Version 0.23.0

Major Features and Improvements

Added EstimatedProbabilityDensityColumn feature column.
Added tft.scale_to_gaussian to transform input to standard gaussian.
Vocabulary related analyzers and mappers now accept a file_format argument allowing the vocabulary to be saved in TFRecord format. The default format remains text (TFRecord format requires tensorflow>=2.4).

Enable SavedModelLoader to import and apply TF2 SavedModels.
tft.min, tft.max, tft.sum, tft.covariance and tft.pca now have default output values to properly process empty analysis datasets.
tft.scale_by_min_max, tft.scale_to_0_1 and the corresponding per-key versions now apply a sigmoid function to scale tensors if the analysis dataset is either empty or contains a single distinct value.
Added best-effort tf.text op registration when loading transformation graphs.
Vocabularies computed over numerical features will now assign values to entries with equal frequency in reverse lexicographical order as well, similarly to string features.
Fixed an issue that causes the TABLE_INITIALIZERS graph collection to contain a tensor instead of an op when a TF2 SavedModel or a TF2 Hub Module containing a table is loaded inside the preprocessing_fn.
Fixes an issue where the output tensors of tft.TransformFeaturesLayer would all have unknown shapes.
Stopped depending on avro-python3.
Depends on apache-beam[gcp]>=2.23,<3.
Depends on tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,<2.4.
Depends on tensorflow-metadata>=0.23,<0.24.
Depends on tfx-bsl>=0.23,<0.24.