GitLab

Swivel: fastprep: Add protobuf 64MB limit warning

Update Swivel code to work with Python 3

Simplify and improve fastprep.mk

Fix the infinitite loop in reading files

Slim walkthough notebook update to show difference of inference for models with 1000 and 1001 classes. (#591)

* Example for VGG-19 inference was added to walkthough notebook. Example shows how to use networks that was trained using 1001 and 1000 classes.

* Small comment was added.

* changed VGG-19 to VGG-16

There is no need in building Tensorflow from scratch, fastprep successfully links with the Python wrapper from pip and system protobuf v3. Tested this on Ubuntu.

add learning to remember rare events

* Sync SyntaxNet with TensorFlow r1.0

* Fix typo back

* Fix Dockerfile to match TensorFlow 1.0

Update resnet model README, API calls, and evaluation code

Removed deprecated op

typo

Updated concat_v2 to concat for 1.0 compatibility

Fixed concat order using tf_upgrade.py

Fix division changing dtype to float in python3

Make slim a python package.

Updated deprecated tf.initialize_all_variables() with tf.global_varia…

Update swivel to TFr1.0

- TF1.0 has breaking changes for tf.concat
- Replace deprecated summary api
- Replace to be deprecated initialize_all_variables

Updated concat_v2 to concat for version 1.0 compatibility for breaking changes introduced in version 1.0
"tf.concat now takes arguments in reversed order and with different keywords. In particular we now match NumPy order as tf.concat(values, axis, name)"

Update concat_v2 to be concat to match 1.0 final

Fixes #1014

Fix bugs and API usage on cifar10 and cifar10_multi_gpu_train

Without the new variable_scope, creating apply_gradient_op raises
an error that additional moving average or slot variables could not
be created. This is because of the 'leaky reuse' of variable scope,
so we correct the problem by explicitly introducing a new variable scope.

Related issues: tensorflow/models#901, tensorflow/tensorflow#6220

Updated summaries in the tutorial models to 1.0