELEASE.md

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Version 0.26.0

Major Features and Improvements

  • Added support for aggregating feature attributions using special metrics that extend from tfma.metrics.AttributionMetric (e.g. tfma.metrics.TotalAttributions, tfma.metrics.TotalAbsoluteAttributions). To use make use of these metrics a custom extractor that add attributions to the tfma.Extracts under the key name tfma.ATTRIBUTIONS_KEY must be manually created.
  • Added support for feature transformations using TFT and other preprocessing functions.
  • Add support for rubber stamping (first run without a valid baseline model) when validating a model. The change threshold is ignored only when the model is rubber stamped, otherwise, an error is thrown.

Bug fixes and other changes

  • Fix the bug that Fairness Indicator UI metric list won't refresh if the input eval result changed.
  • Add support for missing_thresholds failure to validations result.
  • Updated to set min/max value for precision/recall plot to 0 and 1.
  • Fix issue with MinLabelPosition not being sorted by predictions.
  • Updated NDCG to ignore non-positive gains.
  • Fix bug where an example could be aggregated more than once in a single slice if the same slice key were generated from more than one SlicingSpec.
  • Add threshold support for confidence interval type metrics based on its unsampled_value.
  • Depends on apache-beam[gcp]>=2.25,!=2.26.*,<3.
  • Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.4.*,<3.
  • Depends on tensorflow-metadata>=0.26.0,<0.27.0.
  • Depends on tfx-bsl>=0.26.0,<0.27.0.

Breaking changes

  • Changed MultiClassConfusionMatrix threshold check to prediction > threshold instead of prediction >= threshold.
  • Changed default handling of materialize in default_extractors to False.
  • Separated tfma.extractors.BatchedInputExtractor into tfma.extractors.FeaturesExtractor, tfma.extractors.LabelsExtractor, and tfma.extractors.ExampleWeightsExtractor.

Deprecations

  • N/A