Linux安装Anaconda和cuda、cdnn和Tensorflow-gpu

总结 网址： http://blog.youkuaiyun.com/wolframalpha 作者： 李毅

全部看完在敲命令。先安装

Anaconda,在安装cuda和

cudnn,最后是tensorflow

安装tensorflow根据官网：

https://www.tensorflow.org/install/install_linux#installing_with_anaconda

上不了的同学可以到 ：

http://blog.youkuaiyun.com/wolframalpha/article/details/79096840

我已经把他复制下来了

给出的安装方法，共有5种安装方法。

• virtualenv
• "native" pip
• Docker
• Anaconda
• installing from sources, which is documented in a separate guide.

在这里， 选择 Anaconda安装 。

tensorflow有cpu版本和gpu版本，首先确定安装的版本。

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.
• 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.

NVIDIA 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 8.0. For details, see NVIDIA's documentation. Ensure that you append the relevant Cuda pathnames to the LD_LIBRARY_PATH