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Merge commit '6e054dbd4b741d5b8fa8af93fdd7c9b74ae67ce0' into usage_cl…
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…assification

* commit '6e054dbd4b741d5b8fa8af93fdd7c9b74ae67ce0': (511 commits)
  Fix tensordot with list of ints as axes (tensorflow#11959)
  Fix segfault when recording raw allocation returns nullptr (tensorflow#12074)
  [OpenCL] Fix for //tensorflow/python/kernel_tests:image_ops_test (tensorflow#111) (tensorflow#12041)
  Removing visited_node hash table - fixing multinode shape mismatch issue (tensorflow#12044)
  [OpenCL] Fixes core_rnn_cell_tests (tensorflow#12076)
  Added Convolutional LSTM (tensorflow#8891)
  Update monitors_test.py (tensorflow#12062)
  fix a typo in tf.nn.separable_conv2d's doc (tensorflow#12067)
  Fix cmake builds: (tensorflow#12048)
  Fix typo in RELEASE.md (tensorflow#12064)
  Fix typo (tensorflow#12069)
  Handle case where init node is not present in the frozen graph.
  Fix typo in datasets docstring
  tfdbg: fix a bug in string representation of SparseTensors
  BUILD dependency cleanup in tensorflow/stream_executor/cuda
  BUILD dependency cleanups. Rename RecvTensorAsync method to GrpcRecvTensorAsync to fix shadowing of method in Worker with a different signature.
  [tpu:profiler] Dump gzipped json trace.
  Minor cleanup
  tf.nn.separable_conv2d now supports data_format. Avoid unnecessary transposes in tf.layers.separable_conv2d (and implicitly in tf.contrib.layers.separable_conv2d).
  Add an identity initializer that works with partitioned variables.
  ...
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neuron-vision committed Aug 8, 2017
2 parents 9c0c2a2 + 6e054db commit 1f6b1f9
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2 changes: 1 addition & 1 deletion CODEOWNERS
Validating CODEOWNERS rules …
Expand Up @@ -17,7 +17,7 @@ tensorflow/contrib/data/* @mrry
tensorflow/contrib/distributions/* @jvdillon @langmore @rsepassi
tensorflow/contrib/factorization/* @agarwal-ashish @xavigonzalvo
tensorflow/contrib/ffmpeg/* @fredbertsch
# NEED OWNERT: tensorflow/contrib/framework/*
# NEED OWNER: tensorflow/contrib/framework/*
tensorflow/contrib/graph_editor/* @purpledog
# NEED OWNER: tensorflow/contrib/grid_rnn/*
tensorflow/contrib/hvx/* @satok16
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2 changes: 1 addition & 1 deletion ISSUE_TEMPLATE.md
@@ -1,6 +1,6 @@
Please go to Stack Overflow for help and support:

http://stackoverflow.com/questions/tagged/tensorflow
https://stackoverflow.com/questions/tagged/tensorflow

If you open a GitHub issue, here is our policy:

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15 changes: 7 additions & 8 deletions README.md
Expand Up @@ -9,7 +9,7 @@
| [![Build Status](https://ci.tensorflow.org/buildStatus/icon?job=tensorflow-master-cpu)](https://ci.tensorflow.org/job/tensorflow-master-cpu) | [![Build Status](https://ci.tensorflow.org/buildStatus/icon?job=tensorflow-master-linux-gpu)](https://ci.tensorflow.org/job/tensorflow-master-linux-gpu) | [![Build Status](https://ci.tensorflow.org/buildStatus/icon?job=tensorflow-master-mac)](https://ci.tensorflow.org/job/tensorflow-master-mac) | [![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) |

**TensorFlow** is an open source software library for numerical computation using
data flow graphs. Nodes in the graph represent mathematical operations, while
data flow graphs. The graph nodes represent mathematical operations, while
the graph edges represent the multidimensional data arrays (tensors) that flow
between them. This flexible architecture lets you deploy computation to one
or more CPUs or GPUs in a desktop, server, or mobile device without rewriting
Expand All @@ -21,7 +21,7 @@ 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.

**If you'd like to contribute to TensorFlow, be sure to review the [contribution
**If you want to contribute to TensorFlow, be sure to review the [contribution
guidelines](CONTRIBUTING.md).**

**We use [GitHub issues](https://github.com/tensorflow/tensorflow/issues) for
Expand All @@ -35,12 +35,11 @@ and discussion, and please direct specific questions to [Stack Overflow](https:/
People who are a little more adventurous can also try our nightly binaries:


