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* 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

Add LexNet noun compounds model to models repository.

Update running_pets instructions to link to running locally.

* 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)

Add benchmark utility functions for metric logging

samples/java: Link to Fiji/ImageJ integration.

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

Python3 compatibility for AstroNet

* use proper temp directory for end to end tests.

* add supers to tearDown

This reverts commit 6d829caa.

Make TFGAN tutorial Python 3 compatible. Fixes issue #3413

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. 

Add pkulzc to object_detection owners.

This is not a performance issue for the instances replaced because
each instance is expected to iterate over zipped lists of < ~20
references to numpy arrays.

PiperOrigin-RevId: 189060074

plot shown in vis_segmentation