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Merging rc2 back into master.

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Amit Patankar 2017-06-07 11:00:19 -07:00
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12
README.md
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@ -34,12 +34,12 @@ and discussion.**
People who are a little more adventurous can also try our nightly binaries: 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-1.2.0rc1-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/)) * 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-1.2.0rc2-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-1.2.0rc2-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-1.2.0rc2-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-1.2.0rc1-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/)) * 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-1.2.0rc2-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-1.2.0rc2-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-1.2.0rc2-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-1.2.0rc1-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/)) * 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-1.2.0rc2-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-1.2.0rc2-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/))
* 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/)) * 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-1.2.0rc2-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-1.2.0rc2-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-1.2.0rc1-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-1.2.0rc1-cp36-cp36m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows,PY=36/)) * 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-1.2.0rc2-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-1.2.0rc2-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-1.2.0rc1-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-1.2.0rc1-cp36-cp36m-win_amd64.whl) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-win/M=windows-gpu,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-1.2.0rc2-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-1.2.0rc2-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/) * 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/)) ([build history](https://ci.tensorflow.org/view/Nightly/job/nightly-android/))

9
RELEASE.md
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@ -81,6 +81,15 @@
be replaced by calling `embedding_lookup` or `layers.dense` as pre- or post- be replaced by calling `embedding_lookup` or `layers.dense` as pre- or post-
processing of the rnn. For RNN decoding, this functionality has been replaced processing of the rnn. For RNN decoding, this functionality has been replaced
with an alternative API in `tf.contrib.seq2seq`. with an alternative API in `tf.contrib.seq2seq`.
* Intel MKL Integration (https://software.intel.com/en-us/articles/tensorflow-optimizations-on-modern-intel-architecture). Intel developed a number of
optimized deep learning primitives: In addition to matrix multiplication and
convolution, these building blocks include:
Direct batched convolution
Pooling: maximum, minimum, average
Normalization: LRN, batch normalization
Activation: rectified linear unit (ReLU)
Data manipulation: multi-dimensional transposition (conversion), split,
concat, sum and scale.
## Deprecations ## Deprecations

2
tensorflow/core/public/version.h
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@ -24,7 +24,7 @@ limitations under the License.
// TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1", // TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1",
// "-beta", "-rc", "-rc.1") // "-beta", "-rc", "-rc.1")
#define TF_VERSION_SUFFIX "-rc1" #define TF_VERSION_SUFFIX "-rc2"
#define TF_STR_HELPER(x) #x #define TF_STR_HELPER(x) #x
#define TF_STR(x) TF_STR_HELPER(x) #define TF_STR(x) TF_STR_HELPER(x)

2
tensorflow/docs_src/install/install_c.md
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@ -35,7 +35,7 @@ enable TensorFlow for C:
OS="linux" # Change to "darwin" for Mac OS OS="linux" # Change to "darwin" for Mac OS
TARGET_DIRECTORY="/usr/local" TARGET_DIRECTORY="/usr/local"
curl -L \ curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.2.0-rc1.tar.gz" | "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.2.0-rc2.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib` The `tar` command extracts the TensorFlow C library into the `lib`

2
tensorflow/docs_src/install/install_go.md
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@ -35,7 +35,7 @@ steps to install this library and enable TensorFlow for Go:
TF_TYPE="cpu" # Change to "gpu" for GPU support TF_TYPE="cpu" # Change to "gpu" for GPU support
TARGET_DIRECTORY='/usr/local' TARGET_DIRECTORY='/usr/local'
curl -L \ curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.2.0-rc1.tar.gz" | "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.2.0-rc2.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib` The `tar` command extracts the TensorFlow C library into the `lib`

