这个堆栈跟踪告诉我我的 Tensorflow 安装有什么问题

Question

我已经完成并安装了 CUDA、cuDNN，并尽我所能按照说明进行操作。我已经添加了我认为需要的环境变量，但我似乎仍然有问题。

我已经测试过是否正确安装了 tensorflow。当打开命令提示符时，输入 python 以使用 shell，我输入 import tensorflow as tf。

然后我得到这个堆栈跟踪，这是我自己无法解决的问题。这就是我需要社区帮助的地方：

---

>>> import tensorflow as tf
Traceback (most recent call last):
  File "C:\Users\Troy\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\platform\self_check.py", line 75, in preload_check
    ctypes.WinDLL(build_info.cudart_dll_name)
  File"C:\Users\Troy\AppData\Local\Programs\Python\Python36\lib\ctypes\__init__.py", line 348, in __init__
    self._handle = _dlopen(self._name, mode)
OSError: [WinError 126] The specified module could not be found

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\Troy\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\__init__.py", line 24, in <module>
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
  File "C:\Users\Troy\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\__init__.py", line 49, in <module>
from tensorflow.python import pywrap_tensorflow
  File "C:\Users\Troy\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 30, in <module>
self_check.preload_check()
  File "C:\Users\Troy\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\platform\self_check.py", line 82, in preload_check
% (build_info.cudart_dll_name, build_info.cuda_version_number))
ImportError: Could not find 'cudart64_90.dll'. TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable. Download and install CUDA 9.0 from this URL: https://developer.nvidia.com/cuda-toolkit

Answer 1

请尝试安装 CUDA 9.0。问题应该出在 CUDA 9.1 版本上。您可以从以下链接下载驱动程序：CUDA Toolkit 9.0

要卸载 CUDA：

请运行以下命令：

 sudo apt-get --purge remove cuda
 sudo apt autoremove

这些命令应该能够从您的系统中卸载 cuda。

如果您将 cuDNN 配置为使用 GPU：

您可以在设置过程中删除它们，只需删除您复制到的目录中的文件即可。