* Linux CPU-only: [Python 2](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc0-cp27-none-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/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/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc0-cp34-cp34m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/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/Nightly/job/nightly-python35-linux-cpu/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc0-cp35-cp35m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-python35-linux-cpu/))
* Linux GPU: [Python 2](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-linux-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow_gpu-1.3.0rc0-cp27-none-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-linux-gpu/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/Nightly/job/nightly-matrix-linux-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow_gpu-1.3.0rc0-cp34-cp34m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-linux-gpu/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/Nightly/job/nightly-matrix-linux-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.5,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow_gpu-1.3.0rc0-cp35-cp35m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-linux-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.5,label=gpu-linux/))
* Mac CPU-only: [Python 2](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=mac-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc0-py2-none-any.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/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/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=mac-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc0-py3-none-any.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=mac-slave/))
* Mac GPU: [Python 2](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-mac-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=gpu-mac/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow_gpu-1.3.0rc0-py2-none-any.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-mac-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=gpu-mac/)) / [Python 3](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-mac-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=gpu-mac/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow_gpu-1.3.0rc0-py3-none-any.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-mac-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=gpu-mac/))
* Windows CPU-only: [Python 3.5 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows,PY=35/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow-1.3.0rc0-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows,PY=35/)) / [Python 3.6 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows,PY=36/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow-1.3.0rc0-cp36-cp36m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows,PY=36/))
* Windows GPU: [Python 3.5 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows-gpu,PY=35/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow_gpu-1.3.0rc0-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows-gpu,PY=35/)) / [Python 3.6 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows-gpu,PY=36/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow_gpu-1.3.0rc0-cp36-cp36m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows-gpu,PY=36/))
* Linux CPU-only: [Python 2](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc2-cp27-none-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/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/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc2-cp34-cp34m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/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/Nightly/job/nightly-python35-linux-cpu/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc2-cp35-cp35m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-python35-linux-cpu/))
* Linux GPU: [Python 2](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-linux-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow_gpu-1.3.0rc2-cp27-none-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-linux-gpu/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/Nightly/job/nightly-matrix-linux-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow_gpu-1.3.0rc2-cp34-cp34m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-linux-gpu/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/Nightly/job/nightly-matrix-linux-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.5,label=gpu-linux/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow_gpu-1.3.0rc2-cp35-cp35m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-linux-gpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3.5,label=gpu-linux/))
* Mac CPU-only: [Python 2](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=mac-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc2-py2-none-any.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/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/Nightly/job/nightly-matrix-cpu/TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON3,label=mac-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-1.3.0rc2-py3-none-any.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/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/Nightly/job/nightly-win/M=windows,PY=35/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow-1.3.0rc2-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows,PY=35/)) / [Python 3.6 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows,PY=36/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow-1.3.0rc2-cp36-cp36m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows,PY=36/))
* Windows GPU: [Python 3.5 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows-gpu,PY=35/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow_gpu-1.3.0rc2-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows-gpu,PY=35/)) / [Python 3.6 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows-gpu,PY=36/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow_gpu-1.3.0rc2-cp36-cp36m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/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](http://ci.tensorflow.org/view/Nightly/job/nightly-android/lastSuccessfulBuild/artifact/out/native/)
([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-android/))

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25 changes: 19 additions & 6 deletions RELEASE.md
@@ -1,8 +1,15 @@
# Release 1.3.0

## Major Features and Improvements
* Added canned estimators to Tensorflow library. List of added estimators: `DNNClassifier`, `DNNRegressor`, `LinearClassifer`, `LinearRegressor`, `DNNLinearCombinedClassifier`, `DNNLinearCombinedRegressor`.
* Added canned estimators to Tensorflow library. List of added estimators:
* `DNNClassifier`
* `DNNRegressor`
* `LinearClassifier`
* `LinearRegressor`
* `DNNLinearCombinedClassifier`
* `DNNLinearCombinedRegressor`.
* All our prebuilt binaries have been built with cuDNN 6.
* `import tensorflow` now goes much faster.
* Adds a file cache to the GCS filesystem with configurable max staleness for file contents. This permits caching of file contents across close/open boundaries.
* Added an axis parameter to `tf.gather`.
* Added a `constant_values` keyword argument to `tf.pad`.
Expand All @@ -17,10 +24,15 @@
* Introduces base implementations of ClusterResolvers.
* Unify memory representations of TensorShape and PartialTensorShape. As a consequence, tensors now have a maximum of 254 dimensions, not 255.
* Changed references to LIBXSMM to use version 1.8.1.
* TensorFlow Debugger (tfdbg): Display summaries of numeric tensor values with the `-s` flag to command `print_tensor` or `pt`.
* TensorFlow Debugger (tfdbg):
* Display summaries of numeric tensor values with the `-s` flag to command `print_tensor` or `pt`.
* Display feed values with the `print_feed` or `pf` command and clickable links in the curses UI.
* Runtime profiler at the op level and the Python source line level with the `run -p` command.
* Initial release of the statistical distribution library `tf.distributions`.
* GPU kernels and speed improvements for for unary `tf.where` and `tf.nn.top_k`.
* Monotonic Attention wrappers added to `tf.contrib.seq2seq`.
* Added `tf.contrib.signal`, a library for signal processing primitives.
* Added `tf.contrib.resampler`, containing CPU and GPU ops for differentiable resampling of images.

