Merge changes from github.

Revert tensorflow#18413. Too many internal test failures due to the name scope change caused by this change. Revert tensorflow#18192. Cannot use re2::StringPiece internally. Need alternative for set call. Will pull and clean this up in a separate change. PiperOrigin-RevId: 197991247
ggkgg · May 25, 2018 · b59833c · b59833c
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diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -1,5 +1,16 @@
 # Contributing guidelines
 
+## Pull Request Checklist
+
+Before sending your pull requests, make sure you followed this list.
+
+- Read [contributing guidelines](CONTRIBUTING.md).
+- Read [Code of Conduct](CODE_OF_CONDUCT.md).
+- Ensure you have signed the [Contributor License Agreement (CLA)](https://cla.developers.google.com/).
+- Check if my changes are consistent with the [guidelines](https://github.com/tensorflow/tensorflow/blob/master/CONTRIBUTING.md#general-guidelines-and-philosophy-for-contribution).
+- Changes are consistent with the [Coding Style](https://github.com/tensorflow/tensorflow/blob/master/CONTRIBUTING.md#c-coding-style).
+- Run [Unit Tests](https://github.com/tensorflow/tensorflow/blob/master/CONTRIBUTING.md#running-unit-tests).
+
 ## How to become a contributor and submit your own code
 
 ### Contributor License Agreements

diff --git a/README.md b/README.md
@@ -5,9 +5,9 @@
 -----------------
 
 
-| **`Documentation`** | **`Linux CPU`** | **`Linux GPU`** | **`Mac OS CPU`** | **`Windows CPU`** | **`Android`** |
-|-----------------|---------------------|------------------|-------------------|---------------|---------------|
-| [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/api_docs/) | ![Build Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.png) | ![Build Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-gpu-cc.png) | ![Build Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/macos-py2-cc.png) | [![Build Status](https://ci.tensorflow.org/buildStatus/icon?job=tensorflow-master-win-cmake-py)](https://ci.tensorflow.org/job/tensorflow-master-win-cmake-py) | [![Build Status](https://ci.tensorflow.org/buildStatus/icon?job=tensorflow-master-android)](https://ci.tensorflow.org/job/tensorflow-master-android) [ ![Download](https://api.bintray.com/packages/google/tensorflow/tensorflow/images/download.svg) ](https://bintray.com/google/tensorflow/tensorflow/_latestVersion)
+| **`Documentation`** |
+|-----------------|
+| [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/api_docs/) |
 
 **TensorFlow** is an open source software library for numerical computation using
 data flow graphs.  The graph nodes represent mathematical operations, while
@@ -40,15 +40,6 @@ environment to install the nightly TensorFlow build. We support CPU and GPU
 packages on Linux, Mac, and Windows.
 
 
-**Individual whl files**
-* Linux CPU-only: [Python 2](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly-1.head-cp27-none-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=cpu-slave/)) / [Python 3.4](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly-1.head-cp34-cp34m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=cpu-slave/)) / [Python 3.5](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.5,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly-1.head-cp35-cp35m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.5,label=cpu-slave/)) / [Python 3.6](http://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.6,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly-1.head-cp36-cp36m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.6,label=cpu-slave/))
-* Linux GPU: [Python 2](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=gpu-linux/42/artifact/pip_test/whl/tf_nightly_gpu-1.head-cp27-none-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=gpu-linux/)) / [Python 3.4](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly_gpu-1.head-cp34-cp34m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=gpu-linux/)) / [Python 3.5](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.5,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly_gpu-1.head-cp35-cp35m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.5,label=gpu-linux/)) / [Python 3.6](http://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.6,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly_gpu-1.head-cp36-cp36m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-linux/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.6,label=gpu-linux/))
