Tensorflow 安装注意事项

主要问题时 Tensorflow 对 GPU 加速的版本有兼容性要求

下表是主要对应关系

Tensorflow 版本	CPU/GPU	Python 版本	cuDNN	CUDA
tensorflow-1.8.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.8.0	GPU	2.7, 3.3-3.6	7	9
tensorflow-1.7.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.7.0	GPU	2.7, 3.3-3.6	7	9
tensorflow-1.6.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.6.0	GPU	2.7, 3.3-3.6	7	9
tensorflow-1.5.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.5.0	GPU	2.7, 3.3-3.6	7	9
tensorflow-1.4.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.4.0	GPU	2.7, 3.3-3.6	6	8
tensorflow-1.3.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.3.0	GPU	2.7, 3.3-3.6	6	8
tensorflow-1.2.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.2.0	GPU	2.7, 3.3-3.6	5.1	8
tensorflow-1.1.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.1.0	GPU	2.7, 3.3-3.6	5.1	8
tensorflow-1.0.0	CPU	2.7, 3.3-3.6	N/A	N/A
tensorflow_gpu-1.0.0	GPU	2.7, 3.3-3.6	5.1	8

安装固定版本的 tensorflow

pip install tensorflow_gpu==1.1.0

安装CUDA的注意事项：

环境变量需要自行配置

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\lib\x64
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\libnvvp

cuDNN 解压放到 CUDA\v8.0 目录中

检测python脚本

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()