18
tensorflow/docs_src/install/install_java.md
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@ -34,7 +34,7 @@ following to the project's `pom.xml` to use the TensorFlow Java APIs:
<dependency> <dependency>
<groupId>org.tensorflow</groupId> <groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId> <artifactId>tensorflow</artifactId>
<version>1.2.0-rc1</version> <version>1.2.0-rc2</version>
</dependency> </dependency>
``` ```
@ -63,7 +63,7 @@ As an example, these steps will create a Maven project that uses TensorFlow:
<dependency> <dependency>
<groupId>org.tensorflow</groupId> <groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId> <artifactId>tensorflow</artifactId>
<version>1.2.0-rc1</version> <version>1.2.0-rc2</version>
</dependency> </dependency>
</dependencies> </dependencies>
</project> </project>
@ -122,7 +122,7 @@ refer to the simpler instructions above instead.
Take the following steps to install TensorFlow for Java on Linux or Mac OS: Take the following steps to install TensorFlow for Java on Linux or Mac OS:
1. Download 1. Download
[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc1.jar), [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc2.jar),
which is the TensorFlow Java Archive (JAR). which is the TensorFlow Java Archive (JAR).
2. Decide whether you will run TensorFlow for Java on CPU(s) only or with 2. Decide whether you will run TensorFlow for Java on CPU(s) only or with
@ -141,7 +141,7 @@ Take the following steps to install TensorFlow for Java on Linux or Mac OS:
OS=$(uname -s | tr '[:upper:]' '[:lower:]') OS=$(uname -s | tr '[:upper:]' '[:lower:]')
mkdir -p ./jni mkdir -p ./jni
curl -L \ curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.2.0-rc1.tar.gz" | "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.2.0-rc2.tar.gz" |
tar -xz -C ./jni tar -xz -C ./jni
### Install on Windows ### Install on Windows
@ -149,10 +149,10 @@ Take the following steps to install TensorFlow for Java on Linux or Mac OS:
Take the following steps to install TensorFlow for Java on Windows: Take the following steps to install TensorFlow for Java on Windows:
1. Download 1. Download
[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc1.jar), [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc2.jar),
which is the TensorFlow Java Archive (JAR). which is the TensorFlow Java Archive (JAR).
2. Download the following Java Native Interface (JNI) file appropriate for 2. Download the following Java Native Interface (JNI) file appropriate for
[TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.2.0-rc1.zip). [TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.2.0-rc2.zip).
3. Extract this .zip file. 3. Extract this .zip file.
@ -200,7 +200,7 @@ must be part of your `classpath`. For example, you can include the
downloaded `.jar` in your `classpath` by using the `-cp` compilation flag downloaded `.jar` in your `classpath` by using the `-cp` compilation flag
as follows: as follows:
<pre><b>javac -cp libtensorflow-1.2.0-rc1.jar HelloTF.java</b></pre> <pre><b>javac -cp libtensorflow-1.2.0-rc2.jar HelloTF.java</b></pre>
### Running ### Running
@ -214,11 +214,11 @@ two files are available to the JVM:
For example, the following command line executes the `HelloTF` program on Linux For example, the following command line executes the `HelloTF` program on Linux
and Mac OS X: and Mac OS X:
<pre><b>java -cp libtensorflow-1.2.0-rc1.jar:. -Djava.library.path=./jni HelloTF</b></pre> <pre><b>java -cp libtensorflow-1.2.0-rc2.jar:. -Djava.library.path=./jni HelloTF</b></pre>
And the following comand line executes the `HelloTF` program on Windows: And the following comand line executes the `HelloTF` program on Windows:
<pre><b>java -cp libtensorflow-1.2.0-rc1.jar;. -Djava.library.path=jni HelloTF</b></pre> <pre><b>java -cp libtensorflow-1.2.0-rc2.jar;. -Djava.library.path=jni HelloTF</b></pre>
If the program prints <tt>Hello from <i>version</i></tt>, you've successfully If the program prints <tt>Hello from <i>version</i></tt>, you've successfully
installed TensorFlow for Java and are ready to use the API. If the program installed TensorFlow for Java and are ready to use the API. If the program

22
tensorflow/docs_src/install/install_linux.md
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@ -172,7 +172,7 @@ Take the following steps to install TensorFlow with Virtualenv:
virtualenv environment: virtualenv environment:
<pre>(tensorflow)$ <b>pip3 install --upgrade \ <pre>(tensorflow)$ <b>pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc2-cp34-cp34m-linux_x86_64.whl</b></pre>
If you encounter installation problems, see If you encounter installation problems, see
[Common Installation Problems](#common_installation_problems). [Common Installation Problems](#common_installation_problems).
@ -277,7 +277,7 @@ take the following steps:
<pre> <pre>
$ <b>sudo pip3 install --upgrade \ $ <b>sudo pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp34-cp34m-linux_x86_64.whl</b> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc2-cp34-cp34m-linux_x86_64.whl</b>
</pre> </pre>
If this step fails, see If this step fails, see
@ -464,7 +464,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
<pre> <pre>
(tensorflow)$ <b>pip install --ignore-installed --upgrade \ (tensorflow)$ <b>pip install --ignore-installed --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc2-cp34-cp34m-linux_x86_64.whl</b></pre>
<a name="ValidateYourInstallation"></a> <a name="ValidateYourInstallation"></a>
@ -632,14 +632,14 @@ This section documents the relevant values for Linux installations.
CPU only: CPU only:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp27-none-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc2-cp27-none-linux_x86_64.whl
</pre> </pre>
GPU support: GPU support:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc1-cp27-none-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc2-cp27-none-linux_x86_64.whl
</pre> </pre>
