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TensorFlow: Upstream changes to git.
Changes: - Docuementation changes. - Update URL for protobuf submodule. Base CL: 107345722
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‎.gitmodules

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[submodule "google/protobuf"]
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path = google/protobuf
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url = https://github.googlesource.com/google/protobuf.git
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url = https://github.com/google/protobuf.git

‎tensorflow/g3doc/api_docs/cc/index.md

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##Classes <a class="md-anchor" id="AUTOGENERATED-classes"></a>
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* [tensorflow::Env](ClassEnv.md)
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* [tensorflow::EnvWrapper](ClassEnvWrapper.md)
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* [tensorflow::RandomAccessFile](ClassRandomAccessFile.md)
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* [tensorflow::Session](ClassSession.md)
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* [tensorflow::Status](ClassStatus.md)
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* [tensorflow::Tensor](ClassTensor.md)
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* [tensorflow::TensorBuffer](ClassTensorBuffer.md)
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* [tensorflow::TensorShape](ClassTensorShape.md)
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* [tensorflow::TensorShapeIter](ClassTensorShapeIter.md)
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* [tensorflow::TensorShapeUtils](ClassTensorShapeUtils.md)
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* [tensorflow::Thread](ClassThread.md)
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* [tensorflow::WritableFile](ClassWritableFile.md)
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* [tensorflow::Env](../../api_docs/cc/ClassEnv.md)
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* [tensorflow::EnvWrapper](../../api_docs/cc/ClassEnvWrapper.md)
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* [tensorflow::RandomAccessFile](../../api_docs/cc/ClassRandomAccessFile.md)
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* [tensorflow::Session](../../api_docs/cc/ClassSession.md)
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* [tensorflow::Status](../../api_docs/cc/ClassStatus.md)
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* [tensorflow::Tensor](../../api_docs/cc/ClassTensor.md)
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* [tensorflow::TensorBuffer](../../api_docs/cc/ClassTensorBuffer.md)
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* [tensorflow::TensorShape](../../api_docs/cc/ClassTensorShape.md)
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* [tensorflow::TensorShapeIter](../../api_docs/cc/ClassTensorShapeIter.md)
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* [tensorflow::TensorShapeUtils](../../api_docs/cc/ClassTensorShapeUtils.md)
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* [tensorflow::Thread](../../api_docs/cc/ClassThread.md)
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* [tensorflow::WritableFile](../../api_docs/cc/ClassWritableFile.md)
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##Structs <a class="md-anchor" id="AUTOGENERATED-structs"></a>
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* [tensorflow::SessionOptions](StructSessionOptions.md)
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* [tensorflow::Status::State](StructState.md)
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* [tensorflow::TensorShapeDim](StructTensorShapeDim.md)
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* [tensorflow::ThreadOptions](StructThreadOptions.md)
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* [tensorflow::SessionOptions](../../api_docs/cc/StructSessionOptions.md)
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* [tensorflow::Status::State](../../api_docs/cc/StructState.md)
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* [tensorflow::TensorShapeDim](../../api_docs/cc/StructTensorShapeDim.md)
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* [tensorflow::ThreadOptions](../../api_docs/cc/StructThreadOptions.md)
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<div class='sections-order' style="display: none;">

‎tensorflow/g3doc/api_docs/python/index.md

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‎tensorflow/g3doc/extras/tensorflow-whitepaper2015.pdf

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‎tensorflow/g3doc/get_started/index.md

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TensorFlow features.
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## Recommended Next Steps: <a class="md-anchor" id="AUTOGENERATED-recommended-next-steps-"></a>
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* [Download and Setup](os_setup.md)
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* [Basic Usage](basic_usage.md)
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* [Download and Setup](../get_started/os_setup.md)
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* [Basic Usage](../get_started/basic_usage.md)
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* [TensorFlow Mechanics 101](../tutorials/mnist/tf/index.md)
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‎tensorflow/g3doc/how_tos/adding_an_op/index.md

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* [Verify it works](#AUTOGENERATED-verify-it-works)
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* [Validation](#Validation)
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* [Op registration](#AUTOGENERATED-op-registration)
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* [Attrs](#AUTOGENERATED-attrs)
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* [Attrs](#Attrs)
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* [Attr types](#AUTOGENERATED-attr-types)
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* [Polymorphism](#Polymorphism)
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* [Inputs and Outputs](#AUTOGENERATED-inputs-and-outputs)
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You define the interface of an Op by registering it with the TensorFlow system.
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In the registration, you specify the name of your Op, its inputs (types and
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names) and outputs (types and names), as well as [docstrings](#docstrings) and
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any [attrs](#attrs) the Op might require.
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names) and outputs (types and names), as well as docstrings and
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any [attrs](#Attrs) the Op might require.
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To see how this works, suppose you'd like to create an Op that takes a tensor of
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`int32`s and outputs a copy of the tensor, with all but the first element set to
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## Op registration <a class="md-anchor" id="AUTOGENERATED-op-registration"></a>
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### Attrs <a class="md-anchor" id="AUTOGENERATED-attrs"></a>
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### Attrs <a class="md-anchor" id="Attrs"></a>
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Ops can have attrs, whose values are set when the Op is added to a graph. These
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are used to configure the Op, and their values can be accessed both within the

