TensorFlow: Upstream latest changes to Git.

Changes:
- Updates to installation instructions.
- Updates to documentation.
- Minor modifications and tests for word2vec.

Base CL: 107284192

README.md

@@ -11,7 +11,66 @@ organization for the purposes of conducting machine learning and deep neural
 networks research.  The system is general enough to be applicable in a wide
 variety of other domains, as well.
 
+# Download and Setup
+
+For detailed installation instructions, see
+[here](g3doc/get_started/os_setup.md).
+
+## Binary Installation
+
+### Ubuntu/Linux
+
+Make sure you have [pip](https://pypi.python.org/pypi/pip) installed:
+
+```sh
+$ sudo apt-get install python-pip
+```
+
+Install TensorFlow:
+
+```sh
+# For CPU-only version
+$ sudo pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl
+
+# For GPU-enabled version
+$ sudo pip install https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl
+```
+
+### Mac OS X
+
+Make sure you have [pip](https://pypi.python.org/pypi/pip) installed:
+
+If using `easy_install`:
+
+```sh
+$ sudo easy_install pip
+```
+
+Install TensorFlow (only CPU binary version is currently available).
+
+```sh
+$ sudo pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl
+```
+
+### Try your first TensorFlow program
+
+```sh
+$ python
+
+>>> import tensorflow as tf
+>>> hello = tf.constant('Hello, TensorFlow!')
+>>> sess = tf.Session()
+>>> print sess.run(hello)
+Hello, TensorFlow!
+>>> a = tf.constant(10)
+>>> b = tf.constant(32)
+>>> print sess.run(a+b)
+42
+>>>
+
+```
+
+
 ##For more information
 
-* [Installation and setup instructions](/tensorflow/g3doc/get_started/os_setup.md)
 * [TensorFlow website](http://tensorflow.org)

tensorflow/core/framework/tensor.proto

@@ -10,7 +10,7 @@ import "tensorflow/core/framework/types.proto";
 message TensorProto {
   DataType dtype = 1;
 
-  // Shape of the tensor.  TODO(mdevin): sort out the 0-rank issues.
+  // Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
   TensorShapeProto tensor_shape = 2;
 
   // Only one of the representations below is set, one of "tensor_contents" and

tensorflow/core/kernels/softmax_op.h

@@ -46,7 +46,7 @@ struct SoftmaxEigenImpl {
     Eigen::IndexList<Eigen::type2index<1>, int> one_by_class;
     one_by_class.set(1, num_classes);
 #endif
-    // NOTE(mdevin): If you modify this implementation please run
+    // NOTE(touts): If you modify this implementation please run
     // the ImageNetSoftmaxFwd benchmark in core_ops_test.cc.
     //
     // softmax = exp(logits - max(logits along classes));

tensorflow/core/kernels/xent_op.h

@@ -35,7 +35,7 @@ struct XentEigenImpl {
                       typename TTypes<T>::Matrix scratch,
                       typename TTypes<T>::Vec loss,
                       typename TTypes<T>::Matrix backprop) {
-    // NOTE(mdevin): This duplicates some of the computations in softmax_op
+    // NOTE(touts): This duplicates some of the computations in softmax_op
     // because we need the intermediate (logits -max(logits)) values to
     // avoid a log(exp()) in the computation of the loss.
 

tensorflow/core/lib/histogram/histogram.h

@@ -97,7 +97,7 @@ class ThreadSafeHistogram {
 
   void Clear();
 
-  // TODO(mdevin): It might be a good idea to provide a AddN(<many values>)
+  // TODO(touts): It might be a good idea to provide a AddN(<many values>)
   // method to avoid grabbing/releasing the lock when adding many values.
   void Add(double value);
 

tensorflow/core/public/tensor_shape.h

@@ -63,7 +63,7 @@ class TensorShape {
 
   /// \brief Returns the number of elements in dimension "d".
   /// REQUIRES: "0 <= d < dims()"
-  // TODO(mdevin): Rename to dimension() to match Eigen::Tensor::dimension()?
+  // TODO(touts): Rename to dimension() to match Eigen::Tensor::dimension()?
   int64 dim_size(int d) const {
     DCHECK_GE(d, 0);
     DCHECK_LT(d, dims());

tensorflow/core/util/event.proto

@@ -12,7 +12,7 @@ message Event {
   // Timestamp of the event.
   double wall_time = 1;
 
