Version 0.28.0

Major Features and Improvements

Large vocabularies are now computed faster due to partially parallelizing VocabularyOrderAndWrite.

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 SparseTensors 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.

Autograph is disabled when the preprocessing fn is traced using tf.function when force_tf_compat_v1=False and TF2 behavior is enabled.