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Merging rc1 back into master.

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Amit Patankar 2017-05-31 09:25:50 -07:00
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12
README.md
View File

@ -34,12 +34,12 @@ and discussion.**
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-1.2.0rc0-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/))
* 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/))
* 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/))
* 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/))
* 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/))
* 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/))
* 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 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/))
* 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 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/))
* 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/))
* 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/))
* 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/))

37
RELEASE.md
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@ -44,9 +44,43 @@
* Support client-provided ClusterSpec's and propagate them to all workers to enable the creation of dynamic TensorFlow clusters.
* TensorFlow C library now available for Windows.
* We released a new open-source version of TensorBoard.
* [`SavedModel CLI`](https://www.tensorflow.org/versions/master/programmers_guide/saved_model_cli) tool available to inspect and execute MetaGraph in SavedModel
* 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.
* RNNCells' variable names have been renamed for consistency with Keras layers.
Specifically, the previous variable names "weights" and "biases" have
been changed to "kernel" and "bias", respectively.
This may cause backward incompatibility with regard to your old
checkpoints containing such RNN cells, in which case you can use the tool
[checkpoint_convert script](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/rnn/python/tools/checkpoint_convert.py)
to convert the variable names in your old checkpoints.
* Many of the RNN functions and classes that were in the `tf.nn` namespace
before the 1.0 release and which were moved to `tf.contrib.rnn` have now
been moved back to the core namespace. This includes
`RNNCell`, `LSTMCell`, `GRUCell`, and a number of other cells. These
now reside in `tf.nn.rnn_cell` (with aliases in `tf.contrib.rnn` for backwards
compatibility). The original `tf.nn.rnn` function is now `tf.nn.static_rnn`,
and the bidirectional static and state saving static rnn functions are also
now back in the `tf.nn` namespace.
Notable exceptions are the `EmbeddingWrapper`, `InputProjectionWrapper` and
`OutputProjectionWrapper`, which will slowly be moved to deprecation
in `tf.contrib.rnn`. These are inefficient wrappers that should often
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
with an alternative API in `tf.contrib.seq2seq`.
## Deprecations
* TensorFlow 1.2 may be the last time we build with cuDNN 5.1. Starting with
TensorFlow 1.3, we will try to build all our prebuilt binaries with cuDNN 6.0.
While we will try to keep our source code compatible with cuDNN 5.1, it will
be best effort.
## Breaking Changes to the API
* `org.tensorflow.contrib.android.TensorFlowInferenceInterface` now throws exceptions where possible and and has simplified method signatures.
* `org.tensorflow.contrib.android.TensorFlowInferenceInterface` now throws exceptions where possible and has simplified method signatures.
## Changes to contrib APIs
* Added `tf.contrib.util.create_example`.
@ -98,7 +132,6 @@
* Add `tf.summary.text` for outputting text to TensorBoard.
* The "run" command of tfdbg's command-line interface now supports filtering of tensors by node name, op type and tensor dtype.
* `tf.string_to_number` now supports int64 and float64 outputs.
* `SavedModel CLI` tool available to inspect and execute MetaGraph in SavedModel
## Thanks to our Contributors

2
tensorflow/core/public/version.h
View File

@ -24,7 +24,7 @@ limitations under the License.
// TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1",
// "-beta", "-rc", "-rc.1")
#define TF_VERSION_SUFFIX "-rc0"
#define TF_VERSION_SUFFIX "-rc1"
#define TF_STR_HELPER(x) #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
TARGET_DIRECTORY="/usr/local"
curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.2.0-rc0.tar.gz" |
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.2.0-rc1.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib`

2
tensorflow/docs_src/install/install_go.md
View File

@ -35,7 +35,7 @@ steps to install this library and enable TensorFlow for Go:
TF_TYPE="cpu" # Change to "gpu" for GPU support
TARGET_DIRECTORY='/usr/local'
curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.2.0-rc0.tar.gz" |
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.2.0-rc1.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib`