-* Mac CPU-only: [Python 2](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-mac/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=mac-slave/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly-1.head-py2-none-any.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-mac/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=mac-slave/)) / [Python 3](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-mac/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=mac-slave/lastSuccessfulBuild/artifact/pip_test/whl/tf_nightly-1.head-py3-none-any.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-mac/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=mac-slave/))
-* Windows CPU-only: [Python 3.5 64-bit](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-windows/M=windows,PY=35/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tf_nightly-1.head-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-windows/M=windows,PY=35/)) / [Python 3.6 64-bit](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-windows/M=windows,PY=36/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tf_nightly-1.head-cp36-cp36m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-windows/M=windows,PY=36/))
-* Windows GPU: [Python 3.5 64-bit](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-windows/M=windows-gpu,PY=35/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tf_nightly_gpu-1.head-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-windows/M=windows-gpu,PY=35/)) / [Python 3.6 64-bit](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-windows/M=windows-gpu,PY=36/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tf_nightly_gpu-1.head-cp36-cp36m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/tf-nightly/job/tf-nightly-windows/M=windows-gpu,PY=36/))
-* Android: [demo APK](https://ci.tensorflow.org/view/Nightly/job/nightly-android/lastSuccessfulBuild/artifact/out/tensorflow_demo.apk), [native libs](https://ci.tensorflow.org/view/Nightly/job/nightly-android/lastSuccessfulBuild/artifact/out/native/)
-([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-android/))
-
 #### *Try your first TensorFlow program*
 ```shell
 $ python
@@ -82,6 +73,30 @@ The TensorFlow project strives to abide by generally accepted best practices in
 
 [![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/1486/badge)](https://bestpractices.coreinfrastructure.org/projects/1486)
 
+
+## Continuous build status
+
+### Official Builds
+
+| Build Type      | Status | Artifacts |
+| ---             | ---    | ---       |
+| **Linux CPU**   | ![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.png) | [pypi](https://pypi.org/project/tf-nightly/) |
+| **Linux GPU**   | ![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-gpu-cc.png) | [pypi](https://pypi.org/project/tf-nightly-gpu/) |
+| **Linux XLA**   | TBA | TBA |
+| **MacOS**       | ![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/macos-py2-cc.png) | [pypi](https://pypi.org/project/tf-nightly/) |
+| **Windows CPU** | [![Status](https://ci.tensorflow.org/buildStatus/icon?job=tensorflow-master-win-cmake-py)](https://ci.tensorflow.org/job/tensorflow-master-win-cmake-py) | [pypi](https://pypi.org/project/tf-nightly/) |
+| **Windows GPU** | [![Status](http://ci.tensorflow.org/job/tf-master-win-gpu-cmake/badge/icon)](http://ci.tensorflow.org/job/tf-master-win-gpu-cmake/) | [pypi](https://pypi.org/project/tf-nightly-gpu/) |
+| **Android**     | [![Status](https://ci.tensorflow.org/buildStatus/icon?job=tensorflow-master-android)](https://ci.tensorflow.org/job/tensorflow-master-android) | [![Download](https://api.bintray.com/packages/google/tensorflow/tensorflow/images/download.svg)](https://bintray.com/google/tensorflow/tensorflow/_latestVersion) [demo APK](https://ci.tensorflow.org/view/Nightly/job/nightly-android/lastSuccessfulBuild/artifact/out/tensorflow_demo.apk), [native libs](https://ci.tensorflow.org/view/Nightly/job/nightly-android/lastSuccessfulBuild/artifact/out/native/) [build history](https://ci.tensorflow.org/view/Nightly/job/nightly-android/) |
+
+
+### Community Supported Builds
+
+| Build Type      | Status | Artifacts |
+| ---             | ---    | ---       |
+| **IBM s390x**       | [![Build Status](http://ibmz-ci.osuosl.org/job/TensorFlow_IBMZ_CI/badge/icon)](http://ibmz-ci.osuosl.org/job/TensorFlow_IBMZ_CI/) | TBA |
+| **IBM ppc64le CPU** | [![Build Status](http://powerci.osuosl.org/job/TensorFlow_Ubuntu_16.04_CPU/badge/icon)](http://powerci.osuosl.org/job/TensorFlow_Ubuntu_16.04_CPU/) | TBA |
+
+
 ## For more information
 
 * [TensorFlow Website](https://www.tensorflow.org)

diff --git a/RELEASE.md b/RELEASE.md
@@ -6,7 +6,7 @@
 * Added Gradient Boosted Trees as pre-made Estimators: BoostedTreesClassifier, BoostedTreesRegressor.
