GitLab

257314238  by hongkuny<hongkuny@google.com>:

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

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PiperOrigin-RevId: 257314238

* Move to global_step.

* Hook to use global_step.

* fix comment start step 1 not step 0.

* remove hack used for testing.

* Add docstring.

* Update research/maskgan/README.md
Co-Authored-By: Andrew M Dai <andy.dai@gmail.com>

* Improve performance for Cifar ResNet benchmarks

* Revert batch size changes to benchmarks

Update to tf 1.14 syntax, fix bug #7125 (needed additional expand for conv2d).  Suppress compat warnings by moving to compat.v1 versions of some functions.  Note that this code is not 2.0 compatible yet - that will be a future push. (#7177)

* reduce iterations from 20 to 12.

* add fp16 dynamic batch accuracy check.

* fix existing lint issue.

* Bug fix of cifar10_eval.py

line 120: changed from eval_data = FLAGS.eval_data == 'test'
to: eval_data = FLAGS.eval_data
comment: the original code assigns 'true' to eval_data, when the script is being used to evaluate networks on the evaluation set, it DOES NOT load the evaluation set as intended, but actually loads the trainning set (line 105 of cifar10_input.py).

* Remove one line that was an artifact of 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

256204636  by hongkuny<hongkuny@google.com>:

    Internal

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256079834  by hongkuny<hongkuny@google.com>:

    Clean up: move common flags together for further refactoring
    Enable steps_per_loop option for all applications.

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PiperOrigin-RevId: 256204636

* Add StepCounterHook to hooks_helper.py

* Update symbol.

when there are multiple workers.

* borrowing a tf1.x optimization which converts gradients from sparse to dense for better perf

* cleanup after code review

* Merged commit includes the following changes:
255493073  by hongkuny<hongkuny@google.com>:

    BERT initial OSS readme update.

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255470372  by dmchen<dmchen@google.com>:

    Slightly expand expected range for F1 score in BERT SQuAD accuracy test

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255109240  by hongkuny<hongkuny@google.com>:

    Update eval/predict batch sizes.

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255010016  by hongkuny<hongkuny@google.com>:

    Internal

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254874613  by hongkuny<hongkuny@google.com>:

    Update glue tasks enum to match directory name

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254866171  by taylorrobie<taylorrobie@google.com>:

    Internal change

254785517  by zongweiz<zongweiz@google.com>:

    Use train_single_step for BERT GPU models to temporarily work around some performance bugs in GPU runs

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254497647  by hongkuny<hongkuny@google.com>:

    Fix device placement for TPU export model.

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PiperOrigin-RevId: 255493073

* Update README.md

255493073  by hongkuny<hongkuny@google.com>:

    BERT initial OSS readme update.

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255470372  by dmchen<dmchen@google.com>:

    Slightly expand expected range for F1 score in BERT SQuAD accuracy test

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255109240  by hongkuny<hongkuny@google.com>:

    Update eval/predict batch sizes.

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255010016  by hongkuny<hongkuny@google.com>:

    Internal

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PiperOrigin-RevId: 255493073

254874613  by hongkuny<hongkuny@google.com>:

    Update glue tasks enum to match directory name

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254866171  by taylorrobie<taylorrobie@google.com>:

    Internal change

PiperOrigin-RevId: 254874613

254785517  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Use train_single_step for BERT GPU models to temporarily work around some performance bugs in GPU runs

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254497647  by hongkuny<hongkuny@google.com>:

    Fix device placement for TPU export model.

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PiperOrigin-RevId: 254785517

* restored missing function

* missing import

* missing imports

* updated tutorial link

* recovered _print_download_progress func

* change default train with float16 instead of float32 accuracy

* test disable func call

* redundant function call, currently data is pulled automatically in

* optimized imports

* optimized imports

* trying fake merge call

* make metrics optional

* Remove extra print

* cpu benchmark and accuracy tests.

* add docstrings to fix lint.

* XLA FP32 and first test

* More XLA benchmarks FP32.

* Add eager to NCF and refactor resnet.

* fix v2_0 calls and more flag refactor.

* Remove extra flag args.

* 90 epoch default

* add return

* remove xla not used by estimator.

* Remove duplicate run_eagerly.

* fix flag defaults.

* Remove fp16_implementation flag option.

* Remove stop early on mlperf test.

* remove unneeded args.

* load flags from keras mains.

254134531  by yuefengz<yuefengz@google.com>:

    Fix a typo in bert_benchmark.py

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PiperOrigin-RevId: 254134531

* Do not set learning phase when skipping eval

* Do not set learning phase in no dist strat case

* Added device placement, tweaked benchmarks

* Added tweaked benchmarks for Cifar

* Fix device scope

* Fix lint

* Add explicit GPU placement flag

* Also run accuracy test with explicit GPU placement

* Added doc string

254069984  by hongkuny<hongkuny@google.com>:
    Automated rollback of changelist 254060732.

254061429  by hongkuny<hongkuny@google.com>:

    Use host while loop for training steps.

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254060732  by yifeif<yifeif@google.com>:
    Automated rollback of changelist 254027750.

254027750  by hongkuny<hongkuny@google.com>:

    Internal change

PiperOrigin-RevId: 254069984

* 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>