我已经安装了 CUDA8 并安装了 theano，在导入 theano 时它搜索 CUDA7.5 而不是 CUDA8，如何判断theano使用 CUDA8 而不是 CUDA7.5？
我的系统只有 CUDA8，它不包含混合环境 cuda（即同时具有 CUDA7.5 和 CUDA8）。
这是一个输出nvidia-smi
$ nvidia-smi
Sat Feb 4 11:32:30 2017
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 375.26 Driver Version: 375.26 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 970M Off | 0000:01:00.0 Off | N/A |
| N/A 54C P0 22W / N/A | 0MiB / 3016MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
这是一个输出nvcc -V
$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Sun_Sep__4_22:14:01_CDT_2016
Cuda compilation tools, release 8.0, V8.0.44
在 ipython 中导入 theano 时，它无法在 gpu 模式下运行，并出现错误，它找不到libcudart.so.7.5
Python 3.6.0 (default, Jan 16 2017, 12:12:55)
Type "copyright", "credits" or "license" for more information.
IPython 5.1.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
In [1]: import theano
ERROR (theano.sandbox.cuda): Failed to compile cuda_ndarray.cu: libcudart.so.7.5: cannot open shared object file: No such file or directory
WARNING (theano.sandbox.cuda): CUDA is installed, but device gpu0 is not available (error: cuda unavailable)
这是我的内容.theanorc
[global]
floatX = float32
device = gpu0
cuda.root = /opt/cuda
我尝试theano从源代码构建，在卸载之前的安装后，它也不起作用。theano-cache clean我确实使用/清除了 theano-cachetheano-cache purge并手动删除了.theano目录下的内容，这也无济于事。
随着更多的调试，我在这里得到错误 https://github.com/Theano/Theano/blob/8b9f73365e4932f1c005a0a37b907d28985fbc5f/theano/gof/cmodule.py#L302
当nvcc_compiler尝试在 theano 缓存中加载cuda_ndarray.sofromcuda_ndarray
mod.cu 的编译阶段运行没有错误。
在这种情况下，链接器指向错误libcudart
readelf -a cuda_ndarray.so | grep NEEDED
0x0000000000000001 (NEEDED) Shared library: [libcublas.so.8.0]
0x0000000000000001 (NEEDED) Shared library: [libpython3.6m.so.1.0]
0x0000000000000001 (NEEDED) Shared library: [libcudart.so.7.5]
0x0000000000000001 (NEEDED) Shared library: [librt.so.1]
0x0000000000000001 (NEEDED) Shared library: [libpthread.so.0]
0x0000000000000001 (NEEDED) Shared library: [libdl.so.2]
0x0000000000000001 (NEEDED) Shared library: [libstdc++.so.6]
0x0000000000000001 (NEEDED) Shared library: [libm.so.6]
0x0000000000000001 (NEEDED) Shared library: [libgcc_s.so.1]
0x0000000000000001 (NEEDED) Shared library: [libc.so.6]
我假设ldconfig正在正确缓存 cuda 库
$ sudo ldconfig -v | grep -e 'cuda\|blas'
/opt/cuda/lib64:
libcublas.so.8.0 -> libcublas.so.8.0.45
libcudart.so.8.0 -> libcudart.so.8.0.44
libnvblas.so.8.0 -> libnvblas.so.8.0.44
/opt/cuda/nvvm/lib64:
libcuda.so.1 -> libcuda.so.375.26
libblas.so.3 -> libblas.so.3.7.0
libicudata.so.58 -> libicudata.so.58.2
libopenblas.so.0 -> libopenblas.so
libicudata.so.58 -> libicudata.so.58.1