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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

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

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

Modify compression tools to be Python3 compatible.

Update inception model based on tf API changes

Fix regressions caused by a previous change

Update inception model based on tf API changes: replace tf.op_scope with tf.name_scope and tf.variable_op_scope with tf.variable_scope; fix the order of arguments for tf.concat; replace tf.mul with tf.multiply.

Force new instance creation in MultiRNNCell (See also CL 145094809)

update another initializer change

update the initializer changes from december

slim: Typos at datasets/flowers.py

Update README.md

tf.contrib.deprecated elimination bugfix for tf version 12

Update the embedding README to be compatible with Mac

* Update resnet to run with tf r0.12 API.
1. tf.image.per_image_whitening -> tf.image.per_image_standardization
2. Use tf.summary to replace tf.image_summary, tf.scalar_summary, tf.merge_all_summaries.

* remove log