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--auto_config flag to use automatic training configuration values (e.g. optimizer, learning rate, batch size). For compatible models, the automatic values aim to deliver solid performance out of the box.
Include all tokenization assets in exported models
Fixes and improvements
Fix type error during evaluation and inference of FP16 Transformer models
Update the model serving example to use a real pretrained model with the TensorFlow Serving 1.11 GPU Docker image
Small training speed improvement when the optimizer implements sparse updates
Revise some default configuration values:
change bucket_width default value to 1 (from 5)
change inference batch_size default value to 16 (from 1)