## Breaking Changes to the API
* `tf.RewriterConfig` was removed from the Python API after being available in 1.2 release candidates (it was never in an actual release). Graph rewriting is still available, just not as `tf.RewriterConfig`. Instead add an explicit import.
Expand All @@ -33,7 +45,7 @@
* Adds FULLY_CONNECTED Op to tensorflow/contrib/lite/schema.fbs

## Bug Fixes and Other Changes
* Fixes 'strides' and 'begin' dtype mismatch when slicing using int64 Tensor index in python.
* Fixes `strides` and `begin` dtype mismatch when slicing using int64 Tensor index in python.
* Improved convolution padding documentation.
* Add a tag constant, gpu, to present graph with GPU support.
* `saved_model.utils` now support SparseTensors transparently.
Expand All @@ -54,7 +66,7 @@
* Exported model signatures using the 'predict' method will no longer have their input and output keys silently ignored and rewritten to 'inputs' and 'outputs'. If a model was exported with different names before 1.2, and is now served with tensorflow/serving, it will accept requests using 'inputs' and 'outputs'. Starting at 1.2, such a model will accept the keys specified during export. Therefore, inference requests using 'inputs' and 'outputs' may start to fail. To fix this, either update any inference clients to send requests with the actual input and output keys used by the trainer code, or conversely, update the trainer code to name the input and output Tensors 'inputs' and 'outputs', respectively. Signatures using the 'classify' and 'regress' methods are not affected by this change; they will continue to standardize their input and output keys as before.
* Add in-memory caching to the Dataset API.
* Set default end_of_sequence variable in datasets iterators to false.
* [Performance] Increase performance of `tf.layers.con2d` when setting use_bias=True by 2x by using nn.bias_add.
* [Performance] Increase performance of `tf.layers.conv2d` when setting use_bias=True by 2x by using nn.bias_add.
* Update iOS examples to use CocoaPods, and moved to tensorflow/examples/ios.
* Adds a family= attribute in `tf.summary` ops to allow controlling the tab name used in Tensorboard for organizing summaries.
* When GPU is configured, do not require --config=cuda, instead, automatically build for GPU if this is requested in the configure script.
Expand All @@ -65,8 +77,9 @@
* Framework now supports armv7, cocoapods.org now displays correct page.
* Script to create iOS framework for CocoaPods.
* Android releases of TensorFlow are now pushed to jcenter for easier integration into apps. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/android/README.md for more details.
* Fixed a bug that prevented tfdbg from functioning with multi-GPU setups.
* Fixed a bug that prevented tfdbg from working with `tf.Session.make_callable`.
* TensorFlow Debugger (tfdbg):
* Fixed a bug that prevented tfdbg from functioning with multi-GPU setups.
* Fixed a bug that prevented tfdbg from working with `tf.Session.make_callable`.

## Thanks to our Contributors

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3 changes: 3 additions & 0 deletions WORKSPACE
Expand Up @@ -32,6 +32,9 @@ android_ndk_repository(
name="androidndk",
path="/Users/ishay/Library/Android/sdk/ndk-bundle",
# # This needs to be 14 or higher to compile TensorFlow.
# # Please specify API level to >= 21 to build for 64-bit
# # archtectures or the Android NDK will automatically select biggest
# # API level that it supports without notice.
# # Note that the NDK version is not the API level.
api_level=14
)
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81 changes: 81 additions & 0 deletions arm_compiler.BUILD
@@ -0,0 +1,81 @@
package(default_visibility = ["//visibility:public"])

filegroup(
name = "gcc",
srcs = [
"bin/arm-linux-gnueabihf-gcc",
],
)

filegroup(
name = "ar",
srcs = [
"bin/arm-linux-gnueabihf-ar",
],
)

filegroup(
name = "ld",
srcs = [
"bin/arm-linux-gnueabihf-ld",
],
)

filegroup(
name = "nm",
srcs = [
"bin/arm-linux-gnueabihf-nm",
],
)

filegroup(
name = "objcopy",
srcs = [
"bin/arm-linux-gnueabihf-objcopy",
],
)

filegroup(
name = "objdump",
srcs = [
"bin/arm-linux-gnueabihf-objdump",
],
)

filegroup(
name = "strip",
srcs = [
"bin/arm-linux-gnueabihf-strip",
],
)

filegroup(
name = "as",
srcs = [
"bin/arm-linux-gnueabihf-as",
],
)

filegroup(
name = "compiler_pieces",
srcs = glob([
"arm-linux-gnueabihf/**",
"libexec/**",
"lib/gcc/arm-linux-gnueabihf/**",
"include/**",
]),
)

filegroup(
name = "compiler_components",
srcs = [
":ar",
":as",
":gcc",
":ld",
":nm",
":objcopy",
":objdump",
":strip",
],
)

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