 * Add 3rd generation pipeline config for Cloud TPUs which improves performance and usability.
 * `tf.contrib.bayesflow` is moving out to it's own repo.
-* Added `tf.contrib.{proto,rpc}` to allow generic proto parsing and RPC communication.
+* Added `tf.contrib.{proto,rpc}` to allow generic proto parsing and RPC communication<sup>[1](#rpc-issue)</sup>.
 
 ## Bug Fixes and Other Changes
 * `tf.data`:
@@ -49,13 +49,14 @@
   * Fix non-uniformity of orthogonal matrices.
   * Fix bug where multi-image Estimator eval summaries were not displayed correctly.
 
+<a name="rpc-issue"><sup>1</sup></a> The cancellation logic of the RPC op contains a concurrency error. A fix has been submitted to master and will be part of the next release.
+
 ## Thanks to our Contributors
 
 This release contains contributions from many people at Google, as well as:
 
 4d55397500, Aghasy, Alan Du, Alan Lee, Alan Yee, Alex Wiltschko, Animesh Karnewar, Ankit Gupta, Anton Matosov, Aris L, Ben Barsdell, Brent Yi, Brett Koonce, Carl Thomé, cbockman, Chikanaga Tomoyuki, Chris Tava, CéDric Deltheil, Dahan Gong, Dalmo Cirne, Daniel Erenrich, David Norman, DavidNorman, Edd Wilder-James, Fanjin Zeng, Felix Abecassis, fo40225, George Sterpu, Giovanni Terlingen, Gor Baghdasaryan, Guillaume Klein, Hanchen Li, Ilya Polenov, Jakub Kolodziejczyk, Jason Sadler, Jayaram Bobba, Jerry Liu, jinghuangintel, Jiongyan Zhang (张炯衍), Joel Shor, Jong Wook Kim, Julian Eisenschlos, Karl Lessard, Krish Ravindranath, Loo Rong Jie, Lukas Geiger, Luke Iwanski, Mahmoud Abuzaina, ManHyuk, Marvin Richter, Maximilian Mitchell, Mohammad Ashraf Bhuiyan, msofka, Mustafa Kasap, Nathan Burnham, Nathan Luehr, Naveen Marri, ngc92, nio1814, Oleg Zabluda, Ou Changkun, Panos Ipeirotis, Paul Van Eck, Peter Lee, Piotr Czapla, qjivy, Rholais Lii, Rodrigo Formigone, Russell Klopfer, ryantimjohn, Sang Han, SebastiáN RamíRez, shengfuintel, Siby Jose Plathottam, Silver Chan, Stanislaw Antol, Taehoon Lee, Tarang Chugh, Ted Chang, Thomas Bastiani, Xian Xu, Xiaoming (Jason) Cui, Yan Facai (颜发才), yaox12, Yashal Shakti Kanungo, Yong Tang, Yuan (Terry) Tang, Yuxin Wu, Ziyue(Louis) Lu
 
-
 # Release 1.7.0
 
 ## Major Features And Improvements
@@ -235,7 +236,7 @@ Yoni Tsafir, yordun, Yuan (Terry) Tang, Yuxin Wu, zhengdi, Zhengsheng Wei, 田
   * Add `complex64` support to XLA compiler.
   * `bfloat` support is now added to XLA infrastructure.
   * Make `ClusterSpec` propagation work with XLA devices.
-  * Use a determinisitic executor to generate XLA graph.
+  * Use a deterministic executor to generate XLA graph.
 * `tf.contrib`:
   * `tf.contrib.distributions`:
     * Add `tf.contrib.distributions.Autoregressive`.

diff --git a/SECURITY.md b/SECURITY.md
@@ -173,7 +173,7 @@ the progress being made towards a fix and announcement.
