diff options
Diffstat (limited to 'tensorflow/docs_src/install')
| -rw-r--r-- | tensorflow/docs_src/install/install_c.md | 2 | ||||
| -rw-r--r-- | tensorflow/docs_src/install/install_go.md | 2 | ||||
| -rw-r--r-- | tensorflow/docs_src/install/install_java.md | 24 | ||||
| -rw-r--r-- | tensorflow/docs_src/install/install_linux.md | 58 | ||||
| -rw-r--r-- | tensorflow/docs_src/install/install_mac.md | 10 | ||||
| -rw-r--r-- | tensorflow/docs_src/install/install_sources.md | 9 |
6 files changed, 67 insertions, 38 deletions
diff --git a/tensorflow/docs_src/install/install_c.md b/tensorflow/docs_src/install/install_c.md index 274413e294..995b8ae666 100644 --- a/tensorflow/docs_src/install/install_c.md +++ b/tensorflow/docs_src/install/install_c.md @@ -38,7 +38,7 @@ enable TensorFlow for C: OS="linux" # Change to "darwin" for macOS TARGET_DIRECTORY="/usr/local" curl -L \ - "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.7.0.tar.gz" | + "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.8.0-rc0.tar.gz" | sudo tar -C $TARGET_DIRECTORY -xz The `tar` command extracts the TensorFlow C library into the `lib` diff --git a/tensorflow/docs_src/install/install_go.md b/tensorflow/docs_src/install/install_go.md index 1a0956634d..2938a8f7ee 100644 --- a/tensorflow/docs_src/install/install_go.md +++ b/tensorflow/docs_src/install/install_go.md @@ -38,7 +38,7 @@ steps to install this library and enable TensorFlow for Go: TF_TYPE="cpu" # Change to "gpu" for GPU support TARGET_DIRECTORY='/usr/local' curl -L \ - "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.7.0.tar.gz" | + "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.8.0-rc0.tar.gz" | sudo tar -C $TARGET_DIRECTORY -xz The `tar` command extracts the TensorFlow C library into the `lib` diff --git a/tensorflow/docs_src/install/install_java.md b/tensorflow/docs_src/install/install_java.md index cdde45a6f4..05604d95c5 100644 --- a/tensorflow/docs_src/install/install_java.md +++ b/tensorflow/docs_src/install/install_java.md @@ -36,7 +36,7 @@ following to the project's `pom.xml` to use the TensorFlow Java APIs: <dependency> <groupId>org.tensorflow</groupId> <artifactId>tensorflow</artifactId> - <version>1.7.0</version> + <version>1.8.0-rc0</version> </dependency> ``` @@ -65,7 +65,7 @@ As an example, these steps will create a Maven project that uses TensorFlow: <dependency> <groupId>org.tensorflow</groupId> <artifactId>tensorflow</artifactId> - <version>1.7.0</version> + <version>1.8.0-rc0</version> </dependency> </dependencies> </project> @@ -93,6 +93,7 @@ As an example, these steps will create a Maven project that uses TensorFlow: // Execute the "MyConst" operation in a Session. try (Session s = new Session(g); + // Generally, there may be multiple output tensors, all of them must be closed to prevent resource leaks. Tensor output = s.runner().fetch("MyConst").run().get(0)) { System.out.println(new String(output.bytesValue(), "UTF-8")); } @@ -123,12 +124,12 @@ instead: <dependency> <groupId>org.tensorflow</groupId> <artifactId>libtensorflow</artifactId> - <version>1.7.0</version> + <version>1.8.0-rc0</version> </dependency> <dependency> <groupId>org.tensorflow</groupId> <artifactId>libtensorflow_jni_gpu</artifactId> - <version>1.7.0</version> + <version>1.8.0-rc0</version> </dependency> ``` @@ -147,7 +148,7 @@ refer to the simpler instructions above instead. Take the following steps to install TensorFlow for Java on Linux or macOS: 1. Download - [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.7.0.jar), + [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.8.0-rc0.jar), which is the TensorFlow Java Archive (JAR). 2. Decide whether you will run TensorFlow for Java on CPU(s) only or with @@ -166,7 +167,7 @@ Take the following steps to install TensorFlow for Java on Linux or macOS: OS=$(uname -s | tr '[:upper:]' '[:lower:]') mkdir -p ./jni curl -L \ - "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.7.0.tar.gz" | + "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.8.0-rc0.tar.gz" | tar -xz -C ./jni ### Install on Windows @@ -174,10 +175,10 @@ Take the following steps to install TensorFlow for Java on Linux or macOS: Take the following steps to install TensorFlow for Java on Windows: 1. Download - [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.7.0.jar), + [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.8.0-rc0.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_64-1.7.0.zip). + [TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.8.0-rc0.zip). 3. Extract this .zip file. @@ -207,6 +208,7 @@ public class HelloTF { // Execute the "MyConst" operation in a Session. try (Session s = new Session(g); + // Generally, there may be multiple output tensors, all of them must be closed to prevent resource leaks. Tensor output = s.runner().fetch("MyConst").run().get(0)) { System.out.println(new String(output.bytesValue(), "UTF-8")); } @@ -225,7 +227,7 @@ 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-1.7.0.jar HelloTF.java</b></pre> +<pre><b>javac -cp libtensorflow-1.8.0-rc0.jar HelloTF.java</b></pre> ### Running @@ -239,11 +241,11 @@ two files are available to the JVM: For example, the following command line executes the `HelloTF` program on Linux and macOS X: -<pre><b>java -cp libtensorflow-1.7.0.jar:. -Djava.library.path=./jni HelloTF</b></pre> +<pre><b>java -cp libtensorflow-1.8.0-rc0.jar:. -Djava.library.path=./jni HelloTF</b></pre> And the following command line executes the `HelloTF` program on Windows: -<pre><b>java -cp libtensorflow-1.7.0.jar;. -Djava.library.path=jni HelloTF</b></pre> +<pre><b>java -cp libtensorflow-1.8.0-rc0.