diff options
Diffstat (limited to 'tensorflow/docs_src/install/install_windows.md')
| -rw-r--r-- | tensorflow/docs_src/install/install_windows.md | 227 |
1 files changed, 0 insertions, 227 deletions
diff --git a/tensorflow/docs_src/install/install_windows.md b/tensorflow/docs_src/install/install_windows.md deleted file mode 100644 index 0bb0e5aeb9..0000000000 --- a/tensorflow/docs_src/install/install_windows.md +++ /dev/null @@ -1,227 +0,0 @@ -# Install TensorFlow on Windows - -This guide explains how to install TensorFlow on Windows. Although these -instructions might also work on other Windows variants, we have only -tested (and we only support) these instructions on machines meeting the -following requirements: - - * 64-bit, x86 desktops or laptops - * Windows 7 or later - - -## Determine which TensorFlow to install - -You must choose one of the following types of TensorFlow to install: - - * **TensorFlow with CPU support only**. If your system does not have a - NVIDIA® GPU, you must install this version. Note that this version of - TensorFlow is typically much easier to install (typically, - in 5 or 10 minutes), so even if you have an NVIDIA GPU, we recommend - installing this version first. Prebuilt binaries will use AVX instructions. - * **TensorFlow with GPU support**. TensorFlow programs typically run - significantly faster on a GPU than on a CPU. Therefore, if your - system has a NVIDIA® GPU meeting the prerequisites shown below - and you need to run performance-critical applications, you should - ultimately install this version. - -<a name="NVIDIARequirements"></a> - -### Requirements to run TensorFlow with GPU support - -If you are installing TensorFlow with GPU support using one of the mechanisms -described in this guide, then the following NVIDIA software must be -installed on your system: - - * CUDA® Toolkit 9.0. For details, see - [NVIDIA's - documentation](http://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/) - Ensure that you append the relevant Cuda pathnames to the `%PATH%` - environment variable as described in the NVIDIA documentation. - * The NVIDIA drivers associated with CUDA Toolkit 9.0. - * cuDNN v7.0. For details, see - [NVIDIA's documentation](https://developer.nvidia.com/cudnn). - Note that cuDNN is typically installed in a different location from the - other CUDA DLLs. Ensure that you add the directory where you installed - the cuDNN DLL to your `%PATH%` environment variable. - * GPU card with CUDA Compute Capability 3.0 or higher for building - from source and 3.5 or higher for our binaries. See - [NVIDIA documentation](https://developer.nvidia.com/cuda-gpus) for a - list of supported GPU cards. - -If you have a different version of one of the preceding packages, please -change to the specified versions. In particular, the cuDNN version -must match exactly: TensorFlow will not load if it cannot find `cuDNN64_7.dll`. -To use a different version of cuDNN, you must build from source. - -## Determine how to install TensorFlow - -You must pick the mechanism by which you install TensorFlow. The -supported choices are as follows: - - * "native" pip - * Anaconda - -Native pip installs TensorFlow directly on your system without going -through a virtual environment. Since a native pip installation is not -walled-off in a separate container, the pip installation might interfere -with other Python-based installations on your system. However, if you -understand pip and your Python environment, a native pip installation -often entails only a single command! Furthermore, if you install with -native pip, users can run TensorFlow programs from any directory on -the system. - -In Anaconda, you may use conda to create a virtual environment. -However, within Anaconda, we recommend installing TensorFlow with the -`pip install` command, not with the `conda install` command. - -**NOTE:** The conda package is community supported, not officially supported. -That is, the TensorFlow team neither tests nor maintains this conda package. -Use that package at your own risk. - - -## Installing with native pip - -If one of the following versions of Python is not installed on your machine, -install it now: - - * [Python 3.5.x 64-bit from python.org](https://www.python.org/downloads/release/python-352/) - * [Python 3.6.x 64-bit from