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* Fix resnet missing layers.

The official v1 model contains BN and Relu between input layer and
pooling.

* Remove the BN and Relu for V2.

After some discussion with team and refer to existing
implementation, those two layer seems to be only useful in V1.
In V2, the first unit of the block will have a projection, that
apply the BN and Relu for the shortcut. Adding a comment to make
this clear.

* Expand the comment section.

* Remove the pre-trained checkpoint since its broken right now.

Will restore it once we have new checkpoint generated.

The final BN and ReLU layer is only need for v2 model since it was
doing preactivation in each block.

* 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

Refer to commit "use reduce_mean instead of Average Pooling"(d5663b3c), "second_pool_size" and "second_pool_stride" no longer needed in resnet_model

* Add fp16 support to resnet.

* address PR comments

* add dtype checking to model definition

* delint

* more PR comments

* few more tweaks

* update resnet checkpoints

* Try out affine layer instead of dense

* Use reduce mean instead of avg pooling

* Remove np

* Use reduce mean instead of avg pooling

* Fix axes

* Cleanup

* Fixing comment

* Fixing tests

* Glint everything

* Adding rcfile and pylinting

* Extra newline

* Few last lints

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. 

* Update resnet with logging utils

* intermediate commit

* commit before rebase from master

* Add tests of ExamplePerSecondHook

* Done with test

* Fix a style nit

* Fix a style nit

restore --version flag in resnet parser

Create groups of arg parsers and convert the official resnet model to
the new arg parsers.

* 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

Revert "Support to set inter_op_parallelism_threads and intra_op_parallelism_threads for ResNet (#3502)" (#3518)

This reverts commit ce445976.

* Adding support to set inter_op_parallelism_threads and intra_op_parallelism_threads for official/resnet

* Addressing review comments

* 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