GitLab

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

* Fix python style using pyformat

* Fix the turn_off_ds flag problem

* add param names to all args

* 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.

Failed test is python2  and was a kokoro failure

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

* fix method name

* Update doc strings.

* Fixe gpu number.

* 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.

Explicitly allow for script execution from any directory.  Make env vars visible in python script. (#6105)

* Update README.md

1. Clarify instructions to avoid friction. https://github.com/tensorflow/tensorflow/issues/24136
2. If trying to run in Colab experienced issue entering Python path. https://medium.com/@cwcgchello/how-to-set-pythonpath-in-colab-bf8c239c7c29

* Update README.md

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

* fix lint and use tf.gfile

It currently fails with
TypeError: not all arguments converted during string formatting

* Added pass/fail and eager tests

* Add eager multi-gpu test.

* Single timestamp list and return average_exp_per_second.

* Add paren to subtract before division.

* Add timestamp history for each batch in training

* Resolve github comments

* Change the batch start recording logic

* Lint fix

* Add imagenet end-to-end accuracy test.

* Comment why ['foo']

* remove development test example.

* Add end-to-end tests for Estimator.

* comment from keras to estimator.

* remove trailing new line

* Set use_bias=False for conv layers in Keras ResNet model

* Removed bias regularizer from Conv2D layers (which should have no effect after bias is removed)

* Setting default data format based on available devices.

* Handle data format in Keras ResNet model properly for better performance on GPU; Compile only the training graph when skip_eval flag is True

* Added data format fix to Keras Cifar model; Removed unnecessary import

* Add a comment to the skip_eval flag per Priya's request

This reverts commit 63f5827d.