无法在g2.2xlarge实例上安装带有CUDA 8.0和Tensorflow 0.12的cuDNN 5.1.5-Java 学习之路

我采取的步骤如下 . 在 ./configure 步骤期间，除非我允许cuDNN版本（v5）的系统默认值而不是指定v5.1.5（如我所愿），否则我会收到一条错误消息，指出cuDNN的环境版本（v5）不会感到困惑 .

更重要的是，在通过第240行挖掘https://github.com/tensorflow/tensorflow/blob/master/third_party/gpus/cuda_configure.bzl之后，我不确定它将如何安装版本5.1.5 . 也许我看错了？

在任何情况下，有没有人有一个方法在g2.2xlarge实例上安装带有CUDA 8.0和Tensorflow 0.12的cuDNN 5.1.5？

谢谢！

步骤

遵循以下配置步骤：https://medium.com/@giltamari/tensorflow-getting-started-gpu-installation-on-ec2-9b9915d95d6f#.2hv67eeek（即最多但不包括： sudo apt-get update && sudo apt-get -y upgrade ）

熟悉自己：
http://expressionflow.com/2016/10/09/installing-tensorflow-on-an-aws-ec2-p2-gpu-instance/
http://ramhiser.com/2016/01/05/installing-tensorflow-on-an-aws-ec2-instance-with-gpu-support/
https://alliseesolutions.wordpress.com/2016/09/08/install-gpu-tensorflow-from-sources-w-ubuntu-16-04-and-cuda-8-0-rc/
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install -y build-essential git python-pip libfreetype6-dev libxft-dev libncurses-dev libopenblas-dev gfortran python-matplotlib libblas-dev liblapack-dev libatlas-base-dev python-dev python-pydot linux-headers-generic linux-image-extra-virtual unzip python-numpy swig python-pandas python-sklearn unzip wget pkg-config zip g++ zlib1g-dev libcurl3-dev
sudo pip install -U pip

wget https://developer.nvidia.com/compute/cuda/8.0/prod/local_installers/cuda-repo-ubuntu1604-8-0-local_8.0.44-1_amd64-deb
sudo dpkg -i cuda-repo-ubuntu1604-8-0-local_8.0.44-1_amd64-deb
rm cuda-repo-ubuntu1604-8-0-local_8.0.44-1_amd64-deb
sudo apt-get update
sudo apt-get install -y cuda

我们要下载并安装最新版本的cuDNN . 下载cuDNN需要登录NVIDIA开发者网站，因此我们无法使用wget来获取文件 . 从NVIDIA下载以下文件并将其上传到您的AWS实例 .
在linux上下载适用于CUDA 8.0的cuDNN 5.1
scp -i ssh-key.pem path / to / downloaded / cudnn ubuntu @ ec2 .us-west-1.compute.amazonaws.com：〜/
sudo tar -xzvf cudnn-8.0-linux-x64-v5.1.tgz
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*

在 ~/.bashrc 结尾处放下： export CUDA_HOME=/usr/local/cuda export CUDA_ROOT=/usr/local/cuda export PATH=$PATH:$CUDA_ROOT/bin export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_ROOT/lib64:$CUDA_ROOT/extras/CUPTI/lib64
source ~/.bashrc
sudo reboot

sudo add-apt-repository -y ppa:webupd8team/java
sudo apt-get update
echo debconf shared/accepted-oracle-license-v1-1 select true | sudo debconf- set-selections
echo debconf shared/accepted-oracle-license-v1-1 seen true | sudo debconf- set-selections
sudo apt-get install -y oracle-java8-installer
sudo apt-get install pkg-config zip g++ zlib1g-dev
scp https://github.com/bazelbuild/bazel/releases/download/0.3.2/bazel-0.3.2-installer-linux-x86_64.sh 从本地机器到ec2实例
chmod +x bazel-0.1.4-installer-linux-x86_64.sh
./bazel-0.1.4-installer-linux-x86_64.sh --user
rm bazel-0.1.4-installer-linux-x86_64.sh
bazel version

git clone --recurse-submodules https://github.com/tensorflow/tensorflow
cd tensorflow
TF_UNOFFICIAL_SETTING=1 ./configure
命中所有输入/默认值除外：
CUDA版本= 8.0，CUDA依赖= 3.0（k520 gpu）
bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
sudo pip install --upgrade /tmp/tensorflow_pkg/tensorflow-0.12.0rc1-cp27-cp27mu-linux_x86_64.whl