‎tensorflow/g3doc/how_tos/graph_viz/index.md

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![Visualization of a TensorFlow graph](./graph_vis_animation.gif "Visualization of a TensorFlow graph")
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*Visualization of a TensorFlow graph.*
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To see your own graph, run TensorBoard pointing it to the log directory of the job, click on the graph tab on the top pane and select the appropriate run using the menu at the upper left corner. For in depth information on how to run TensorBoard and make sure you are logging all the necessary information, see [Summaries and TensorBoard](../summaries_and_tensorboard/index.md).
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To see your own graph, run TensorBoard pointing it to the log directory of the job, click on the graph tab on the top pane and select the appropriate run using the menu at the upper left corner. For in depth information on how to run TensorBoard and make sure you are logging all the necessary information, see [Summaries and TensorBoard](../../how_tos/summaries_and_tensorboard/index.md).
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## Name scoping and nodes <a class="md-anchor" id="AUTOGENERATED-name-scoping-and-nodes"></a>
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‎tensorflow/g3doc/how_tos/index.md

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TensorFlow Variables are in-memory buffers containing tensors. Learn how to
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use them to hold and update model parameters during training.
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[View Tutorial](variables/index.md)
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[View Tutorial](../how_tos/variables/index.md)
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## TensorFlow Mechanics 101 <a class="md-anchor" id="AUTOGENERATED-tensorflow-mechanics-101"></a>
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as how to add Summary ops to automatically output data to the Events files that
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[View Tutorial](summaries_and_tensorboard/index.md)
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[View Tutorial](../how_tos/summaries_and_tensorboard/index.md)
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## TensorBoard: Graph Visualization <a class="md-anchor" id="AUTOGENERATED-tensorboard--graph-visualization"></a>
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This tutorial describes how to use the graph visualizer in TensorBoard to help
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[View Tutorial](graph_viz/index.md)
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[View Tutorial](../how_tos/graph_viz/index.md)
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## Reading Data <a class="md-anchor" id="AUTOGENERATED-reading-data"></a>
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This tutorial describes the three main methods of getting data into your
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[View Tutorial](reading_data/index.md)
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[View Tutorial](../how_tos/reading_data/index.md)
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## Threading and Queues <a class="md-anchor" id="AUTOGENERATED-threading-and-queues"></a>
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This tutorial describes the various constructs implemented by TensorFlow
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[View Tutorial](threading_and_queues/index.md)
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[View Tutorial](../how_tos/threading_and_queues/index.md)
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## Adding a New Op <a class="md-anchor" id="AUTOGENERATED-adding-a-new-op"></a>
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TensorFlow already has a large suite of node operations from which you can
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[View Tutorial](../how_tos/adding_an_op/index.md)
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## Custom Data Readers <a class="md-anchor" id="AUTOGENERATED-custom-data-readers"></a>
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[View Tutorial](../how_tos/new_data_formats/index.md)
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## Using GPUs <a class="md-anchor" id="AUTOGENERATED-using-gpus"></a>
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[View Tutorial](../how_tos/using_gpu/index.md)
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## Sharing Variables <a class="md-anchor" id="AUTOGENERATED-sharing-variables"></a>
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[View Tutorial](../how_tos/variable_scope/index.md)
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<div class='sections-order' style="display: none;">
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<!--

‎tensorflow/g3doc/how_tos/new_data_formats/index.md

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Next you will create the actual Reader op. It will help if you are familiar
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with [the adding an op how-to](../adding_an_op/index.md). The main steps
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with [the adding an op how-to](../../how_tos/adding_an_op/index.md). The main steps
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* Registering the op.
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To define an `OpKernel`, Readers can use the shortcut of descending from
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so follow [the instructions to add an Op](../../how_tos/adding_an_op/index.md). You may
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‎tensorflow/g3doc/how_tos/reading_data/index.md

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[view your summaries as training progresses using TensorBoard](../../how_tos/summaries_and_tensorboard/index.md).
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#### Aside: How clean shut-down when limiting epochs works <a class="md-anchor" id="AUTOGENERATED-aside--how-clean-shut-down-when-limiting-epochs-works"></a>
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[the shared variables tutorial](../../how_tos/variable_scope/index.md).

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