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Reason: break 1-gpu nightly test.

This reverts commit 371645fc.

Don't pass `batch_size` to keras.layers.Input in DS multi-replica case. There is currently a bug in Keras side which will cause a batch size incompatible error.

* Update resnet_model.py

* Ensure static shapes when enabling XLA.

* Define `drop_remainder` as a variable.

* Handles per_replica_batch_size in non-XLA mode

* Remove trailing whitespace.

* Add tweaked test for fp16 nonXLA

* Add dummy test for dataset warmup

Co-authored-by: Jiri Simsa <jsimsa@google.com>

* Add tests for Resnet data input pipeline

* Added trivial model class to isolate data input pipeline tests

* Move distribution strategy creation before creating any ops, which is
required by multi-node collective ops in eager mode.

* Scale up learning rate according to num workers in ResNet50 w/
Estimator.

* Scale up LR in cifar.

* Fix a typo.

* Add num_workers to run param as well. Make num_worker optional in
params.

* initial commit

* bug fix

* Move build_stats from common to keras main, because it is only applicable in keras

* remove tailing blank line

* add test for synth data

* add kwargs to init

* add kwargs to function invokation

* correctly pass kwargs

* debug

* debug

* debug

* fix super init

* bug fix

* fix local_flags

* fix import

* bug fix

* fix log_steps flag

* bug fix

* bug fix: add missing return value

* resolve double-defined flags

* lint fix

* move log_steps flag to benchmarK flag

* fix lint

* lint fix

* lint fix

* try flag core default values

* bug fix

* bug fix

* bug fix

* debug

* debug

* remove debug prints

* rename benchmark methods

* flag bug fix for synth benchmark

* Initial commit

* Fininshed

* bug fix

* bug fix

* bug fix

* Resolve review comments

* Typo fix

* resolve comments

* fix number error

* Resolve comments

required by multi-node collective ops in eager mode.

* Add `input_context` to `input_fn` in cifar10_main.

* Change sharding log message to be consistent with `dataset.shard` params.

* Lint

* Shard input for distribution strategy.

* Pass in input_context from real input_fn.

* Pass in input_context from real input_fn.

* Make pipeline id base 1 for better readability.

* xla to bs=128 for num_gpu=8

* remove todo

* optimizer back to compat.v1

* add doc string to fix lint

* Adding LARS to ResNet

* Fixes for the LARS patch

* Fixes for the LARS patch

* more fixes

* 1 more fix

* s/CollectiveAllReduceStrategy/MultiWorkerMirroredStrategy

* More s/contrib.distribute/distribute.experimental

* Collective communication options in MultiWorkerMirroredStrategy.

* Minor fixes

* No checkpointing if multi worker.

* turn off checkpointing

* fix lint

* Mixed precision support

* Add TODOs

* fix resnet breakage and add keras end-to-end tests

* delint

* address PR comments

* tmp commit

* tmp commit

* first attempt (without eval)

* Bug fixes

* bug fixes

* training done

* Loss NAN, no eval

* Loss weight problem solved

* resolve the NAN loss problem

* Problem solved. Clean up needed

* Added a todo

* Remove debug prints

* Extract get_optimizer to ncf_common

* Move metrics computation back to neumf; use DS.scope api

* Extract DS.scope code to utils

* lint fixes

* Move obtaining DS above producer.start to avoid race condition

* move pt 1

* move pt 2

* Update the run script

* Wrap keras_model related code into functions

* Update the doc for softmax_logitfy and change the method name

* Resolve PR comments

* working version with: eager, DS, batch and no masks

* Remove git conflict indicator

* move reshape to neumf_model

* working version, not converge

* converged

* fix a test

* more lint fix

* more lint fix

* more lint fixes

* more lint fix

* Removed unused imports

* fix test

* dummy commit for kicking of checks

* fix lint issue

* dummy input to kick off checks

* dummy input to kick off checks

* add collective to dist strat

* addressed review comments

* add a doc string

* Added XLA test with a monkey-patched op to avoid OOM

* Added doc strings in Keras benchmarks to avoid Lint error

* Add benchmarks for thread tuning.

* Address comment/

* Add a comment.

Add root_data_dir to constructor of Resnet50KerasBenchmarkSynth and Resnet50KerasBenchmarkReal (#6259)

* Remove isintance change for contrib strategy

Replace it with class name check instead which should work regardless

* Add quotes for string

* fix quote type