GitLab

mobilenet_v1 train and eval script and quantization support.

Corrected number of shots in research/learning_to_remember_rare_events/train.py (method Trainer.run)

Fix extra -- when not using the bazel command line.

* ENH: Modified autoencoder to accept multilayer autoencoders

* ENH: Modified autoencoder to accept multilayer autoencoders

* Cleanup of commented code.

Delete "tutorials/rnn/translate" 

__rgb_resnet_v2_50_path__ is defined on line 28.

PiperOrigin-RevId: 186781401

Fix github issue #3269 where the accuracy is wrongly underestimated for binary classification and build issue #2784

Move gen_data and gen_vocab to parent directory to prevent import madness in the open-source code. Remove unnecessary bazel dependency and documentation in README.

PiperOrigin-RevId: 186638059

Fix license text

Seems like it was changed accidentally as it is different than any of the other files.

PiperOrigin-RevId: 186541910

Internal changes for object detection.

Fix PythonPath dependencies

PiperOrigin-RevId: 186265033

Merging in improvements and fixes to adversarial_text

Previously, code block one attempted to import `from object_detection.utils` before the `object_detection` directory was added to the PythonPath via `sys.path.append("..")`.

This generated a `ModuleNotFoundError`.

Accordingly, append `".."` to the PythonPath before attempting to import from `object_detection` as a module, instead of after.

PiperOrigin-RevId: 185783053

Replace tf.contrib.framework.get_or_create_global_step() with tf.train.get_or_create_global_step() in third_party/tensorflow_models

See https://www.tensorflow.org/api_docs/python/tf/contrib/framework/get_or_create_global_step and #2795

PiperOrigin-RevId: 176534973

PiperOrigin-RevId: 173414999

Add option for when there is only one label for classification, for speed. (The case for the standard datasets).

PiperOrigin-RevId: 172774825

PiperOrigin-RevId: 172665358

memory and fixes the OOM errors.

PiperOrigin-RevId: 172374935

Change logit and activation shapes to follow standard convention with batch size in the first dimension.

PiperOrigin-RevId: 172172495

PiperOrigin-RevId: 171498799

MNIST: Eager execution.