18
tensorflow/docs_src/install/install_java.md
View File

@ -34,7 +34,7 @@ following to the project's `pom.xml` to use the TensorFlow Java APIs:
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId>
<version>1.2.0-rc0</version>
<version>1.2.0-rc1</version>
</dependency>
```
@ -63,7 +63,7 @@ As an example, these steps will create a Maven project that uses TensorFlow:
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId>
<version>1.2.0-rc0</version>
<version>1.2.0-rc1</version>
</dependency>
</dependencies>
</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:
1. Download
[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc0.jar),
[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc1.jar),
which is the TensorFlow Java Archive (JAR).
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=$(uname -s | tr '[:upper:]' '[:lower:]')
mkdir -p ./jni
curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.2.0-rc0.tar.gz" |
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.2.0-rc1.tar.gz" |
tar -xz -C ./jni
### 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:
1. Download
[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc0.jar),
[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.2.0-rc1.jar),
which is the TensorFlow Java Archive (JAR).
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-rc0.zip).
[TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.2.0-rc1.zip).
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
as follows:
<pre><b>javac -cp libtensorflow-1.2.0-rc0.jar HelloTF.java</b></pre>
<pre><b>javac -cp libtensorflow-1.2.0-rc1.jar HelloTF.java</b></pre>
### Running
@ -214,11 +214,11 @@ two files are available to the JVM:
For example, the following command line executes the `HelloTF` program on Linux
and Mac OS X:
<pre><b>java -cp libtensorflow-1.2.0-rc0.jar:. -Djava.library.path=./jni HelloTF</b></pre>
<pre><b>java -cp libtensorflow-1.2.0-rc1.jar:. -Djava.library.path=./jni HelloTF</b></pre>
And the following comand line executes the `HelloTF` program on Windows:
<pre><b>java -cp libtensorflow-1.2.0-rc0.jar;. -Djava.library.path=jni HelloTF</b></pre>
<pre><b>java -cp libtensorflow-1.2.0-rc1.jar;. -Djava.library.path=jni HelloTF</b></pre>
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

40
tensorflow/docs_src/install/install_linux.md
View File

@ -154,6 +154,26 @@ Take the following steps to install TensorFlow with Virtualenv:
If the preceding command succeeds, skip Step 5. If the preceding
command fails, perform Step 5.
5. (Optional) If Step 4 failed (typically because you invoked a pip version
lower than 8.1), install TensorFlow in the active virtualenv environment
by issuing a command of the following format:
<pre> (tensorflow)$ <b>pip install --upgrade</b> <i>tfBinaryURL</i> # Python 2.7
(tensorflow)$ <b>pip3 install --upgrade</b> <i>tfBinaryURL</i> # Python 3.n </pre>
where <code><em>tfBinaryURL</em></code> identifies the URL of the
TensorFlow Python package. The appropriate value of
<code><em>tfBinaryURL</em></code>depends on the operating system,
Python version, and GPU support. Find the appropriate value for
<code><em>tfBinaryURL</em></code> for your system
[here](#the_url_of_the_tensorflow_python_package). For example, if you
are installing TensorFlow for Linux, Python 2.7, and CPU-only support,
issue the following command to install TensorFlow in the active
virtualenv environment:
<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>
If you encounter installation problems, see
[Common Installation Problems](#common_installation_problems).
@ -257,7 +277,7 @@ take the following steps:
<pre>
$ <b>sudo pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc0-cp34-cp34m-linux_x86_64.whl</b>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp34-cp34m-linux_x86_64.whl</b>
</pre>
If this step fails, see
@ -444,7 +464,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
<pre>
(tensorflow)$ <b>pip install --ignore-installed --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc0-cp34-cp34m-linux_x86_64.whl</b></pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre>
<a name="ValidateYourInstallation"></a>
@ -612,14 +632,14 @@ This section documents the relevant values for Linux installations.
CPU only:
<pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc0-cp27-none-linux_x86_64.whl
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp27-none-linux_x86_64.whl
</pre>
GPU support:
<pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc0-cp27-none-linux_x86_64.whl
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc1-cp27-none-linux_x86_64.whl
</pre>
Note that GPU support requires the NVIDIA hardware and software described in
@ -631,14 +651,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only:
<pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc0-cp34-cp34m-linux_x86_64.whl
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp34-cp34m-linux_x86_64.whl
</pre>
GPU support:
<pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc0-cp34-cp34m-linux_x86_64.whl
