TFX 0.28.0

Major Features and Improvements

• Publically released TFX docker image in tensorflow/tfx will use GPU
  compatible based TensorFlow images from Deep Learning Containers. This allow
  these images to be used with GPU out of box.
• Added an example pipeline for a ranking model (using
  tensorflow_ranking)
  at tfx/examples/ranking. More documentation will be available in future
  releases.
• Added a spans_resolver
  that can resolve spans based on range_config.

Breaking Changes

For Pipeline Authors

• Custom arg key in google_cloud_ai_platform.tuner.executor is renamed to
  ai_platform_tuning_args from ai_platform_training_args, to better
  distinguish usage with Trainer.

For component authors

• N/A

Deprecations

• Deprecated input/output compatibility aliases for Transform and SchemaGen.

Bug Fixes and Other Changes

• Change Bigquery ML Pusher to publish the model to the user specified project
  instead of the default project from run time context.
• Depends on apache-beam[gcp]>=2.28,<3.
• Depends on ml-metadata>=0.28.0,<0.29.0.
• Depends on kfp-pipeline-spec>=0.1.6,<0.2.
• Depends on struct2tensor>=0.28.0,<0.29.0.
• Depends on tensorflow-data-validation>=0.28.0,<0.29.0.
• Depends on tensorflow-model-analysis>=0.28.0,<0.29.0.
• Depends on tensorflow-transform>=0.28.0,<0.29.0.
• Depends on tfx-bsl>=0.28.1,<0.29.0.

Documentation Updates

• Published a migration instruction
  for legacy custom launcher developers.