Python 在theano中使用CUDA8

我有CUDA8的工作安装，并且安装了theano，在导入theano时，它搜索CUDA7.5而不是CUDA8，如何告诉

theano

使用CUDA8而不是CUDA7.5

我的系统只有CUDA8，不包含混合环境cuda（即既有CUDA7.5又有CUDA8）

这是英伟达smi的输出

$ 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                                                 |

这里是

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，出现错误，无法找到

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

.theanoc

[global]                                                                                                                                                                                                       
floatX = float32
device = gpu0
cuda.root = /opt/cuda

在卸载以前安装的theano后，我试图从源代码构建它，但同样不起作用。我确实用

theano cache clean

/

theano cache purge

清除了theano缓存，并手动删除了

.theano

目录下的内容，这也帮不上忙

通过更多的调试，我在这里得到了错误

当

nvcc\u编译器

尝试加载无缓存中的

cuda\u ndarray.so

时

mod.cu的comiplation阶段运行无误

在这种情况下，链接器指向错误的

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

---

在进一步挖掘“我的问题”之后，我重构了我的原始问题，并将其发布在这里，从而解决了我的问题。

可能会检查.theanoc的内容，但可能需要根据源代码重新编译？我已检查了它（），但似乎没有关于它的选项“config.cuda.root”中是否有任何内容在.theanoc？yes@colinbeckham中，我尝试了这个，在我的例子中，

/opt/cuda

是我的安装目录。