TensorFlow Model Analysis 0.24.0

Major Features and Improvements

• Use TFXIO and batched extractors by default in TFMA.

Bug fixes and other changes

• Updated the type hint of FilterOutSlices.
• Fix issue with precision@k and recall@k giving incorrect values when
  negative thresholds are used (i.e. keras defaults).
• Fix issue with MultiClassConfusionMatrixPlot being overridden by
  MultiClassConfusionMatrix metrics.
• Made the Fairness Indicators UI thresholds drop down list sorted.
• Fix the bug that Sort menu is not hidden when there is no model comparison.
• Depends on absl-py>=0.9,<0.11.
• Depends on ipython>=7,<8.
• Depends on pandas>=1.0,<2.
• Depends on protobuf>=3.9.2,<4.
• Depends on tensorflow-metadata>=0.24.0,<0.25.0.
• Depends on tfx-bsl>=0.24.0,<0.25.0.

Breaking changes

• Query based metrics evaluations that make use of MetricsSpecs.query_key
  are now passed tfma.Extracts with leaf values that are of type
  np.ndarray containing an additional dimension representing the values
  matched by the query (e.g. if the labels and predictions were previously 1D
  arrays, they will now be 2D arrays where the first dimension's size is equal
  to the number of examples matching the query key). Previously a list of
  tfma.Extracts was passed instead. This allows user's to now add custom
  metrics based on tf.keras.metrics.Metric as well as tf.metrics.Metric
  (any previous customizations based on tf.metrics.Metric will need to be
  updated). As part of this change the tfma.metrics.NDCG,
  tfma.metrics.MinValuePosition, and tfma.metrics.QueryStatistics have
  been updated.
• Renamed ConfusionMatrixMetric.compute to ConfusionMatrixMetric.result
  for consistency with other APIs.

Deprecations

• Deprecating Py3.5 support.