python.org](https://www.python.org/downloads/release/python-362/) - -TensorFlow supports Python 3.5.x and 3.6.x on Windows. -Note that Python 3 comes with the pip3 package manager, which is the -program you'll use to install TensorFlow. - -To install TensorFlow, start a terminal. Then issue the appropriate -<tt>pip3 install</tt> command in that terminal. To install the CPU-only -version of TensorFlow, enter the following command: - -<pre>C:\> <b>pip3 install --upgrade tensorflow</b></pre> - -To install the GPU version of TensorFlow, enter the following command: - -<pre>C:\> <b>pip3 install --upgrade tensorflow-gpu</b></pre> - -## Installing with Anaconda - -**The Anaconda installation is community supported, not officially supported.** - -Take the following steps to install TensorFlow in an Anaconda environment: - - 1. Follow the instructions on the - [Anaconda download site](https://www.continuum.io/downloads) - to download and install Anaconda. - - 2. Create a conda environment named <tt>tensorflow</tt> - by invoking the following command: - - <pre>C:\> <b>conda create -n tensorflow pip python=3.5</b> </pre> - - 3. Activate the conda environment by issuing the following command: - - <pre>C:\> <b>activate tensorflow</b> - (tensorflow)C:\> # Your prompt should change </pre> - - 4. Issue the appropriate command to install TensorFlow inside your conda - environment. To install the CPU-only version of TensorFlow, enter the - following command: - - <pre>(tensorflow)C:\> <b>pip install --ignore-installed --upgrade tensorflow</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 tensorflow-gpu</b> </pre> - -## Validate your installation - -Start a terminal. - -If you installed through Anaconda, activate your Anaconda environment. - -Invoke python from your shell as follows: - -<pre>$ <b>python</b></pre> - -Enter the following short program inside the python interactive shell: - -```python ->>> import tensorflow as tf ->>> hello = tf.constant('Hello, TensorFlow!') ->>> sess = tf.Session() ->>> print(sess.run(hello)) -``` - -If the system outputs the following, then you are ready to begin writing -TensorFlow programs: - -<pre>Hello, TensorFlow!</pre> - -If the system outputs an error message instead of a greeting, see [Common -installation problems](#common_installation_problems). - -To learn more, see the [TensorFlow tutorials](../tutorials/). - -## Common installation problems - -We are relying on Stack Overflow to document TensorFlow installation problems -and their remedies. The following table contains links to Stack Overflow -answers for some common installation problems. -If you encounter an error message or other -installation problem not listed in the following table, search for it -on Stack Overflow. If Stack Overflow doesn't show the error message, -ask a new question about it on Stack Overflow and specify -the `tensorflow` tag. - -<table> -<tr> <th>Stack Overflow Link</th> <th>Error Message</th> </tr> - -<tr> - <td><a href="https://stackoverflow.com/q/41007279">41007279</a></td> - <td> - <pre>[...\stream_executor\dso_loader.cc] Couldn't open CUDA library nvcuda.dll</pre> - </td> -</tr> - -<tr> - <td><a href="https://stackoverflow.com/q/41007279">41007279</a></td> - <td> - <pre>[...\stream_executor\cuda\cuda_dnn.cc] Unable to load cuDNN DSO</pre> - </td> -</tr> - -<tr> - <td><a href="http://stackoverflow.com/q/42006320">42006320</a></td> - <td><pre>ImportError: Traceback (most recent call last): -File "...\tensorflow\core\framework\graph_pb2.py", line 6, in <module> -from google.protobuf import descriptor as _descriptor -ImportError: cannot import name 'descriptor'</pre> - </td> -</tr> - -<tr> - <td><a href="https://stackoverflow.com/q/42011070">42011070</a></td> - <td><pre>No module named "pywrap_tensorflow"</pre></td> -</tr> - -<tr> - <td><a href="https://stackoverflow.com/q/42217532">42217532</a></td> - <td> - <pre>OpKernel ('op: "BestSplits" device_type: "CPU"') for unknown op: BestSplits</pre> - </td> -</tr> - -<tr> - <td><a href="https://stackoverflow.com/q/43134753">43134753</a></td> - <td> - <pre>The TensorFlow library wasn't compiled to use SSE instructions</pre> - </td> -</tr> - -<tr> - <td><a href="https://stackoverflow.com/q/38896424">38896424</a></td> - <td> - <pre>Could not find a version that satisfies the requirement tensorflow</pre> - </td> -</tr> - -</table> |