GitLab

* 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

* 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

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

In TensorFlow 1.7, the TPUClusterResolver and the TPU RunConfig are changed
to reduce the amount of boilerplate required.

Adding dockerfiles to generate official docker images that can used for running models in this repo on container based platforms (#3399)
Signed-off-by: Vishnu kannan <vishnuk@google.com>