Tensorflow(GPU) 在Win10+Cuda8.0环境下安装以及Cudnn包配置图文详细教程

安装环境

Win10
Python3.6.4 3.5以上版本都可以，目前Tensorflow只支持64位python3.5以上版本
numpy 安装好Python后打开终端cmd输入 pip3 install numpy ###具体流程

下载安装Cuda8.0，一定要是8.0版本！下载地址，并按照下图选择下载本地安装包。

如果安装错了记得要把之前的删除卸载干净

安装完成后配置系统环境变量Path TensorFlow 是一个编程系统, 使用图来表示计算任务，图必须在Session(会话)里被启动. Session将图的op(操作)分发到诸如CPU或GPU之类的设备上运行。所以，这个时候你运行python然后import tensorflow as tf是不会报错的，但是当你要执行tf.Session()的时候可能就有问题了。这个时候将会调用cuda，我在这里遇到的问题是各种lib,dll加载不了。经过一番检查，定位到问题，Cuda安装完成后默认的环境变量配置不对，不能直接访问到bin和libx64下的程序包，在path中加上这两个路径即可。

原本安装好之后并不会有以上四个环境变量，有两个需要自己加上。 C:Program FilesNVIDIA GPU Computing ToolkitCUDAv8.0 C:Program FilesNVIDIA GPU Computing ToolkitCUDAv8.0bin C:Program FilesNVIDIA GPU Computing ToolkitCUDAv8.0libx64 C:Program FilesNVIDIA GPU Computing ToolkitCUDAv8.0libnvvp 附配置环境变量教程最后在cmd里输入 echo %path% 就能查看你的是否添加进环境变量了

下载Cudnn6.0，下载地址，需要注册并填问卷，下载后解压压缩包，将包内文件夹里面的内容分别拷贝到C:Program FilesNVIDIA GPU Computing ToolkitCUDAv8.0里面的三个文件夹中去。

最后测试和检查一下，代码如下

代码语言：javascript复制

import ctypes  
import imp  
import sys  
  
  
def main():  
    try:  
        import tensorflow as tf  
        print("TensorFlow successfully installed.")  
        if tf.test.is_built_with_cuda():  
            print("The installed version of TensorFlow includes GPU support.")  
        else:  
            print("The installed version of TensorFlow does not include GPU support.")  
        sys.exit(0)  
    except ImportError:  
        print("ERROR: Failed to import the TensorFlow module.")  
  
    candidate_explanation = False  
  
    python_version = sys.version_info.major, sys.version_info.minor  
    print("n- Python version is %d.%d." % python_version)  
    if not (python_version == (3, 5) or python_version == (3, 6)):  
        candidate_explanation = True  
        print("- The official distribution of TensorFlow for Windows requires "  
              "Python version 3.5 or 3.6.")  
  
    try:  
        _, pathname, _ = imp.find_module("tensorflow")  
        print("n- TensorFlow is installed at: %s" % pathname)  
    except ImportError:  
        candidate_explanation = False  
        print(""" 
- No module named TensorFlow is installed in this Python environment. You may 
  install it using the command `pip install tensorflow`.""")  
  
    try:  
        msvcp140 = ctypes.WinDLL("msvcp140.dll")  
    except OSError:  
        candidate_explanation = True  
        print(""" 
- Could not load 'msvcp140.dll'. TensorFlow requires that this DLL be 
  installed in a directory that is named in your %PATH% environment 
  variable. You may install this DLL by downloading Microsoft Visual 
  C   2015 Redistributable Update 3 from this URL: 
  https://www.microsoft.com/en-us/download/details.aspx?id=53587""")  
  
    try:  
        cudart64_80 = ctypes.WinDLL("cudart64_80.dll")  
    except OSError:  
        candidate_explanation = True  
        print(""" 
- Could not load 'cudart64_80.dll'. The GPU version of TensorFlow 
  requires that this DLL be installed in a directory that is named in 
  your %PATH% environment variable. Download and install CUDA 8.0 from 
  this URL: https://developer.nvidia.com/cuda-toolkit""")  
  
    try:  
        nvcuda = ctypes.WinDLL("nvcuda.dll")  
    except OSError:  
        candidate_explanation = True  
        print(""" 
- Could not load 'nvcuda.dll'. The GPU version of TensorFlow requires that 
  this DLL be installed in a directory that is named in your %PATH% 
  environment variable. Typically it is installed in 'C:WindowsSystem32'. 
  If it is not present, ensure that you have a CUDA-capable GPU with the 
  correct driver installed.""")  
  
    cudnn5_found = False  
    try:  
        cudnn5 = ctypes.WinDLL("cudnn64_5.dll")  
        cudnn5_found = True  
    except OSError:  
        candidate_explanation = True  
        print(""" 
- Could not load 'cudnn64_5.dll'. The GPU version of TensorFlow 
  requires that this DLL be installed in a directory that is named in 
  your %PATH% environment variable. Note that installing cuDNN is a 
  separate step from installing CUDA, and it is often found in a 
  different directory from the CUDA DLLs. You may install the 
  necessary DLL by downloading cuDNN 5.1 from this URL: 
  https://developer.nvidia.com/cudnn""")  
  
    cudnn6_found = False  
    try:  
        cudnn = ctypes.WinDLL("cudnn64_6.dll")  
        cudnn6_found = True  
    except OSError:  
        candidate_explanation = True  
  
    if not cudnn5_found or not cudnn6_found:  
        print()  
        if not cudnn5_found and not cudnn6_found:  
            print("- Could not find cuDNN.")  
        elif not cudnn5_found:  
            print("- Could not find cuDNN 5.1.")  
        else:  
            print("- Could not find cuDNN 6.")  
            print(""" 
  The GPU version of TensorFlow requires that the correct cuDNN DLL be installed 
  in a directory that is named in your %PATH% environment variable. Note that 
  installing cuDNN is a separate step from installing CUDA, and it is often 
  found in a different directory from the CUDA DLLs. The correct version of 
  cuDNN depends on your version of TensorFlow: 
 
  * TensorFlow 1.2.1 or earlier requires cuDNN 5.1. ('cudnn64_5.dll') 
  * TensorFlow 1.3 or later requires cuDNN 6. ('cudnn64_6.dll') 
 
  You may install the necessary DLL by downloading cuDNN from this URL: 
  https://developer.nvidia.com/cudnn""")  
  
    if not candidate_explanation:  
        print(""" 
- All required DLLs appear to be present. Please open an issue on the 
  TensorFlow GitHub page: https://github.com/tensorflow/tensorflow/issues""")  
  
    sys.exit(-1)  
  
  
if __name__ == "__main__":  
    main()

如果失败的话记得检查一下报错信息，没有安装CUDA8.0或者环境配置不对：

Could not load ‘cudart64_80.dll’. The GPU version of TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable. Download and install CUDA 8.0 from this URL: https://developer.nvidia.com/cuda-toolkit

安装成功：

TensorFlow successfully installed. The installed version of TensorFlow includes GPU support.

注意几点

Cuba一定要安装8.0版本！Cuba一定要安装8.0版本！Cuba一定要安装8.0版本！
Anaconda并不是必需，可以使用可以不使用
Cudnn的版本我这里提示的是Cudnn6，大家看提示安装

后续

跑个DQN玩FlappyBird测试：源码在这里

tensorflow python numpy 深度学习

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Tensorflow(GPU) 在Win10+Cuda8.0环境下安装以及Cudnn包配置 图文详细教程

安装环境

注意几点

后续

Tensorflow(GPU) 在Win10+Cuda8.0环境下安装以及Cudnn包配置图文详细教程