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RELEASE.md

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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.

Release 0.1.10

Major Features and Improvements

  • Add json-example serving input functions to TF.Transform.
  • Add variance analyzer to tf.transform.

Bug Fixes and Other Changes

  • Remove duplication in output of tft.tfidf.
  • Ensure ngrams output dense_shape is greater than or equal to 0.
  • Alters the behavior and interface of tensorflow_transform.mappers.ngrams.
  • Depends on apache-beam[gcp]=>2,<3.
  • Making TF Parallelism runner-dependent.
  • Fixes issue with csv serving input function.
  • Various performance and stability improvements.

Deprecations

  • tft.map will be removed on version 0.2.0, see the examples directory for instructions on how to use tft.apply_function instead (as needed).
  • tft.tfidf_weights will be removed on version 0.2.0, use tft.tfidf instead.

Release 0.1.9

Major Features and Improvements

  • Refactor internals to remove Column and Statistic classes

Bug Fixes and Other Changes

  • Remove collections from graph to avoid warnings
  • Return float32 from tfidf_weights
  • Update tensorflow_transform to use tf.saved_model APIs.
  • Add default values on example proto coder.
  • Various performance and stability improvements.