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Amit Patankar
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Merging rc1 back into master.
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‎README.md

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@@ -34,12 +34,12 @@ and discussion.**
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People who are a little more adventurous can also try our nightly binaries:
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* 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-1.2.0rc0-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-1.2.0rc0-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-1.2.0rc0-cp35-cp35m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-python35-linux-cpu/))
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* 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-1.2.0rc0-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-1.2.0rc0-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-1.2.0rc0-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/))
39-
* 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-1.2.0rc0-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-1.2.0rc0-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/))
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* 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-1.2.0rc0-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-1.2.0rc0-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/))
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* Windows CPU-only: [Python 3.5 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/DEVICE=cpu,OS=windows/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow-1.2.0rc0-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/DEVICE=cpu,OS=windows/))
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* Windows GPU: [Python 3.5 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/DEVICE=gpu,OS=windows/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow_gpu-1.2.0rc0-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/DEVICE=gpu,OS=windows/))
37+
* 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-1.2.0rc1-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-1.2.0rc1-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-1.2.0rc1-cp35-cp35m-linux_x86_64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-python35-linux-cpu/))
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* 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-1.2.0rc1-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-1.2.0rc1-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-1.2.0rc1-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/))
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* 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-1.2.0rc1-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-1.2.0rc1-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/))
40+
* 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-1.2.0rc1-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-1.2.0rc1-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/))
41+
* Windows CPU-only: [Python 3.5 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/DEVICE=cpu,OS=windows/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow-1.2.0rc1-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/DEVICE=cpu,OS=windows/))
42+
* Windows GPU: [Python 3.5 64-bit](https://ci.tensorflow.org/view/Nightly/job/nightly-win/DEVICE=gpu,OS=windows/lastSuccessfulBuild/artifact/cmake_build/tf_python/dist/tensorflow_gpu-1.2.0rc1-cp35-cp35m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/DEVICE=gpu,OS=windows/))
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* 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/)
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([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-android/))
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‎RELEASE.md

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* Support client-provided ClusterSpec's and propagate them to all workers to enable the creation of dynamic TensorFlow clusters.
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* TensorFlow C library now available for Windows.
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* We released a new open-source version of TensorBoard.
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* [`SavedModel CLI`](https://www.tensorflow.org/versions/master/programmers_guide/saved_model_cli) tool available to inspect and execute MetaGraph in SavedModel
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* Android releases of TensorFlow are now pushed to jcenter for easier
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integration into apps. See
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https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/android/README.md
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for more details.
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* RNNCells' variable names have been renamed for consistency with Keras layers.
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Specifically, the previous variable names "weights" and "biases" have
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been changed to "kernel" and "bias", respectively.
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This may cause backward incompatibility with regard to your old
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checkpoints containing such RNN cells, in which case you can use the tool
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[checkpoint_convert script](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/rnn/python/tools/checkpoint_convert.py)
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to convert the variable names in your old checkpoints.
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* Many of the RNN functions and classes that were in the `tf.nn` namespace
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before the 1.0 release and which were moved to `tf.contrib.rnn` have now
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been moved back to the core namespace. This includes
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`RNNCell`, `LSTMCell`, `GRUCell`, and a number of other cells. These
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now reside in `tf.nn.rnn_cell` (with aliases in `tf.contrib.rnn` for backwards
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compatibility). The original `tf.nn.rnn` function is now `tf.nn.static_rnn`,
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and the bidirectional static and state saving static rnn functions are also
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now back in the `tf.nn` namespace.
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Notable exceptions are the `EmbeddingWrapper`, `InputProjectionWrapper` and
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`OutputProjectionWrapper`, which will slowly be moved to deprecation
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in `tf.contrib.rnn`. These are inefficient wrappers that should often
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be replaced by calling `embedding_lookup` or `layers.dense` as pre- or post-
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processing of the rnn. For RNN decoding, this functionality has been replaced
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with an alternative API in `tf.contrib.seq2seq`.
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## Deprecations
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* TensorFlow 1.2 may be the last time we build with cuDNN 5.1. Starting with
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TensorFlow 1.3, we will try to build all our prebuilt binaries with cuDNN 6.0.
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While we will try to keep our source code compatible with cuDNN 5.1, it will
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be best effort.
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## Breaking Changes to the API
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* `org.tensorflow.contrib.android.TensorFlowInferenceInterface` now throws exceptions where possible and and has simplified method signatures.
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* `org.tensorflow.contrib.android.TensorFlowInferenceInterface` now throws exceptions where possible and has simplified method signatures.
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## Changes to contrib APIs
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* Added `tf.contrib.util.create_example`.
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* Add `tf.summary.text` for outputting text to TensorBoard.
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* The "run" command of tfdbg's command-line interface now supports filtering of tensors by node name, op type and tensor dtype.
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* `tf.string_to_number` now supports int64 and float64 outputs.
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* `SavedModel CLI` tool available to inspect and execute MetaGraph in SavedModel
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## Thanks to our Contributors
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‎tensorflow/core/public/version.h