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 diff --git a/tensorflow/docs_src/install/install_linux.md b/tensorflow/docs_src/install/install_linux.md index 04e4242b0f..1a349f5412 100644 --- a/tensorflow/docs_src/install/install_linux.md +++ b/tensorflow/docs_src/install/install_linux.md @@ -65,16 +65,38 @@ must be installed on your system: <pre> $ <b>sudo apt-get install libcupti-dev</b> </pre> + * **[OPTIONAL]** For optimized inferencing performance, you can also install - NVIDIA TensorRT 3.0. For details, see - [NVIDIA's TensorRT documentation](http://docs.nvidia.com/deeplearning/sdk/tensorrt-install-guide/index.html#installing-tar). - Only steps 1-4 in the TensorRT Tar File installation instructions are - required for compatibility with TensorFlow; the Python package installation - in steps 5 and 6 can be omitted. Detailed installation instructions can be found at [package documentataion](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/tensorrt#installing-tensorrt-304) + **NVIDIA TensorRT 3.0**. The minimal set of TensorRT runtime components needed + for use with the pre-built `tensorflow-gpu` package can be installed as follows: + + <pre> + $ <b>wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1404/x86_64/nvinfer-runtime-trt-repo-ubuntu1404-3.0.4-ga-cuda9.0_1.0-1_amd64.deb</b> + $ <b>sudo dpkg -i nvinfer-runtime-trt-repo-ubuntu1404-3.0.4-ga-cuda9.0_1.0-1_amd64.deb</b> + $ <b>sudo apt-get update</b> + $ <b>sudo apt-get install -y --allow-downgrades libnvinfer-dev libcudnn7-dev=7.0.5.15-1+cuda9.0 libcudnn7=7.0.5.15-1+cuda9.0</b> + </pre> **IMPORTANT:** For compatibility with the pre-built `tensorflow-gpu` - package, please use the Ubuntu **14.04** tar file package of TensorRT - even when installing onto an Ubuntu 16.04 system. + package, please use the Ubuntu **14.04** package of TensorRT as shown above, + even when installing onto an Ubuntu 16.04 system.<br/> + <br/> + To build the TensorFlow-TensorRT integration module from source rather than + using pre-built binaries, see the [module documentation](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/tensorrt#using-tensorrt-in-tensorflow). + For detailed TensorRT installation instructions, see [NVIDIA's TensorRT documentation](http://docs.nvidia.com/deeplearning/sdk/tensorrt-install-guide/index.html).<br/> + <br/> + To avoid cuDNN version conflicts during later system upgrades, you can hold + the cuDNN version at 7.0.5: + + <pre> + $ <b> sudo apt-mark hold libcudnn7 libcudnn7-dev</b> + </pre> + + To later allow upgrades, you can remove the hold: + + <pre> + $ <b> sudo apt-mark unhold libcudnn7 libcudnn7-dev</b> + </pre> If you have an earlier version of the preceding packages, please upgrade to the specified versions. If upgrading is not possible, then you may still run @@ -194,7 +216,7 @@ Take the following steps to install TensorFlow with Virtualenv: Virtualenv environment: <pre>(tensorflow)$ <b>pip3 install --upgrade \ - https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.7.0-cp34-cp34m-linux_x86_64.whl</b></pre> + https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc0-cp34-cp34m-linux_x86_64.whl</b></pre> If you encounter installation problems, see [Common Installation Problems](#common_installation_problems). @@ -299,7 +321,7 @@ take the following steps: <pre> $ <b>sudo pip3 install --upgrade \ - https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.7.0-cp34-cp34m-linux_x86_64.whl</b> + https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc0-cp34-cp34m-linux_x86_64.whl</b> </pre> If this step fails, see @@ -485,7 +507,7 @@ 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-1.7.0-cp34-cp34m-linux_x86_64.whl</b></pre> + https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc0-cp34-cp34m-linux_x86_64.whl</b></pre> <a name="ValidateYourInstallation"></a> ## Validate your installation @@ -659,14 +681,14 @@ This section documents the relevant values for Linux installations. CPU only: <pre> -https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.7.0-cp27-none-linux_x86_64.whl +https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc0-cp27-none-linux_x86_64.whl </pre> GPU support: <pre> -https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.7.0-cp27-none-linux_x86_64.whl +https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0rc0-cp27-none-linux_x86_64.whl </pre> Note that GPU support requires the NVIDIA hardware and software described in @@ -678,14 +700,14 @@ Note that GPU support requires the NVIDIA hardware and software described in CPU only: <pre> -https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.7.0-cp34-cp34m-linux_x86_64.whl +https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc0-cp34-cp34m-linux_x86_64.whl </pre> GPU support: <pre> -https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.7.0-cp34-cp34m-linux_x86_64.whl +https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0rc0-cp34-cp34m-linux_x86_64.whl </pre> Note that GPU support requires the NVIDIA hardware and software described in @@ -697,14 +719,14 @@ Note that GPU support requires the NVIDIA hardware and software described in CPU only: <pre> -https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.7.0-cp35-cp35m-linux_x86_64.whl +https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc0-cp35-cp35m-linux_x86_64.whl </pre> GPU support: <pre> -https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.7.0-cp35-cp35m-linux_x86_64.whl +https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0rc0-cp35-cp35m-linux_x86_64.whl </pre> @@ -716,14 +738,14 @@ Note that GPU support requires the NVIDIA hardware and software described in CPU only: <pre> -https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.7.0-cp36-cp36m-linux_x86_64.whl +https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0rc0-cp36-cp36m-linux_x86_64.whl </pre> GPU support: <pre> -https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.7.0-cp36-cp36m-linux_x86_64.whl +https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0rc0-cp36-cp36m-linux_x86_64.whl </pre> diff --git a/tensorflow/docs_src/install/install_mac.md b/tensorflow/docs_src/install/install_mac.md index b3e9616a05..a237d1af54 100644 --- a/tensorflow/docs_src/install/install_mac.md +++ b/tensorflow/docs_src/install/install_mac.md @@ -119,7 +119,7 @@ Take the following steps to install TensorFlow with Virtualenv: TensorFlow in the active Virtualenv is as follows: <pre> $ <b>pip3 install --upgrade \ - https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.7.0-py3-none-any.whl</b></pre> + https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc0-py3-none-any.whl</b></pre> If you encounter installation problems, see [Common Installation Problems](#common-installation-problems). @@ -242,7 +242,7 @@ take the following steps: issue the following command: <pre> $ <b>sudo pip3 install --upgrade \ - https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.7.0-py3-none-any.whl</b> </pre> + https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc0-py3-none-any.whl</b> </pre> If the preceding command fails, see [installation problems](#common-installation-problems). @@ -350,7 +350,7 @@ Take the following steps to install TensorFlow in an Anaconda environment: TensorFlow for Python 2.7: <pre> (<i>targetDirectory</i>)$ <b>pip install --ignore-installed --upgrade \ - https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.7.0-py2-none-any.whl</b></pre> + https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc0-py2-none-any.whl</b></pre> <a name="ValidateYourInstallation"></a> @@ -524,7 +524,7 @@ The value you specify depends on your Python version. <pre> -https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.7.0-py2-none-any.whl +https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc0-py2-none-any.whl </pre> @@ -532,5 +532,5 @@ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.7.0-py2-none-any. <pre> -https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.7.0-py3-none-any.whl +https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0rc0-py3-none-any.whl </pre> diff --git a/tensorflow/docs_src/install/install_sources.md b/tensorflow/docs_src/install/install_sources.md index 26287aa3a1..b186758653 100644 --- a/tensorflow/docs_src/install/install_sources.md +++ b/tensorflow/docs_src/install/install_sources.md @@ -354,10 +354,10 @@ 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 1.7.0 on Linux: +for TensorFlow 1.8.0rc0 on Linux: <pre> -$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.7.0-py2-none-any.whl</b> +$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.8.0rc0-py2-none-any.whl</b> </pre> ## Validate your installation @@ -454,6 +454,8 @@ Stack Overflow and specify the `tensorflow` tag. **Linux** <table> <tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr> +<tr><td>tensorflow-1.8.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.10.0</td><td>N/A</td><td>N/A</td></tr> +<tr><td>tensorflow_gpu-1.8.0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.9.0</td><td>7</td><td>9</td></tr> <tr><td>tensorflow-1.7.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.10.0</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow_gpu-1.7.0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.9.0</td><td>7</td><td>9</td></tr> <tr><td>tensorflow-1.6.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.9.0</td><td>N/A</td><td>N/A</td></tr> @@ -475,6 +477,7 @@ Stack Overflow and specify the `tensorflow` tag. **Mac** <table> <tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr> +<tr><td>tensorflow-1.8.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.10.1</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.7.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.10.1</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.6.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.8.1</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.5.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.8.1</td><td>N/A</td><td>N/A</td></tr> @@ -490,6 +493,8 @@ Stack Overflow and specify the `tensorflow` tag. **Windows** <table> <tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr> +<tr><td>tensorflow-1.8.0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr> +<tr><td>tensorflow_gpu-1.8.0</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>7</td><td>9</td></tr> <tr><td>tensorflow-1.7.0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow_gpu-1.7.0</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>7</td><td>9</td></tr> <tr><td>tensorflow-1.6.0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr> |