Major Features and Improvements

Generate statistics for sparse features.
Directly convert a batch of tf.Examples to Arrow tables. Avoids conversion of
tf.Example to intermediate Dict representation.

Bug Fixes and Other Changes

Generate statistics for the weight feature.
Support validation and schema inference from sliced statistics that include
the default slice (validation/inference will be done using the default slice
statistics).
Avoid flattening null arrays.
Set weighted_num_examples field in the statistics proto if a weight
feature is specified.
Replace DecodedExamplesToTable with a Python implementation.
Building TFDV from source does not need pyarrow anymore.
Depends on apache-beam[gcp]>=2.16,<3.
Depends on six>=1.12,<2.
Depends on scikit-learn>=0.18,<0.22.
Depends on tfx-bsl>=0.15,<0.16.
Depends on tensorflow-metadata>=0.15,<0.16.
Depends on tensorflow-transform>=0.15,<0.16.
Depends on tensorflow>=1.15,<3.
- Starting from 1.15, package
  tensorflow comes with GPU support. Users won't need to choose between
  tensorflow and tensorflow-gpu.
- Caveat: tensorflow 2.0.0 is an exception and does not have GPU
  support. If tensorflow-gpu 2.0.0 is installed before installing
  tensorflow-data-validation, it will be replaced with tensorflow 2.0.0.
  Re-install tensorflow-gpu 2.0.0 if needed.