 In addition, please include the following information along with your report:
 
 * Your name and affiliation (if any).
-* A description the technical details of the vulnerabilities. It is very
+* A description of the technical details of the vulnerabilities. It is very
   important to let us know how we can reproduce your findings.
 * An explanation who can exploit this vulnerability, and what they gain when
   doing so -- write an attack scenario. This will help us evaluate your report

diff --git a/configure.py b/configure.py
@@ -1222,6 +1222,9 @@ def set_tf_cuda_compute_capabilities(environ_cp):
         ask_cuda_compute_capabilities, default_cuda_compute_capabilities)
     # Check whether all capabilities from the input is valid
     all_valid = True
+    # Remove all whitespace characters before splitting the string
+    # that users may insert by accident, as this will result in error 
+    tf_cuda_compute_capabilities = ''.join(tf_cuda_compute_capabilities.split())
     for compute_capability in tf_cuda_compute_capabilities.split(','):
       m = re.match('[0-9]+.[0-9]+', compute_capability)
       if not m:

diff --git a/tensorflow/compiler/jit/encapsulate_subgraphs_pass.cc b/tensorflow/compiler/jit/encapsulate_subgraphs_pass.cc
@@ -240,7 +240,7 @@ class Encapsulator {
   // Once edges between compiled and outside_compilation clusters have been
   // replaced by send/recv ops, some dependencies may no longer be apparent.
   // A clustering pass finds all the dependencies between HC nodes that are only
-  // present as a result of edges between nodes in outside_compilaton clusters.
+  // present as a result of edges between nodes in outside_compilation clusters.
   // Suppose there is a path from outside_compilation cluster C in subgraph S
   // to outside_compilation cluster D in subgraph T. If S != T then a control
   // edge is added from the call node for S to the call node for T, which

diff --git a/tensorflow/compiler/xla/README.md b/tensorflow/compiler/xla/README.md
@@ -1 +1,7 @@
-This is the home of XLA.
+<p align="center">
+  <img width="200" src="xlalogo.png"/>
+</p>
+
+XLA (Accelerated Linear Algebra) is a domain-specific compiler for linear
+algebra that optimizes TensorFlow computations. See the
+[documentation](https://www.tensorflow.org/performance/xla/) for more details.
diff --git a/tensorflow/compiler/xla/service/conditional_simplifier.cc b/tensorflow/compiler/xla/service/conditional_simplifier.cc
@@ -35,7 +35,7 @@ namespace xla {
 
 // Tries to replace a conditional with a call operation of the corresponding
 // computation. If the given conditional has a constant predicate, tries to
-// replace it with a call to its true/false computation as appropirate and then
+// replace it with a call to its true/false computation as appropriate and then
 // inline that computation.
 //
 // Returns true if it made a change to the graph.

diff --git a/tensorflow/compiler/xla/service/copy_insertion.cc b/tensorflow/compiler/xla/service/copy_insertion.cc
@@ -64,7 +64,7 @@ struct SpecialCaseCopyPolicy {
   // output tuple.
   bool copy_root_replicated_buffers = false;
   // If true, insert a copy if a buffer coming from a constant or a parameter
-  // is found wihtin the output tuple.
+  // is found within the output tuple.
   bool copy_parameters_and_constants = false;
 };
 

diff --git a/tensorflow/compiler/xla/service/cpu/ir_function.h b/tensorflow/compiler/xla/service/cpu/ir_function.h
@@ -33,8 +33,8 @@ namespace cpu {
 // emitters for function and function argument access.
 // The llvm::Function is created with the standard function signature
 // used in the XLA CPU backend (see ir_function.cc for argument details).
-// In addtion IrFunction saves the callers IR insert point during contruction,
-// and restores it after desctruction.
+// In addition IrFunction saves the callers IR insert point during construction,
+// and restores it after destruction.
