GitLab

261171038  by gjn<gjn@google.com>:

    Remove weight_decay_rate 0 early exit check

    Removing this code path should be fine since this was actually not doing
    what it meant to do. Since weight_decay_rate is actually a tensor, the
    equality check was only looking at the id of the object and comparing to
    0. This should never be true. Evaluating a tensor is also not what we
    want to do at this point of the code. Thus it should be fine to simply
    remove this code.

--
261169862  by haoyuzhang<haoyuzhang@google.com>:

    Internal change

261153520  by haoyuzhang<haoyuzhang@google.com>:

    Internal change

261140302  by hongkuny<hongkuny@google.com>:

    Clean up

--

PiperOrigin-RevId: 261171038

* 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.

--

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>

* 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.

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

* Fixes that make transformer run.

* Remove debug print statements.

* Changed the permissions to 644.

* Fix the rest of the permissions.

* enable static batch in all benchmarks

* Restrict dist strat hack to training mode

For now we will do predict/eval without dist strat, so remove that hack in non training cases.

* Use `inputs` instead of `x` as arg name for call

Keras has different behavior based on whether the inputs are called `inputs` or not. Using `inputs` gives expected behaviors.

* Avoid extra map fn on input in dist strat case

* Update how we handle custom metrics

This new approach works with and without dist strat. The previous one didn't work with dist strat. We need to fix that but this is reasonable in meantime (b/133724664).

* Update benchmarks

* typo in metrics code

* Revert metrics change

Didn't actually work in distributed case..

This shuffling should help in getting shuffling each epoch.