Major Features and Improvements
* Large vocabularies are now computed faster due to partially parallelizing
`VocabularyOrderAndWrite`.
Bug Fixes and Other Changes
* Generic `tf.SparseTensor` input support has been added to
`tft.scale_to_0_1`, `tft.scale_to_z_score`, `tft.scale_by_min_max`,
`tft.min`, `tft.max`, `tft.mean`, `tft.var`, `tft.sum`, `tft.size` and
`tft.word_count`.
* Optimize SavedModel written out by `tf.Transform` when using native TF2 to
speed up loading it.
* Added `tft_beam.PTransformAnalyzer` as a base PTransform class for
`tft.ptransform_analyzer` users who wish to have access to a base temporary
directory.
* Fix an issue where >2D `SparseTensor`s may be incorrectly represented in
instance_dicts format.
* Added support for out-of-vocabulary keys for per_key mappers.
* Added `tft.get_num_buckets_for_transformed_feature` which provides the
number of buckets for a transformed feature if it is a direct output of
`tft.bucketize`, `tft.apply_buckets`, `tft.compute_and_apply_vocabulary` or
`tft.apply_vocabulary`.
* Depends on `apache-beam[gcp]>=2.28,<3`.
* Depends on `numpy>=1.16,<1.20`.
* Depends on `tensorflow-metadata>=0.28.0,<0.29.0`.
* Depends on `tfx-bsl>=0.28.1,<0.29.0`.
Breaking changes
* Autograph is disabled when the preprocessing fn is traced using tf.function
when `force_tf_compat_v1=False` and TF2 behavior is enabled.
Deprecations