-  // Globale step of the event.
+  // Global step of the event.
   int64 step = 2;
 
   oneof what {

tensorflow/examples/android/README.md

@@ -20,7 +20,6 @@ installed the NDK and SDK. Otherwise an error such as:
 "The external label '//external:android/sdk' is not bound to anything" will
 be reported.
 
-
 To build the APK, run this from your workspace root:
 ```
 bazel build //tensorflow/examples/android:tensorflow_demo -c opt --copt=-mfpu=neon
@@ -29,11 +28,19 @@ Note that "-c opt" is currently required; if not set, an assert (for an
 otherwise non-problematic issue) in Eigen will halt the application during
 execution. This issue will be corrected in an upcoming release.
 
-If adb debugging is enabled on your device, you may instead use the following
-command from your workspace root to automatically build and install:
+If adb debugging is enabled on your Android 5.0 or later device, you may then
+use the following command from your workspace root to install the APK once
+built:
+'''
+adb install -r -g bazel-bin/tensorflow/examples/android/tensorflow_demo_incremental.apk
+'''
+
+Alternatively, a streamlined means of building, installing and running in one
+command is:
 ```
-bazel mobile-install //tensorflow/examples/android:tensorflow_demo -c opt --copt=-mfpu=neon
+bazel mobile-install //tensorflow/examples/android:tensorflow_demo -c opt --start_app --copt=-mfpu=neon
 ```
 
-Add the "--start_app" flag if you wish to automatically start the app after
-installing. Otherwise, find the application icon labeled "Tensorflow Demo".
+If camera permission errors are encountered (possible on Android Marshmallow or
+above), then the adb install command above should be used instead, as it
+automatically grants the required camera permissions with '-g'.

tensorflow/g3doc/api_docs/index.md

@@ -9,7 +9,7 @@ Over time, we hope that the TensorFlow community will develop front ends for
 languages like Go, Java, Javascript, Lua R, and perhaps others. With SWIG, it's
 relatively easy to contribute a TensorFlow interface to your favorite language.
 
-Note: Many practical aspects of ssage are covered in the Mechanics tab, and
+Note: Many practical aspects of usage are covered in the Mechanics tab, and
 some additional documentation not specific to any particular language API is
 available in the Resources tab.
 

tensorflow/g3doc/api_docs/python/array_ops.md

@@ -1,6 +1,10 @@
 <!-- This file is machine generated: DO NOT EDIT! -->
 
 # Tensor Transformations
+
+Note: Functions taking `Tensor` arguments can also take anything
+accepted by [`tf.convert_to_tensor`](framework.md#convert_to_tensor).
+
 <!-- TOC-BEGIN This section is generated by neural network: DO NOT EDIT! -->
 ## Contents
 * [Casting](#AUTOGENERATED-casting)

tensorflow/g3doc/api_docs/python/client.md

@@ -299,7 +299,8 @@ The operation that failed, if known.
 or `Recv` op, there will be no corresponding
 [`Operation`](framework.md#Operation) object.  In that case, this
 will return `None`, and you should instead use the
-[`node_def`](OpError.node_def) to discover information about the op.
+[`OpError.node_def`](#OpError.node_def) to discover information about the
+op.
 
 ##### Returns:
 
@@ -536,7 +537,7 @@ The operation was aborted, typically due to a concurrent action.
 
 For example, running a [`queue.enqueue()`](io_ops.md#QueueBase.enqueue)
 operation may raise `AbortedError` if a
-[`queue.close()`](io_ops.md@QueueBase.close) operation previously ran.
+[`queue.close()`](io_ops.md#QueueBase.close) operation previously ran.
 
