GitLab

* Update colab demo

* fix typo

* Small word tweak

* Few more tweaks

np.uint8 to np.int64 for detection class label index overflow when using OIDv4 labels

Added additional information on using the `SavedModel` for prediction purposes.

The evaluation crashes in python3 if iteritems() is used instead of items()

* Use tf.image.resize_with_crop_or_pad

* exp_per_second and hr_at_10

* TF cifar10 cnn tutorial: use tensorflow-datasets to load the data.

* Load cifar10 in memory.

* Fix imports

* More import fixes

* Remove contrib imports, or move them inline

* Use exposed API for FixedLenFeature

* Replace tf.logging with absl logging

* Change GFile to v2 APIs

* replace tf.logging with absl loggin in movielens

* Fixing an import bug

* Change gfile to v2 APIs in code

* Swap to keras optimizer v2

* Bug fix for optimizer

* Change tf.log to tf.keras.backend.log

* Change the loss function to keras loss

* convert another loss to keras loss

* Resolve comments and fix lint

* Add a doc string

* Fix existing tests and add new tests for DS

* Added tests for multi-replica

* Fix lint

* resolve comments

* make estimator run in tf2.0

* use compat v1 loss

* fix lint issue

* Internal change.

PiperOrigin-RevId: 185564155

* Fix small bug when reading DELF features when file is empty.
A new test is added that catches this bug.

PiperOrigin-RevId: 213839503

* Refactors DELF example code to expose a function to create a DELF feature extractor.

PiperOrigin-RevId: 241492615

* Merged commit includes the following changes:
244073180  by Andre Araujo:

    Internal change

--
243646498  by Andre Araujo:

    Detect and save bounding boxes for a list of images.
    A new proto is added, along with auxiliary read/write functions, and tests.

--

PiperOrigin-RevId: 244073180

* before moving test cases to the base class

* Added tests for keras cifar and keras imagenet

* fix cifar10_test

* add blank lines

* fix lint errors

* fix lint

* Resolve comments

* Modified two resnet keras tests

* Tests passed

* Remove keras_test_base

* Remove gpu from the no-dist tests

* Revert "Set input layer `batch_size` in multi-replica mode (#6578)"

This reverts commit f1a59682.

* Rename variables.

1. In python3, dict.iteritems() is gone, change it to dict.items(). And it also doesn't treat zip object as a list, so change zip to list type.
2. Add encoding flag with open function to make it more compatible for Windows/Linux system.
3. For newer tensorflow, it expected int64 without giving a dtype parameter to embedding layer. We give it float32 to solve it.

* Update resnet_run_loop.py

* Update resnet_run_loop.py

* Update resnet_run_loop.py

* Update resnet_run_loop.py

* Update resnet_run_loop.py

Dictionary's .iteritem() raises an error in Python3.
Replaced it with iteritem from six library.

* Update README.md

* Update README.md

* Update README.md

* Revert "Revert " Ensure static shapes when enabling XLA in Resnet Keras model (#6508)" (#6517)"

This reverts commit cc9eef76.

* Set `batch_size` to keras.Input in non-eager mode.

Eager mode currently has OOM problem.

* Add comments for enable_eager flag.

* Always set drop_remainder=True.

* Only set drop_remainder=True for XLA.

* Make BatchTimestamp object printable.

* Removing trailing whitespace.

* Make BatchTimestamp repr a string.

* Refactored ResNet code and added additional architectures.

* Added numerical layer names instead of alphabetical.

* Change dash to underscore.

* Corrected return statement.

* Use conv_strides argument.

* Set classes=10

* Use partial to reduce code duplication.

With trivial model, it improves the data input pipeline throughput from 12.5K to 15K on a DGX1 V100 machine.

* 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

* Add code backticks for the code to obtain TensorFlow version (line 31)

* Add code backticks for the code to obtain TensorFlow version

* Added main function to the two keras resent benchmarks

* remove asserts

Forgot to add the `dtype='fp16'` flag in previous CL...

* Add profiler callback for Keras models

* Update build stats to identify time callback by type

* Add warning message when both TensorBoard and profiler callbacks are used

* Add benchmarks for dynamic loss scaling.

I add one convergence benchmark and five performance benchmarks.

* Fix lint error

This should give better performance in tweaked benchmarks.