GitLab

* 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>

* first version of ctl

* fix indent

* remove monkey patching for core

* add dtype arg

* fix dtype arg

* add logging lib

* remove compat.v1.logging

* add datetime import

* fix FLAGS import

* add constant vals

* move to using as tf import

* move to using as tf import

* remove steps per epoch = 1

* test train and test for one step

* test train and test for one step

* test train and test for one step

* test train and test for the entire dataset

* use an iterator for test

* pass tensors instead of an iterator

* add stats dict

* fix list declaration

* fix list declaration

* fix elapsed time calc

* print lr at epoch boundary alone

* Use regular tf import instead of compat

* remove tensorboard chkpts

* add correct logging import

* add correct logging import

* add benchmark configs

* add tests and configs

* add tests and configs

* add keras flags import

* add keras flags import

* fix eval ds creation cond

* return numpy value of train_loss

* return numpy value of loss and acc values

* add option for full eager mode

* fix lint errors

* add ctl flags

* add ctl import

* add the xla flag

* enable v2 behavior in unit tests

* rename dataset var

* add synthetic dataset without monkey patching

* add ctl local constants

* add ctl local constants

* change to using v2 imports

* change to using v2 imports

* change to using v2 imports

* change to using keras synthetic input fn

* remove enable_eager flag from benchmarks

* remove enable_eager flag from benchmarks

* remove enable_eager flag from benchmarks

* add option for no distrat

* add lambda for flags

* remove no_func benchmarks due to OOM error

* remove README

* remove unused comments

* remove unchanged file

* remove unchanged file

* remove unused drop_remainder_arg

* use keras.common lr function

* address PR comments

* remove reference to deleted file

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* fix lint errors

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* add flags info

* first version of ctl

* fix indent

* remove monkey patching for core

* add dtype arg

* fix dtype arg

* add logging lib

* remove compat.v1.logging

* add datetime import

* fix FLAGS import

* add constant vals

* move to using as tf import

* move to using as tf import

* remove steps per epoch = 1

* test train and test for one step

* test train and test for one step

* test train and test for one step

* test train and test for the entire dataset

* use an iterator for test

* pass tensors instead of an iterator

* add stats dict

* fix list declaration

* fix list declaration

* fix elapsed time calc

* print lr at epoch boundary alone

* Use regular tf import instead of compat

* remove tensorboard chkpts

* add correct logging import

* add correct logging import

* add benchmark configs

* add tests and configs

* add tests and configs

* add keras flags import

* add keras flags import

* fix eval ds creation cond

* return numpy value of train_loss

* return numpy value of loss and acc values

* add option for full eager mode

* fix lint errors

* add ctl flags

* add ctl import

* add the xla flag

* enable v2 behavior in unit tests

* rename dataset var

* add synthetic dataset without monkey patching

* add ctl local constants

* add ctl local constants

* change to using v2 imports

* change to using v2 imports

* change to using v2 imports

* change to using keras synthetic input fn

* remove enable_eager flag from benchmarks

* remove enable_eager flag from benchmarks

* remove enable_eager flag from benchmarks

* add option for no distrat

* add lambda for flags

* remove no_func benchmarks due to OOM error

* remove README

* remove unused comments

* remove unchanged file

* remove unchanged file

* remove unused drop_remainder_arg

* use keras.common lr function

* address PR comments

* remove reference to deleted file

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* fix lint errors

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253850824  by hongkuny<hongkuny@google.com>:

    Improve bert training utils.

--
253818191  by hongkuny<hongkuny@google.com>:

    Update savedmodel export to use new model.save() api.

--

PiperOrigin-RevId: 253850824

* adding a new perf test for ncf, and changing some names

* Added change to make ncf use the data from the gcp bucket, and removed the need to re-download data >1day old. Reorganized the perf-zero tests

253636854  by dmchen<dmchen@google.com>:

    Run only training in BERT SQuAD performance test

--
253118910  by hongkuny<hongkuny@google.com>:

    Internal change

PiperOrigin-RevId: 253636854

* tf.compat.v1.train.experimental.enable_mixed_precision_graph_rewrite

* Remove num_parallel_batches which is not used.

* layout off for some tests and channels last.

* 8 gpu tests channels_last

* more layout off tests.

* Add 1 gpu force_eager benchmark

* Add accuracy for no dist strat eager

* remvove return.

* Merged commit includes the following changes:
253126424  by Andre Araujo:

    Scripts to compute metrics for Google Landmarks dataset.

    Also, a small fix to metric in retrieval case: avoids duplicate predicted images.

--
253118971  by Andre Araujo:

    Metrics for Google Landmarks dataset.

--
253106953  by Andre Araujo:

    Library to read files from Google Landmarks challenges.

--
250700636  by Andre Araujo:

    Handle case of aggregation extraction with empty set of input features.

--
250516819  by Andre Araujo:

    Add minimum size for DELF extractor.

--
250435822  by Andre Araujo:

    Add max_image_size/min_image_size for open-source DELF proto / module.

--
250414606  by Andre Araujo:

    Refactor extract_aggregation to allow reuse with different datasets.

--
250356863  by Andre Araujo:

    Remove unnecessary cmd_args variable from boxes_and_features_extraction.

--
249783379  by Andre Araujo:

    Create directory for writing mapping file if it does not exist.

--
249581591  by Andre Araujo:

    Refactor scripts to extract boxes and features from images in Revisited datasets.
    Also, change tf.logging.info --> print for easier logging in open source code.

--
249511821  by Andre Araujo:

    Small change to function for file/directory handling.

--
249289499  by Andre Araujo:

    Internal change.

--

PiperOrigin-RevId: 253126424

* Updating DELF init to adjust to latest changes

* Editing init files for python packages

* Edit D2R dataset reader to work with py3.

PiperOrigin-RevId: 253135576

* DELF package: fix import ordering

* move step and epoch counts after super init call

* move comment block

* move super to the top

253113801  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Internal change

252697519  by dmchen<dmchen@google.com>:

    BERT SQuAD accuracy test

--
252663512  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Internal change

--
252647871  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Enable multi worker TPU training for BERT pretraining.

--

PiperOrigin-RevId: 253113801

* Moved VGGish code into its own directory.

* Moved most of old README.md into vggish/README.md.

Add rachellj218 to official/ owner
Add saberkun and hongjunCHoi to official/bert/ owner

252697519 by dmchen<dmchen@google.com>:

        BERT SQuAD accuracy test

25266352 by hongjunchoi<hongjunchoi@google.com>:

        Internal change

252647871 by hongjunchoi<hongjunchoi@google.com>:

        Enable multi worker TPU training for BERT pretraining.

252534787  by hongkuny<hongkuny@google.com>:

    Transformer vocab fix to strip correctly in py2

--

PiperOrigin-RevId: 252534787

252522861  by hongkuny<hongkuny@google.com>:

    Remove export using trained model due to implementation error

--
252156812  by yuefengz<yuefengz@google.com>:

    Fix the callback method name in BERT: replaced on_batch_start with on_batch_begin. Without the fix, it won't work with Keras callbacks.

--
251782065  by A. Unique TensorFlower<gardener@tensorflow.org>:

    Internal change

PiperOrigin-RevId: 252522861

Before, there was a global default loss scale for all models. Currently, only resnet uses loss scaling, but this will be useful once more models support it.

251762562  by hongkuny<hongkuny@google.com>:

    Fix blue score inconsistency

--

PiperOrigin-RevId: 251762562

* Modify tweaked tests for better performance in no cloning mode

* Tweak trivial models