Merge changes from github.

END_PUBLIC

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Commit cf375f067 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
Adds cudnn_rnn_ops_op_lib and cudnn_rnn_kernels to contrib_ops_op_lib and
contrib_kernels respectively.

PiperOrigin-RevId: 164170971

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Commit 95ec58e27 authored by Asim Shankar<ashankar@google.com>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
C API: Make TF_TensorFromTensor return an error instead of just logging it.

PiperOrigin-RevId: 164167582

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Commit 15175c870 authored by Jonathan Hseu<jhseu@google.com>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
Build fixes.

- Allow var_list as a positional argument in CrossShardOptimizer.
- Set the number of shards to 1 when not running on TPU, to allow evaluate() and predict() on CPU/GPU to work.

PiperOrigin-RevId: 164161640

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Commit bd3e894f7 authored by Yao Zhang<yaozhang@google.com>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
Support freeze mode for fused batch norm.

PiperOrigin-RevId: 164149032

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Commit e6b6b84c0 authored by Asim Shankar<ashankar@google.com>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
C API: TF_Tensors will always be in host memory.

This change undoes some experimentation in
commit 22651083406ca01ac9d481e3367a3510d25f88cd
and restores TF_Tensor behavior to what is was prior to that change.

PiperOrigin-RevId: 164146670

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Commit 8bf3f88f7 authored by Peter Hawkins<phawkins@google.com>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
[TF:XLA] Add _XLASend and _XLARecv TF ops that wrap the XLA Send/Recv HLO ops.

PiperOrigin-RevId: 164124764

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Commit 626d3200f authored by Peter Hawkins<phawkins@google.com>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
[XLA] Add test blacklist mechanism for XLA C++ unit tests.

PiperOrigin-RevId: 164124423

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Commit 359cc5f5e authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
Document dict ordering in nest and make it consistent with sonnet.

PiperOrigin-RevId: 164114335

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Commit 05813b531 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
Go: Update generated wrapper functions for TensorFlow ops.

PiperOrigin-RevId: 164089206

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Commit c451f465d authored by Anna R<annarev@google.com>
Committed by Benoit Steiner<benoitsteiner@users.noreply.github.com>:
BEGIN_PUBLIC
Automated g4 rollback of changelist 164078808

PiperOrigin-RevId: 164318935

2 files changed, 5 insertions, 5 deletions

diff --git a/tensorflow/examples/image_retraining/label_image.py b/tensorflow/examples/image_retraining/label_image.py
index ecfa672462..de2713fc10 100644
--- a/tensorflow/examples/image_retraining/label_image.py
+++ b/tensorflow/examples/image_retraining/label_image.py
@@ -99,7 +99,7 @@ def run_graph(image_data, labels, input_layer_name, output_layer_name,
               num_top_predictions):
   with tf.Session() as sess:
     # Feed the image_data as input to the graph.
-    #   predictions  will contain a two-dimensional array, where one
+    #   predictions will contain a two-dimensional array, where one
     #   dimension represents the input image count, and the other has
     #   predictions per class
     softmax_tensor = sess.graph.get_tensor_by_name(output_layer_name)
diff --git a/tensorflow/examples/image_retraining/retrain.py b/tensorflow/examples/image_retraining/retrain.py
index 2e2e578050..3549891461 100644
--- a/tensorflow/examples/image_retraining/retrain.py
+++ b/tensorflow/examples/image_retraining/retrain.py
@@ -293,7 +293,7 @@ def run_bottleneck_on_image(sess, image_data, image_data_tensor,
     sess: Current active TensorFlow Session.
     image_data: String of raw JPEG data.
     image_data_tensor: Input data layer in the graph.
-    decoded_image_tensor: Output of initial image resizing and  preprocessing.
+    decoded_image_tensor: Output of initial image resizing and preprocessing.
     resized_input_tensor: The input node of the recognition graph.
     bottleneck_tensor: Layer before the final softmax.
 
@@ -391,9 +391,9 @@ def get_or_create_bottleneck(sess, image_lists, label_name, index, image_dir,
     label_name: Label string we want to get an image for.
     index: Integer offset of the image we want. This will be modulo-ed by the
     available number of images for the label, so it can be arbitrarily large.
-    image_dir: Root folder string  of the subfolders containing the training
+    image_dir: Root folder string of the subfolders containing the training
     images.
-    category: Name string of which  set to pull images from - training, testing,
+    category: Name string of which set to pull images from - training, testing,
     or validation.
     bottleneck_dir: Folder string holding cached files of bottleneck values.
     jpeg_data_tensor: The tensor to feed loaded jpeg data into.
@@ -969,7 +969,7 @@ def main(_):
   # See https://github.com/tensorflow/tensorflow/issues/3047
   tf.logging.set_verbosity(tf.logging.INFO)
 
-  # Prepare necessary directories  that can be used during training
+  # Prepare necessary directories that can be used during training
   prepare_file_system()
 
   # Gather information about the model architecture we'll be using.