ImportError: DLL load failed: 找不到指定的模块。

今年的软件杯中，我们比赛选题是关于深度学习的内容，在配置Pycharm里面引用电脑GPU时候出现“ImportError: DLL load failed: 找不到指定的模块。”的问题，我踩坑踩了很多，才找到的解决办法，分享一下：

首先说一下环境，我的配置是win10 + python3.6 + pycharm + tensorflow-gpu1.3 + CUDA8.0+cudnn-8.0-windows10-x64-v5.1

版本之间是有配置要求的，有的版本和版本之间是会出现问题的，所以在下载安装时候一定要看好自己电脑里面已有的配置，配置信息可以在https://github.com/fo40225/tensorflow-windows-wheel网址查看：

 

 

各个配置之间的版本都写得很好，可以进行下载，安装。

安装好以后，记得CUDA是要配置环境变量的，将cudnn里面的文件拷贝到CUDA文件路径下，安装时候，他会自己默认安装到C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0下

将下载好的cudnn里面文件放到相同文件夹名字下面就好。

然后在pycharm里面下载tensorflow-gpu，这里也要需要注意版本问题，下载好以后如果出现“ImportError: DLL load failed: 找不到指定的模块，就在https://github.com/fo40225/tensorflow-windows-wheel里面下载相应的wheel文件，然后cmd里面输入“pip install ”然后打开保存下载好whl文件的文件夹，将文件拖到cmd里面即可

然后回车就行。后面就会成功啦

这里给大家献上配置代码，直接pycharm里面运行，根据i下面的报错信息也好下载你需要的版本文件：

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:\Windows\System32'. 
  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()

　　在配置好以后，会出现gpu可以用的好消息啦。