GitLab

using existing flag --fp16_implementation in official/utils/flags/_performance.py to enable automatic mixed precision

Only the V1 resnet model uses --max_train_steps. This unexposes the flag in the keras_application_models, mnist, keras resnet, CTL resnet Models. Before this change, such models allowed the flag to be specified, but ignored it.

I also removed the "max_train" argument from the run_synthetic function, since this only had any meaning for the V1 resnet model. Instead, the V1 resnet model now directly passes --max_train_steps=1 to run_synthetic.

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Moving Keras ResNet models to `official/vision/image_classification` and benchmarks to `official/benchmark`.

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An earlier change made it so running this file would cause an error. The unit tests still passed, as the unit tests do not directly call the main() function

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Also add `worker_hosts` and `task_index` flags.  These flags enable running the
model over multiple hosts by passing the cluster information via command line.

Setting `TF_CONFIG` will continue to work.

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263011341  by hongkuny<hongkuny@google.com>:

    reduce batch size for bert squad v8 accuracy test

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262988559  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Enable NCF TF 2.0 model to run on TPUStrategy.

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262971756  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Internal change

262967691  by hongkuny<hongkuny@google.com>:

    Internal

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