Note that GPU support requires the NVIDIA hardware and software described in Note that GPU support requires the NVIDIA hardware and software described in
@ -651,14 +651,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only: CPU only:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp34-cp34m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc2-cp34-cp34m-linux_x86_64.whl
</pre> </pre>
GPU support: GPU support:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc1-cp34-cp34m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc2-cp34-cp34m-linux_x86_64.whl
</pre> </pre>
Note that GPU support requires the NVIDIA hardware and software described in Note that GPU support requires the NVIDIA hardware and software described in
@ -670,14 +670,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only: CPU only:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp35-cp35m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc2-cp35-cp35m-linux_x86_64.whl
</pre> </pre>
GPU support: GPU support:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc1-cp35-cp35m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc2-cp35-cp35m-linux_x86_64.whl
</pre> </pre>
@ -689,14 +689,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only: CPU only:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp36-cp36m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc2-cp36-cp36m-linux_x86_64.whl
</pre> </pre>
GPU support: GPU support:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc1-cp36-cp36m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc2-cp36-cp36m-linux_x86_64.whl
</pre> </pre>

10
tensorflow/docs_src/install/install_mac.md
View File

@ -109,7 +109,7 @@ Take the following steps to install TensorFlow with Virtualenv:
TensorFlow in the active Virtualenv is as follows: TensorFlow in the active Virtualenv is as follows:
<pre> $ <b>pip3 install --upgrade \ <pre> $ <b>pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-any.whl</b></pre> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc2-py2-none-any.whl</b></pre>
If you encounter installation problems, see If you encounter installation problems, see
[Common Installation Problems](#common-installation-problems). [Common Installation Problems](#common-installation-problems).
@ -230,7 +230,7 @@ take the following steps:
issue the following command: issue the following command:
<pre> $ <b>sudo pip3 install --upgrade \ <pre> $ <b>sudo pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-any.whl</b> </pre> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc2-py2-none-any.whl</b> </pre>
If the preceding command fails, see If the preceding command fails, see
[installation problems](#common-installation-problems). [installation problems](#common-installation-problems).
@ -339,7 +339,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
TensorFlow for Python 2.7: TensorFlow for Python 2.7:
<pre> (tensorflow)$ <b>pip install --ignore-installed --upgrade \ <pre> (tensorflow)$ <b>pip install --ignore-installed --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-any.whl</b></pre> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc2-py2-none-any.whl</b></pre>
<a name="ValidateYourInstallation"></a> <a name="ValidateYourInstallation"></a>
@ -512,7 +512,7 @@ This section documents the relevant values for Mac OS installations.
<pre> <pre>
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-any.whl https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc2-py2-none-any.whl
</pre> </pre>
@ -520,7 +520,7 @@ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-a
<pre> <pre>
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py3-none-any.whl https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc2-py3-none-any.whl
</pre> </pre>

4
tensorflow/docs_src/install/install_sources.md
View File

@ -320,10 +320,10 @@ Invoke `pip install` to install that pip package.
The filename of the `.whl` file depends on your platform. The filename of the `.whl` file depends on your platform.
For example, the following command will install the pip package For example, the following command will install the pip package
for TensorFlow 1.2.0rc1 on Linux: for TensorFlow 1.2.0rc2 on Linux:
<pre> <pre>
$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.2.0rc1-py2-none-any.whl</b> $ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.2.0rc2-py2-none-any.whl</b>
</pre> </pre>
## Validate your installation ## Validate your installation

4
tensorflow/docs_src/install/install_windows.md
View File

@ -114,12 +114,12 @@ Take the following steps to install TensorFlow in an Anaconda environment:
environment. To install the CPU-only version of TensorFlow, enter the environment. To install the CPU-only version of TensorFlow, enter the
following command: following command:
<pre>(tensorflow)C:\> <b>pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.0rc1-cp35-cp35m-win_amd64.whl</b> </pre> <pre>(tensorflow)C:\> <b>pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.0rc2-cp35-cp35m-win_amd64.whl</b> </pre>
To install the GPU version of TensorFlow, enter the following command To install the GPU version of TensorFlow, enter the following command
(on a single line): (on a single line):
<pre>(tensorflow)C:\> <b>pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.2.0rc1-cp35-cp35m-win_amd64.whl</b> </pre> <pre>(tensorflow)C:\> <b>pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.2.0rc2-cp35-cp35m-win_amd64.whl</b> </pre>
## Validate your installation ## Validate your installation

2
tensorflow/tools/pip_package/setup.py
View File

@ -29,7 +29,7 @@ from setuptools.dist import Distribution
# This version string is semver compatible, but incompatible with pip. # This version string is semver compatible, but incompatible with pip.
# For pip, we will remove all '-' characters from this string, and use the # For pip, we will remove all '-' characters from this string, and use the
# result for pip. # result for pip.
_VERSION = '1.2.0-rc1' _VERSION = '1.2.0-rc2'
REQUIRED_PACKAGES = [ REQUIRED_PACKAGES = [
'numpy >= 1.11.0', 'numpy >= 1.11.0',