TensorFlow Model Analysis 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