 - - -
 

tensorflow/g3doc/api_docs/python/constant_op.md

@@ -1,6 +1,10 @@
 <!-- This file is machine generated: DO NOT EDIT! -->
 
 # Constants, Sequences, and Random Values
+
+Note: Functions taking `Tensor` arguments can also take anything
+accepted by [`tf.convert_to_tensor`](framework.md#convert_to_tensor).
+
 <!-- TOC-BEGIN This section is generated by neural network: DO NOT EDIT! -->
 ## Contents
 * [Constant Value Tensors](#AUTOGENERATED-constant-value-tensors)

tensorflow/g3doc/api_docs/python/control_flow_ops.md

@@ -1,6 +1,10 @@
 <!-- This file is machine generated: DO NOT EDIT! -->
 
 # Control Flow
+
+Note: Functions taking `Tensor` arguments can also take anything
+accepted by [`tf.convert_to_tensor`](framework.md#convert_to_tensor).
+
 <!-- TOC-BEGIN This section is generated by neural network: DO NOT EDIT! -->
 ## Contents
 * [Control Flow Operations](#AUTOGENERATED-control-flow-operations)

tensorflow/g3doc/api_docs/python/framework.md

@@ -33,7 +33,7 @@
 
 <!-- TOC-END This section was generated by neural network, THANKS FOR READING! -->
 
-Import names from the framework library.
+Classes and functions for building TensorFlow graphs.
 
 ## Core graph data structures <div class="md-anchor" id="AUTOGENERATED-core-graph-data-structures">{#AUTOGENERATED-core-graph-data-structures}</div>
 
@@ -126,6 +126,10 @@ with tf.Graph().as_default() as g:
 
 Returns a serialized `GraphDef` representation of this graph.
 
+The serialized `GraphDef` can be imported into another `Graph`
+(using [`import_graph_def()`](#import_graph_def)) or used with the
+[C++ Session API](../cc/index.md).
+
 This method is thread-safe.
 
 ##### Args:
@@ -137,8 +141,7 @@ This method is thread-safe.
 
 ##### Returns:
 
-  A
-  [`GraphDef`](https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/graph.proto)
+  A [`GraphDef`](https://tensorflow.googlesource.com/tensorflow/+/master/tensorflow/core/framework/graph.proto)
   protocol buffer.
 
 

tensorflow/g3doc/api_docs/python/image.md

@@ -1,32 +1,36 @@
 <!-- This file is machine generated: DO NOT EDIT! -->
 
 # Images
+
+Note: Functions taking `Tensor` arguments can also take anything
+accepted by [`tf.convert_to_tensor`](framework.md#convert_to_tensor).
+
 <!-- TOC-BEGIN This section is generated by neural network: DO NOT EDIT! -->
 ## Contents
-* [Encoding and Decoding.](#AUTOGENERATED-encoding-and-decoding.)
+* [Encoding and Decoding](#AUTOGENERATED-encoding-and-decoding)
   * [tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, name=None)](#decode_jpeg)
   * [tf.image.encode_jpeg(image, format=None, quality=None, progressive=None, optimize_size=None, chroma_downsampling=None, density_unit=None, x_density=None, y_density=None, xmp_metadata=None, name=None)](#encode_jpeg)
   * [tf.image.decode_png(contents, channels=None, name=None)](#decode_png)
   * [tf.image.encode_png(image, compression=None, name=None)](#encode_png)
-* [Resizing.](#AUTOGENERATED-resizing.)
+* [Resizing](#AUTOGENERATED-resizing)
   * [tf.image.resize_images(images, new_height, new_width, method=0)](#resize_images)
   * [tf.image.resize_area(images, size, name=None)](#resize_area)
   * [tf.image.resize_bicubic(images, size, name=None)](#resize_bicubic)
   * [tf.image.resize_bilinear(images, size, name=None)](#resize_bilinear)
   * [tf.image.resize_nearest_neighbor(images, size, name=None)](#resize_nearest_neighbor)
-* [Cropping.](#AUTOGENERATED-cropping.)
+* [Cropping](#AUTOGENERATED-cropping)