 //
 // Example usage:
 //

diff --git a/tensorflow/compiler/xla/service/cpu/shape_partition.h b/tensorflow/compiler/xla/service/cpu/shape_partition.h
@@ -38,7 +38,7 @@ namespace cpu {
 //
 //     [0, 1), [1, 2), [2, 3), [3, 4), [4, 5) [5, 8)
 //
-//   Note that the last partition has residule because the dimension size is
+//   Note that the last partition has residual because the dimension size is
 //   not a multiple of the partition count.
 //
 //

diff --git a/tensorflow/compiler/xla/service/despecializer.h b/tensorflow/compiler/xla/service/despecializer.h
@@ -25,7 +25,7 @@ namespace xla {
 
 // Creates an HloPassPipeline containing multiple HloPasses that can
 // despecialize an optimized HloModule. This is useful to run an HloModule
-// optimized for one specfic platform on a different platform (undoing platform
+// optimized for one specific platform on a different platform (undoing platform
 // specific passes) with matching numerics for comparison.
 //
 // Current despecialization passes are Defuser, ImplicitBroadcastRemover,

diff --git a/tensorflow/compiler/xla/service/gpu/ir_emitter_unnested.h b/tensorflow/compiler/xla/service/gpu/ir_emitter_unnested.h
@@ -38,7 +38,7 @@ namespace gpu {
 //
 // Examples of things that are not unnested computations:
 //
-//  - The reducer of a kReduce HLO.  This is emited using IrEmitterNested.
+//  - The reducer of a kReduce HLO.  This is emitted using IrEmitterNested.
 //  - The body of a fusion node.  IrEmitterUnenested emits the relevant code
 //    within a kernel function using FusedIrEmitter.  (FusedIrEmitter is not
 //    really an IrEmitter, but is more an "IR generator generator".)

diff --git a/tensorflow/compiler/xla/service/hlo_evaluator.cc b/tensorflow/compiler/xla/service/hlo_evaluator.cc
@@ -135,6 +135,7 @@ StatusOr<std::unique_ptr<Literal>> Compare<complex64>(
 
 }  // namespace
 
+
 HloEvaluator::HloEvaluator(int64 max_loop_iterations)
     : max_loop_iterations_(max_loop_iterations) {
   typed_visitors_[PRED] = MakeUnique<HloEvaluatorTypedVisitor<bool>>(this);

diff --git a/tensorflow/compiler/xla/service/interpreter/README.md b/tensorflow/compiler/xla/service/interpreter/README.md
@@ -5,7 +5,7 @@ evaluating the result of the HLO graph directly with HloEvaluator, without
 lowering it further (to LLVM IR for example) before execution as other backends
 (CPU and GPU for example) do.
 
-Its key componenets are:
+Its key components are:
 
 *   [`InterpreterCompiler`] despite the inherited naming of "compiler", all
     `InterpreterCompiler` really does is the following:

diff --git a/tensorflow/compiler/xla/service/layout_assignment.h b/tensorflow/compiler/xla/service/layout_assignment.h
@@ -282,8 +282,8 @@ class LayoutAssignment : public HloPassInterface {
   // the case that no particular layout is requested.
   //
   // channel_constraints is both an input and output. Any sends or recvs that
-  // are present in channel_constraints will be layed out as constrained. Any
-  // unconstrained sends or recvs will be layed out as locally optimal and their
+  // are present in channel_constraints will be laid out as constrained. Any
+  // unconstrained sends or recvs will be laid out as locally optimal and their
   // layout will be added as a constraint to channel_constraints.
   //
   // If channel_constraints is nullptr, no kSend or kRecvs must be contained

diff --git a/tensorflow/compiler/xla/service/reduce_precision_insertion.cc b/tensorflow/compiler/xla/service/reduce_precision_insertion.cc
@@ -75,7 +75,7 @@ StatusOr<bool> ReducePrecisionInsertion::insert_after(
     return false;
   }
 
-  // Check that we haven't already inserted an equivalant reduce-precision
+  // Check that we haven't already inserted an equivalent reduce-precision
   // operation after this instruction.  (The zero-user case occurs when this is
   // the root instruction.)
   if (instruction->user_count() > 0) {