带有 CUDA 的 Tensorflow：导入错误

我已经按照 NVIDIA 教程中的说明一步步安装了 TensorFlow（Ubuntu 16.04 桌面版、GTX 970）：

http://www.nvidia.com/object/gpu-accelerated-applications-tensorflow-installation.html http://www.nvidia.com/object/gpu-accelerated-applications-tensorflow-installation.html

每个步骤都顺利完成，但如果我随后尝试在 Python 中导入 TensorFlow，我总是会收到此错误消息：

>>> import tensorflow as tf
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/__init__.py", line 24, in <module>
    from tensorflow.python import *
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/__init__.py", line 72, in <module>
    raise ImportError(msg)
ImportError: Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/__init__.py", line 61, in <module>
    from tensorflow.python import pywrap_tensorflow
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 28, in <module>
    _pywrap_tensorflow = swig_import_helper()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
ImportError: libcudart.so.8.0: cannot open shared object file: No such file or directory


Failed to load the native TensorFlow runtime.

See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md#import_error

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

我已将 CUDA-Toolkit 安装到 /opt/cuda/toolkit （也是 cuDNN）。 我已经尝试过符号链接：

sudo ln -s /opt/cuda-toolkit /usr/local/cuda
sudo ln -s /opt/cuda-toolkit /usr/local/cuda-8.0

Or this:

sudo export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/opt/cuda-toolkit/lib64:/opt/cuda-toolkit/extras/CUPTI/lib64
sudo export CUDA_HOME=/opt/cuda-toolkit

但错误仍然存​​在。有人能给我提示为什么会出现这个错误吗？ 多谢 ：）

我在具有类似硬件（GTX 970M）的机器上遇到了类似的问题，我使用以下帖子中提供的步骤解决了该问题：https://askubuntu.com/a/278840 https://askubuntu.com/a/278840

我的情况唯一的区别是在 nvidia.conf 文件中我仅添加了以下行： /usr/local/cuda-8.0/lib64

然后运行： sudo ldconfig

希望能帮助到你 ：）