   * [tf.image.resize_image_with_crop_or_pad(image, target_height, target_width)](#resize_image_with_crop_or_pad)
   * [tf.image.pad_to_bounding_box(image, offset_height, offset_width, target_height, target_width)](#pad_to_bounding_box)
   * [tf.image.crop_to_bounding_box(image, offset_height, offset_width, target_height, target_width)](#crop_to_bounding_box)
   * [tf.image.random_crop(image, size, seed=None, name=None)](#random_crop)
   * [tf.image.extract_glimpse(input, size, offsets, centered=None, normalized=None, uniform_noise=None, name=None)](#extract_glimpse)
-* [Flipping and Transposing.](#AUTOGENERATED-flipping-and-transposing.)
+* [Flipping and Transposing](#AUTOGENERATED-flipping-and-transposing)
   * [tf.image.flip_up_down(image)](#flip_up_down)
   * [tf.image.random_flip_up_down(image, seed=None)](#random_flip_up_down)
   * [tf.image.flip_left_right(image)](#flip_left_right)
   * [tf.image.random_flip_left_right(image, seed=None)](#random_flip_left_right)
   * [tf.image.transpose_image(image)](#transpose_image)
-* [Image Adjustments.](#AUTOGENERATED-image-adjustments.)
+* [Image Adjustments](#AUTOGENERATED-image-adjustments)
   * [tf.image.adjust_brightness(image, delta, min_value=None, max_value=None)](#adjust_brightness)
   * [tf.image.random_brightness(image, max_delta, seed=None)](#random_brightness)
   * [tf.image.adjust_contrast(images, contrast_factor, min_value=None, max_value=None)](#adjust_contrast)
@@ -36,7 +40,7 @@
 
 <!-- TOC-END This section was generated by neural network, THANKS FOR READING! -->
 
-## Encoding and Decoding. <div class="md-anchor" id="AUTOGENERATED-encoding-and-decoding.">{#AUTOGENERATED-encoding-and-decoding.}</div>
+## Encoding and Decoding <div class="md-anchor" id="AUTOGENERATED-encoding-and-decoding">{#AUTOGENERATED-encoding-and-decoding}</div>
 
 TensorFlow provides Ops to decode and encode JPEG and PNG formats.  Encoded
 images are represented by scalar string Tensors, decoded images by 3-D uint8
@@ -211,7 +215,7 @@ the smallest output, but is slower.
 
 
 
-## Resizing. <div class="md-anchor" id="AUTOGENERATED-resizing.">{#AUTOGENERATED-resizing.}</div>
+## Resizing <div class="md-anchor" id="AUTOGENERATED-resizing">{#AUTOGENERATED-resizing}</div>
 
 The resizing Ops accept input images as tensors of several types.  They always
 output resized images as float32 tensors.
@@ -376,7 +380,7 @@ Input images can be of different types but output images are always float.
 
 
 
-## Cropping. <div class="md-anchor" id="AUTOGENERATED-cropping.">{#AUTOGENERATED-cropping.}</div>
+## Cropping <div class="md-anchor" id="AUTOGENERATED-cropping">{#AUTOGENERATED-cropping}</div>
 
 - - -
 
@@ -555,7 +559,7 @@ The argument `normalized` and `centered` controls how the windows are built:
 
 
 
-## Flipping and Transposing. <div class="md-anchor" id="AUTOGENERATED-flipping-and-transposing.">{#AUTOGENERATED-flipping-and-transposing.}</div>
+## Flipping and Transposing <div class="md-anchor" id="AUTOGENERATED-flipping-and-transposing">{#AUTOGENERATED-flipping-and-transposing}</div>
 
 - - -
 
@@ -687,7 +691,7 @@ See also `transpose()`.
 
 
 
-## Image Adjustments. <div class="md-anchor" id="AUTOGENERATED-image-adjustments.">{#AUTOGENERATED-image-adjustments.}</div>
+## Image Adjustments <div class="md-anchor" id="AUTOGENERATED-image-adjustments">{#AUTOGENERATED-image-adjustments}</div>
 
 TensorFlow provides functions to adjust images in various ways: brightness,
 contrast, hue, and saturation.  Each adjustment can be done with predefined