GitLab

* Add force_run_distributed tests.

* Added enable_eager

* r/force_run_distributed/force_v2_in_keras_compile

* Adding force_v2 tests and FLAGs.

* Rename method to avoid conflict.

* Add cpu force_v2 tests.

* fix lint, wrap line.

* change to force_v2_in_keras_compile

* Update method name.

* Lower mlperf target to 0.736.

* Record highest uncased bleu found.

* change to bleu_best_score_iteration

257314238  by hongkuny<hongkuny@google.com>:

    Creates transformer v2 README.
    Remove contents that are not implemented.

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PiperOrigin-RevId: 257314238

* reduce iterations from 20 to 12.

* add fp16 dynamic batch accuracy check.

* fix existing lint issue.

* Fix unit tests failures.

* 96% of TF 2.0 tests on GPU are passing.

* Currently all passing GPU and CPU TF 2.0

* Address code comments.

* use tf 2.0 cast.

* Comment about working on TF 2.0 CPU

* Uses contrib turn off for TF 2.0.

* Fix wide_deep and add keras_common_tests.

* use context to get num_gpus.

* Switch to tf.keras.metrics

* trying fake merge call

* make metrics optional

* Remove extra print

* Add XLA benchmark tests FP32 only for now.

* Add FP16 XLA tests.

* FP16 only tests.

* set default steps to 300K.

* Log flags to perfzero.

* Add XLA support to transformer

- Moved config logic to keras_utils
- Added enable_xla flag to _performance flags
- Did not refactor enable_xla flag from keras resnet due to
  reliance on calling FLAGs in estimator keras and that is
  a needed refactor for another time.

* fix g3 lint complaint.

* Refactor set config into keras_utils.

* Move flags out of main.

* pipe through enable_xla

* Update official/transformer/v2/misc.py
Co-Authored-By: Reed <reedwm@google.com>

252534787  by hongkuny<hongkuny@google.com>:

    Transformer vocab fix to strip correctly in py2

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PiperOrigin-RevId: 252534787

251762562  by hongkuny<hongkuny@google.com>:

    Fix blue score inconsistency

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PiperOrigin-RevId: 251762562

* Fix various lint errors

* Fix logging format

* Make max_length and static_batch configurable.

* Fix line length.

* Fix incorrect parameters in building eval input.

* Improve comments for readability.

* Add static batch benchmarks to estimator 

So we can distinguish how much static vs dynamic batch matter.

* change max_length for static_batch tests

* Add flag for max length

this is not going to help with current tf.data semantics. so removing it.