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* Add golden test util to streamline symbolic and numerical comparison to reference graphs, and apply golden tests to ResNet.

update tests

use more concise logic for path property

delint

add some comments

delint

address PR comments

make resnet tests more concise, and supress warning test in py2

change resnet name template

more shuffling of data dirs

address PR comments and add tensorflow version info

Remove subTest due to py2

switch from tf.__version__ to tf.VERSION, and include tf.GIT_VERSION

supress lint error from json load unpack

* address PR comments

* address PR comments

* delint

PR #3460 renamed FLAGS.epochs_per_eval to flags.epochs_between_evals; it missed this one

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

* direct pip info to README

* Init test for logging benchmark run.

* Fix collect CPU info.

* Update max split for handling GPU information.

* Another fix for parse GPU info.

* Fix GPU and CPU info collector.

* Update logging function to be static.

* Remove the cifar10 logging and fix a lint error.

* Address the review comment.

* Fix lint error.

* Fix lint error for logger and logger_test.

* Another lint fix for the test.

* Simplify the CPU info logging.

We will start in a conserative way, and probably add more info in
future.

* Remove unused dependencies.

* Update reset model for benchmark logging.

To enable benchmark logging, just add "--hooks LoggingMetricHook"

* Benchmark logger fix for resnet.

1. Update default at_end to False for metric logger to avoid
checkpoint error.
2. Update resnet run to log final evaluation result.

* Update log output for final eval_result.

* Typo fix.

* Unset the default value for benchmark_log_dir.

Usually the benchmark should be logged to different directly for
each run. Having a default value will hide the choice from user.

* Bug fix for benchmark logger initialization.

* Fix lint error.

* Address the review comment.

1. Update the logger to cover evaluation result.
2. Move the flag to performance parser.

* Undo the change for arg_parser.

* move wide_deep parser

* move mnist parsers

* Add session hook for benchmark metric logging.

Current hook is very similar as the LoggingTensorHook. Some of the
function are directly copied since the original one was not
exposed for import. We should seek to eventually move this code to
core when it is mature enough.

* Update metric_hook to use LoggingTensorHook as base.

The existing hook is similar enough to LoggingTensorHook, and
we should eliminate duplicate as much as possible.

* Address review comment.

1. Update global step tensor handle.
2. Update tests.
3. Update document.

* Update tests for py3.

* Fix lint error

* 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

Set correct number of train_epochs for resnet on imagenet, and fix help interception caused by moving arg parsing into main functions for resnet. (#3653)

* Glint everything

* Adding rcfile and pylinting

* Extra newline

* Few last lints

Use util functions hooks_helper and parser in mnist and wide_deep, and rename epochs_between_eval (from epochs_per_eval) (#3650)

1. Update logger to convert the value type to float to please JSON.
2. Update logger test to call parent test tearDown.

* 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. 

* 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

* Removing dependency on tf.test

* New lines

1. Added Tensorflow version information.
2. Added environment variables.
3. Fix typo for hyperparameters.
4. Added cloud related information.

restore --version flag in resnet parser

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

The current schema contains the entity information about model
and train data metadata, as well as machine config. Future change
will contain benchmark metric.

The json schema can be used to create bigquery table. A sample
table can be found in
https://bigquery.cloud.google.com/table/tf-benchmark-dashboard:test_benchmark.benchmark_run.

* Adding logging utils

* restore utils

* delete old file

* update inputs and docstrings

* Update import and fix typos

* Fix formatting and comments

* Update tests

* Remove cd and checkout

* Updating comment