1.3.0

• support tf.estimator.train_and_evaluate() API
• use local file instead of ppid to uniquely identify executors
• surface GPU allocation errors more readily
• add sharding, epochs, and shuffling to mnist Dataset example.
• TFoS example for criteo data (contributed by @amantrac)
• use tf.train.MonitoredTrainingSession in mnist/spark example (contributed by @wuyifan18)

1.2.1

• Error handling for TF exceptions in InputMode.SPARK (from @eordentlich).
• Add timeout for reservations (from @eordentlich).
• Errors will exit Spark job with non-zero exit code.
• Fix regression in pipeline API.
• Model export tool

1.2.0

• Added Scala Inference API
• Support driver-side PS node(s) (contributed by @winston-zillow)