PiperOrigin-RevId: 298520611

PiperOrigin-RevId: 297839074

has been added).

PiperOrigin-RevId: 286109114

PiperOrigin-RevId: 282695365

PiperOrigin-RevId: 277973281

PiperOrigin-RevId: 277793274

PiperOrigin-RevId: 274241934

PiperOrigin-RevId: 271873759

2nd half of rough replacement pass

fix dataset map functions

reduce bias in sample selection

cache pandas work on a daily basis

cleanup and fix batch check for multi gpu

multi device fix

fix treatment of eval data padding

print data producer

replace epoch overlap with padding and masking

move type and shape info into the producer class and update run.sh with larger batch size hyperparams

remove xla for multi GPU

more cleanup

remove model runner altogether

bug fixes

address subtle pipeline hang and improve producer __repr__

fix crash

fix assert

use popen_helper to create pools

add StreamingFilesDataset and abstract data storage to a separate class

bug fix

fix wait bug and add manual stack trace print

more bug fixes and refactor valid point mask to work with TPU sharding

misc bug fixes and adjust dtypes

address crash from decoding bools

fix remaining dtypes and change record writer pattern since it does not append

fix synthetic data

use TPUStrategy instead of TPUEstimator

minor tweaks around moving to TPUStrategy

cleanup some old code

delint and simplify permutation generation

remove low level tf layer definition, use single table with slice for keras, and misc fixes

missed minor point on removing tf layer definition

fix several bugs from recombinging layer definitions

delint and add docstrings

Update ncf_test.py. Section for identical inputs and different outputs was removed.

update data test to run against the new producer class

* first pass at __getattr__ abuse logger

* first pass at adding tags to NCF

* minor formatting updates

* fix tag name

* convert metrics to python floats

* getting closer...

* direct mlperf logs to a file

* small tweaks and add stitching

* update tags

* fix tag and add a sudo call

* tweak format of run.sh

* delint

* use distribution strategies for evaluation

* address PR comments

* delint and fix test

* adjust flag validation for xla

* add prefix to distinguish log stitching

* fix index bug

* fix clear cache for root user

* dockerize cache drop

* TIL some regex magic

* intermediate commit

* ncf now working

* reorder pipeline

* allow batched decode for file backed dataset

* fix bug

* more tweaks

* parallize false negative generation

* shared pool hack

* workers ignore sigint

* intermediate commit

* simplify buffer backed dataset creation to fixed length record approach only. (more cleanup needed)

* more tweaks

* simplify pipeline

* fix misplaced cleanup() calls. (validation works\!)

* more tweaks

* sixify memoryview usage

* more sixification

* fix bug

* add future imports

* break up training input pipeline

* more pipeline tuning

* first pass at moving negative generation to async

* refactor async pipeline to use files instead of ipc

* refactor async pipeline

* move expansion and concatenation from reduce worker to generation workers

* abandon complete async due to interactions with the tensorflow threadpool

* cleanup

* remove performance_comparison.py

* experiment with rough generator + interleave pipeline

* yet more pipeline tuning

* update on-the-fly pipeline

* refactor preprocessing, and move train generation behind a GRPC server

* fix leftover call

* intermediate commit

* intermediate commit

* fix index error in data pipeline, and add logging to train data server

* make sharding more robust to imbalance

* correctly sample with replacement

* file buffers are no longer needed for this branch

* tweak sampling methods

* add README for data pipeline

* fix eval sampling, and vectorize eval metrics

* add spillover and static training batch sizes

* clean up cruft from earlier iterations

* rough delint

* delint 2 / n

* add type annotations

* update run script

* make run.sh a bit nicer

* change embedding initializer to match reference

* rough pass at pure estimator model_fn

* impose static shape hack (revisit later)

* refinements

* fix dir error in run.sh

* add documentation

* add more docs and fix an assert

* old data test is no longer valid. Keeping it around as reference for the new one

* rough draft of data pipeline validation script

* don't rely on shuffle default

* tweaks and documentation

* add separate eval batch size for performance

* initial commit

* terrible hacking

* mini hacks

* missed a bug

* messing about trying to get TPU running

* TFRecords based TPU attempt

* bug fixes

* don't log remotely

* more bug fixes

* TPU tweaks and bug fixes

* more tweaks

* more adjustments

* rework model definition

* tweak data pipeline

* refactor async TFRecords generation

* temp commit to run.sh

* update log behavior

* fix logging bug

* add check for subprocess start to avoid cryptic hangs

* unify deserialize and make it TPU compliant

* delint

* remove gRPC pipeline code

* fix logging bug

* delint and remove old test files

* add unit tests for NCF pipeline

* delint

* clean up run.sh, and add run_tpu.sh

* forgot the most important line

* fix run.sh bugs

* yet more bash debugging

* small tweak to add keras summaries to model_fn

* Clean up sixification issues

* address PR comments

* delinting is never over

* begin branch

* finish download script

* rename download to dataset

* intermediate commit

* intermediate commit

* misc tweaks

* intermediate commit

* intermediate commit

* intermediate commit

* delint and update census test.

* add movie tests

* delint

* fix py2 issue

* address PR comments

* intermediate commit

* intermediate commit

* intermediate commit

* finish wide deep transition to vanilla movielens

* delint

* intermediate commit

* intermediate commit

* intermediate commit

* intermediate commit

* fix import

* add default ncf csv construction

* change default on download_if_missing

* shard and vectorize example serialization

* fix import

* update ncf data unittests

* delint

* delint

* more delinting

* fix wide-deep movielens serialization

* address PR comments

* add file_io tests

* investigate wide-deep test failure

* remove hard coded path and properly use flags.

* address file_io test PR comments

* missed a hash_bucked_size

* port changes from previous branch now that transformer util changes are in master

fix incorrect count

correct (hopefully) treatment of batch_size

set eval_metrics to a dummy function for now

add some comments

start bringing metrics to transformer TPU

resolve logits shape

metrics are now working except for tf.py_func metrics

increase batch_size for tpu, and create summary host call

fix host call

reduce tpu default batch size

further tune batch sizes

add minibatch loss to summary

handle case of single_iteration_train_steps > number points in an epoch

begin to incorporate hooks

add sleep workarounds

disable hooks altogether

generalize host call function and move to newly created tpu utils module

remove all traces of params as an object

switch from  to

address some PR comments, and change the number of data points.

minor tweaks

add tpu dry run for testing, and use matmul for TPU embedding

infeed/outfeed queue issue is fixed. Sleeps are no longer necessary

add some documentation.

cleanup and address PR comments

delint

add accelerator __init__

fix embedding

missed PR comment

address PR comments

fix validator bug

rewrite cloud storage validator, and add oauth dependency to requirements.txt

* delint

* Add boosted_trees to the official models

* Comments addressed from review, and a test added; using absl.flags instead of argparser.

* Used help_wrap. Also added instructions for inference.

* Add benchmark upload util to bigquery.

Also update the benchmark logger and bigquery schema for the
errors found during the integration test.

* Fix lint error.

* Update test to clear all the env vars during test.

This was causing error since the Kokoro test has TF_PKG=tf-nightly
injected during test.

* Update lintrc to ignore google related package.

* Another attempt to fix lint import error.

* Address the review comment.

* Fix lint error.

* Another fix for lint.

* Update test comment for env var clean up.

* add requirements.txt now that there are dependencies beyond tensorflow

* direct pip info to README