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc1-cp34-cp34m-linux_x86_64.whl
</pre>
Note that GPU support requires the NVIDIA hardware and software described in
@ -650,14 +670,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only:
<pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc0-cp35-cp35m-linux_x86_64.whl
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp35-cp35m-linux_x86_64.whl
</pre>
GPU support:
<pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc0-cp35-cp35m-linux_x86_64.whl
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc1-cp35-cp35m-linux_x86_64.whl
</pre>
@ -669,14 +689,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only:
<pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc0-cp36-cp36m-linux_x86_64.whl
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.0rc1-cp36-cp36m-linux_x86_64.whl
</pre>
GPU support:
<pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc0-cp36-cp36m-linux_x86_64.whl
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0rc1-cp36-cp36m-linux_x86_64.whl
</pre>

28
tensorflow/docs_src/install/install_mac.md
View File

@ -91,6 +91,26 @@ Take the following steps to install TensorFlow with Virtualenv:
<pre> (tensorflow)$ <b>pip install --upgrade tensorflow</b> # for Python 2.7
(tensorflow)$ <b>pip3 install --upgrade tensorflow</b> # for Python 3.n
7. Optional. If Step 6 failed (typically because you invoked a pip version
lower than 8.1), install TensorFlow in the active
virtualenv environment by issuing a command of the following format:
<pre> $ <b>pip install --upgrade</b> <i>tfBinaryURL</i> # Python 2.7
$ <b>pip3 install --upgrade</b> <i>tfBinaryURL</i> # Python 3.n </pre>
where <i>tfBinaryURL</i> identifies the URL
of the TensorFlow Python package. The appropriate value of
<i>tfBinaryURL</i> depends on the operating system and
Python version. Find the appropriate value for
<i>tfBinaryURL</i> for your system
[here](#the_url_of_the_tensorflow_python_package).
For example, if you are installing TensorFlow for Mac OS X,
Python 2.7, the command to install
TensorFlow in the active Virtualenv is as follows:
<pre> $ <b>pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-any.whl</b></pre>
If you encounter installation problems, see
[Common Installation Problems](#common-installation-problems).
@ -210,7 +230,7 @@ take the following steps:
issue the following command:
<pre> $ <b>sudo pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc0-py2-none-any.whl</b> </pre>
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-any.whl</b> </pre>
If the preceding command fails, see
[installation problems](#common-installation-problems).
@ -319,7 +339,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
TensorFlow for Python 2.7:
<pre> (tensorflow)$ <b>pip install --ignore-installed --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc0-py2-none-any.whl</b></pre>
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-any.whl</b></pre>
<a name="ValidateYourInstallation"></a>
@ -492,7 +512,7 @@ This section documents the relevant values for Mac OS installations.
<pre>
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc0-py2-none-any.whl
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py2-none-any.whl
</pre>
@ -500,7 +520,7 @@ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc0-py2-none-a
<pre>
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc0-py3-none-any.whl
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.2.0rc1-py3-none-any.whl
</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.
For example, the following command will install the pip package
for TensorFlow 1.2.0rc0 on Linux:
for TensorFlow 1.2.0rc1 on Linux:
<pre>
$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.2.0rc0-py2-none-any.whl</b>
$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.2.0rc1-py2-none-any.whl</b>
</pre>
## 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
following command:
<pre>(tensorflow)C:\> <b>pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.0rc0-cp35-cp35m-win_amd64.whl</b> </pre>
<pre>(tensorflow)C:\> <b>pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.0rc1-cp35-cp35m-win_amd64.whl</b> </pre>
To install the GPU version of TensorFlow, enter the following command
(on a single line):
<pre>(tensorflow)C:\> <b>pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.2.0rc0-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-1.2.0rc1-cp35-cp35m-win_amd64.whl</b> </pre>
## Validate your installation

1
tensorflow/tools/docs/pretty_docs.py
View File

@ -58,6 +58,7 @@ def build_md_page(page_info):
def _build_function_page(page_info):
"""Given a FunctionPageInfo object Return the page as an md string."""
parts = [_Metadata(page_info.full_name).build_html()]
parts.append('# %s\n\n' % page_info.full_name)
parts.append('# %s\n\n' % page_info.full_name)

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.
# For pip, we will remove all '-' characters from this string, and use the
# result for pip.
_VERSION = '1.2.0-rc0'
_VERSION = '1.2.0-rc1'
REQUIRED_PACKAGES = [
'numpy >= 1.11.0',