GitLab

* Set the --clone_model_in_keras_dist_strat to None.  Remove the separate no_cloning benchmarks and add a couple of cloning ones.  Fixes the learning rate schedule to cache its ops per graph.

* Add benchmarks with the --cloning flag to Resnet and NFC.

* Renamed cloning to clone_model_in_keras_dist_strat. Dropped a few tests that aren't essential.

* Fixed up the formatting after re-naming the flag to a much longer  name.  Thanks, lint.
* Fixed the lint error in nfc_common.py

* add ds support for ncf

* remove comments for in_top_k

* avoid expanding the input layers

* resolve comments and fix lint

* Added some comments in code and fix lint

* fix lint

* add some documentation

* add tensorflow imports

* Added main function to the two keras resent benchmarks

* remove asserts

This is needed to avoid breaking benchmark execution if PerfZero provides more
Named arguments before  the benchmark class constructor is updated.

* Allow user to specify root_data_dir in the benchmark class constructor

* Address comments

* Add a flag to specify distribution strategies.

* Fix a small error.

* Address comments.

* Address comments.

* Fix typos.

* fix test benchmark_graph_1_gpu_no_dist_strat failing

- Failure only occurs when all 1_gpu tests are run
together with the error:
tensorflow.python.framework.errors_impl.NotFoundError:
Resource localhost/logdir:/tmp/cifar10_model/
N10tensorflow22SummaryWriterInterfaceE does not exist.
[Op:WriteScalarSummary] name: epoch_loss/

Another fix might be to generate a different model_dir
in the core code, but that has other draw backs such as
restarting from the checkpoint.

* Model_dir for all tests.

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

* Fix python style using pyformat

* 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.

* Change to gfile.Exists and deeper link to CIFAR-10

* fix lint and use tf.gfile

* Added pass/fail and eager tests

* Add eager multi-gpu test.

- kears_cifar_main returns dict of stats after run.
- unit tests added for keras_common.
- lint issues fixed in all 4 files.