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// TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1",
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// "-beta", "-rc", "-rc.1")
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#define TF_VERSION_SUFFIX "-rc0"
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#define TF_VERSION_SUFFIX "-rc1"
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#define TF_STR_HELPER(x) #x
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#define TF_STR(x) TF_STR_HELPER(x)

‎tensorflow/docs_src/install/install_c.md

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OS="linux" # Change to "darwin" for Mac OS
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TARGET_DIRECTORY="/usr/local"
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curl -L \
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"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.2.0-rc0.tar.gz" |
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"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.2.0-rc1.tar.gz" |
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sudo tar -C $TARGET_DIRECTORY -xz
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The `tar` command extracts the TensorFlow C library into the `lib`

‎tensorflow/docs_src/install/install_go.md

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TF_TYPE="cpu" # Change to "gpu" for GPU support
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TARGET_DIRECTORY='/usr/local'
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curl -L \
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"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.2.0-rc0.tar.gz" |
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"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.2.0-rc1.tar.gz" |
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sudo tar -C $TARGET_DIRECTORY -xz
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The `tar` command extracts the TensorFlow C library into the `lib`

‎tensorflow/docs_src/install/install_java.md

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<dependency>
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<groupId>org.tensorflow</groupId>
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<artifactId>tensorflow</artifactId>
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<version>1.2.0-rc0</version>
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<version>1.2.0-rc1</version>
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</dependency>
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```
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<dependency>
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<groupId>org.tensorflow</groupId>
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<artifactId>tensorflow</artifactId>
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<version>1.2.0-rc0</version>
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<version>1.2.0-rc1</version>
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</dependency>
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</dependencies>
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</project>
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Take the following steps to install TensorFlow for Java on Linux or Mac OS:
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1. Download
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[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc0.jar),
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[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc1.jar),
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which is the TensorFlow Java Archive (JAR).
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2. Decide whether you will run TensorFlow for Java on CPU(s) only or with
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OS=$(uname -s | tr '[:upper:]' '[:lower:]')
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mkdir -p ./jni
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curl -L \
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"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.2.0-rc0.tar.gz" |
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"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.2.0-rc1.tar.gz" |
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tar -xz -C ./jni
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### Install on Windows
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Take the following steps to install TensorFlow for Java on Windows:
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1. Download
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[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc0.jar),
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[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc1.jar),
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which is the TensorFlow Java Archive (JAR).
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2. Download the following Java Native Interface (JNI) file appropriate for
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[TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.2.0-rc0.zip).
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[TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.2.0-rc1.zip).
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3. Extract this .zip file.
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downloaded `.jar` in your `classpath` by using the `-cp` compilation flag
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as follows:
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<pre><b>javac -cp libtensorflow-1.2.0-rc0.jar HelloTF.java</b></pre>
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<pre><b>javac -cp libtensorflow-1.2.0-rc1.jar HelloTF.java</b></pre>
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### Running
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For example, the following command line executes the `HelloTF` program on Linux
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and Mac OS X:
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<pre><b>java -cp libtensorflow-1.2.0-rc0.jar:. -Djava.library.path=./jni HelloTF</b></pre>
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<pre><b>java -cp libtensorflow-1.2.0-rc1.jar:. -Djava.library.path=./jni HelloTF</b></pre>
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And the following comand line executes the `HelloTF` program on Windows:
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<pre><b>java -cp libtensorflow-1.2.0-rc0.jar;. -Djava.library.path=jni HelloTF</b></pre>
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<pre><b>java -cp libtensorflow-1.2.0-rc1.jar;. -Djava.library.path=jni HelloTF</b></pre>
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If the program prints <tt>Hello from <i>version</i></tt>, you've successfully
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installed TensorFlow for Java and are ready to use the API. If the program

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