GitLab

* Add resnet56 short tests. (#6101)

* Add resnet56 short tests.
- created base benchmark module
- renamed accuracy test class to contain the word Accuracy
which will result in a need to update all the jobs
and a loss of history but is worth it.
- short tests are mostly copied from shining with oss refactor

* Address feedback.

* Move flag_methods to init
- Address setting default flags repeatedly.

* Rename accuracy tests.

* Lint errors resolved.

* fix model_dir set to flags.data_dir.

* fixed not fulling pulling out flag_methods.

* Use core mirrored strategy in official models (#6126)

* Imagenet short tests (#6132)

* Add short imagenet tests (taken from seemuch)
- also rename to match go forward naming

* fix method name

* Update doc strings.

* Fixe gpu number.

* points default data_dir to child folder. (#6131)

Failed test is python2  and was a kokoro failure

* Imagenet short tests (#6136)

* Add short imagenet tests (taken from seemuch)
- also rename to match go forward naming

* fix method name

* Update doc strings.

* Fixe gpu number.

* Add fill_objects

* fixed calling wrong class in super.

* fix lint issue.

* Flag (#6121)

* Fix the turn_off_ds flag problem

* add param names to all args

* Export benchmark stats using tf.test.Benchmark.report_benchmark() (#6103)

* Export benchmark stats using tf.test.Benchmark.report_benchmark()

* Fix python style using pyformat

* Typos. (#6120)

* log verbosity=2 logs every epoch no progress bars (#6142)

* tf_upgrade_v2 on resnet and utils folder.

* tf_upgrade_v2 on resnet and utils folder.

* Add 5 epoch warmup

* get_lr with warm_up only for imagenet

* Add base_lr, remove fp16 unittest arg validation

* Remove validation check stopping v1 and FP16

* warm start a resent with all but the dense layer and only update the final layer weights when fine tuning

* Update README for Transfer Learning

* make lint happy and variable naming error related to scaled gradients

* edit the test cases for cifar10 and imagenet to reflect the default case of no fine tuning

* Remove one hot labels, Add drop_remainder to batch, Use parallel interleve in imagenet dataset.

* minor lint fix

* Don't try to read the files twice...

* Add explanation for cycle_length

* forbid resnet v1 fp16

* address PR comments

* rename --version flag and fix tests to correctly specify version rather than verbosity

* rename version to resnet_version throughout

* fix bugs

* delint

* missed layer_test

* fix indent

* Revert 823da318. This restores distribution strategies for resnet.

This commit is not a direct revert due to significant merge conflict
resolution.

* fix flags test

* npc is no longer used in resnet

* fix treatment of main() and absl flags

* add mnist_eager, and delint

* add mnist_eager docstring

* squash of modular absl usage commits

* delint

* address PR comments

* change hooks to comma separated list, as absl behavior for space separated lists is not as expected

This reverts commit 32aa6563.

* begin transfer from contrib fork

more changes to resnet_run_loop

use AUTOTUNE in prefetch

first pass at resnet with functional distribution strategies

fix syntax error

delint

aesthetic tweaks

delint and fix typos

rip multi_gpu flag out of resnet entirely. Subject to saved model load verification

update cifar10 and imagenet tests to reflect that the model function no longer need to know about multi_gpu

fix imagenet test

start addressing PR comments

more PR response work

* misc tweaks

* add a comment

* final pr tweaks

* fix parsers

* Add fp16 support to resnet.

* address PR comments

* add dtype checking to model definition

* delint

* more PR comments

* few more tweaks

* update resnet checkpoints

* Glint everything

* Adding rcfile and pylinting

* Extra newline

* Few last lints

* use proper temp directory for end to end tests.

* add supers to tearDown

This commit adds a basic end to end test for resnet cifar10 and imagenet models to check for syntax errors outside of the core neural net code. 

* Adding logging utils

* restore utils

* delete old file

* update inputs and docstrings

* make /official a python module

* remove /utils directory

* Update readme for python path setting

* Change readme texts

* Adding option to run with synthetic data.

* Adding option to run with synthetic data.

Adding option to run with synthetic data.

Adding option to run with synthetic data.

Debugging

Debugging

Debugging

Removing dataset

Removing dataset

Updating comments

Updating tests

Updating tests

Clarifying name of fn

Tests

* Copy pasta

* Using dataset as recommended by mrry

* Updating tests to use datasets

* Refactor and use class-based model for Resnet

* Linting

* Cleanup

* Cleanup in lieu of MNIST changes

* Moving params to init function

* Making learning_rate function

* Testing remotely...

* Testing remotely...

* Testing remotely...

* Testing remotely...

* Testing remotely...

* Respond to CR pt 1

* Respond to CR pt 2

* Respond to CR pt 3

* Respond to CR pt 4

* Adding batch norm vars in

* Exclude batch norm vars as the default

* Fixing CIFAR-10 naming

* Adding multi-GPU code

* Git rewind

* Git add file

* Manual revert

* Fixing tests

* Allowing input thread specification

* Adding comments

* Allowing input thread specification

* Merging resnet files

* Merging resnet files

* Refactoring input methods to allow for Reed's improvements

* Adding comments

* Changing arg name

* Removing contrib shuffle_and_repeat

* Removing contrib shuffle_and_repeat

* Removing contrib shuffle_and_repeat

* Debugging

* Removing with dependency on update_op

* Updating comments.

* Returning dataset directly

* Adding newline

* Adding num_gpus flag

* Refining preprocessing, part 1

* Refinements to preprocessing resulting from multi-GPU tests

* Reviving one-hot labels

* Reviving one-hot labels

* Fixing label shapes

* Removing epoch leftovers

* Adding random flip back in

* Reverting unnecessary linting of test file

* Respond to CR

* Respond to CR

* Respond to CR

* Remove conversion to float

* Remove conversion to float- comment

* Making means full-scale

* Pulling data.take under multi_gpu flag

* Pulling data.take under multi_gpu flag- Cifar

* Pulling data.take under multi_gpu flag- Cifar

* Removing num_gpus

* Removing num_gpus

* Refactoring input function

* Updating name of variable