结果出现以下输出，说明配置成功
首先下载cuDNN5.1，直接下载是非常慢的，必须走代理，我用的是终端下载的方法，注意前提是你已经注册为开发者了！
proxychains wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v5.1/prod/8.0/cudnn-8.0-linux-x64-v5.1-tgz 这个会被forbidden，因为没有认证，开发者需要认证才能下载，你先用chrome下载，然后到show all里面去copy真实的下载地址 proxychains wget http://developer.download.nvidia.com/compute/machine-learning/cudnn/secure/v5.1/prod/8.0/cudnn-8.0-linux-x64-v5.1.tgz?autho=1479703345_7fbb517b03361780b45a2c43277bb9ac&file=cudnn-8.0-linux-x64-v5.1.tgz 这次成功了！！速度还可以！不过下载下来的文件名字有问题，修改成cudnn-8.0-linux-x64-v5.1.tgz就可以了 然后是解压 tar xvzf cudnn-8.0-linux-x64-v5.1.tgz 然后将库和头文件copy到cuda目录（一定是你自己安装的目录如/usr/local/cuda-8.0）,不过正确安装的话，ubuntu一般就会有软链接/usr/local/cuda -> /usr/local/cuda-8.0/ sudo cp cuda/include/cudnn.h /usr/local/cuda/include sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* 安装tensorflow gpu enable python 2.7 版本，详见 export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0-cp27-none-linux_x86_64.whl sudo pip install --upgrade $TF_BINARY_URL 验证 $python Python 2.7.12 (default, Jul 1 2016, 15:12:24) [GCC 5.4.0 20160609] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so locally I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcudnn.so locally I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so locally I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so locally >>> quit() 大功告成！ 错误