GitLab

* 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

Remove the deprecated `scalar_summary` and use `summary.scalar` instead. 

The current program gets the following warning:
WARNING:tensorflow:
build_graph.: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.

Update tf.concat_v2 to tf.concat

Updated the cifar10 model to be compatible with the latest version of TensorFlow

Corrections and explanations for the updated Neural GPU model.

Update to the Neural GPU.

Changes to Resnet for TF 1.0 compatibility