Tensorflow Transform 0.3.0

Release 0.3.0

Major Features and Improvements

• Added hash_strings mapper.
• Write vocabularies as asset files instead of constants in the SavedModel.

Bug Fixes and Other Changes

• 'tft.tfidf' now adds 1 to idf values so that terms in every document in the
  corpus have a non-zero tfidf value.
• Performance and memory usage improvement when running with Beam runners that
  use multi-threaded workers.
• Performance optimizations in ExampleProtoCoder.
• Depends on apache-beam[gcp]>=2.1.1,<3.
• Depends on protobuf>=3.3.0<4.
• Depends on six>=1.9,<1.11.

Breaking changes

• Requires pre-installed TensorFlow >= 1.3.
• Removed tft.map use tft.apply_function instead (as needed).
• Removed tft.tfidf_weights use tft.tfidf instead.
• beam_metadata_io.WriteMetadata now requires a second pipeline argument
  (see examples).
• A Beam bug will now affect users who call AnalyzeAndTransformDataset in
  certain circumstances. Roughly speaking, if you call beam.Pipeline() at
  some point (as all our examples do) you will not experience this bug. The
  bug is characterized by an error similar to
  KeyError: (u'AnalyzeAndTransformDataset/AnalyzeDataset/ComputeTensorValues/Extract[Maximum:0]', None)
  This bug will be fixed in Beam 2.2.