theano 安装 (windows 64bit python 2)

Posted 2023-02-23

【中文标题】theano 安装 (windows 64bit python 2)

【英文标题】：theano installation (windows 64bit python 2)

【发布时间】：2015-05-07 11:34:07

【问题描述】：

我开始安装 theano。

我的电脑规格： - 操作系统：Windows 7 64 位 - 显卡：NVIDIA Geforce GT 630 - CPU : AMD FX-8120

我通过 deeplearning.net 的安装指南安装了 theano。 (http://deeplearning.net/software/theano/install_windows.html#configure-theano-for-gpu-use)

我成功完成了下的安装过程。

Visual Studio 2010 -> Windows 软件开发工具包版本 7.1 -> CUDA -> Microsoft Visual C++ Complier for Python 2.7（添加头文件）-> TDM GCC -> WinPython-64bit-2.7.9.4 -> env.bat -> Theano 设置

当我创建一个测试文件（下）并测试它时，它成功执行。

-------测试文件-----------------------------------

import numpy as np
import time
import theano
A = np.random.rand(1000,10000).astype(theano.config.floatX)
B = np.random.rand(10000,1000).astype(theano.config.floatX)
np_start = time.time()
AB = A.dot(B)
np_end = time.time()
X,Y = theano.tensor.matrices('XY')
mf = theano.function([X,Y],X.dot(Y))
t_start = time.time()
tAB = mf(A,B)
t_end = time.time()
print "NP time: %f[s], theano time: %f[s] (times should be close when run on CPU!)" %(np_end-np_start, t_end-t_start)
print "Result difference: %f" % (np.abs(AB-tAB).max(), )

---

但是当我添加 .theanorc.txt ---.theanorc.txt--------------------------------

[global]
device = gpu
floatX = float32

[nvcc]
flags = --use-local-env  --cl-version=2008

---

它给了我这样的错误（下）

https://www.dropbox.com/s/gjspcpaz4hkeep8/11.PNG?dl=0

我对 CUDA-devicequery 和 nvidia-smi.exe 没有任何问题

--------------设备查询--------------------- -----

C:\ProgramData\NVIDIA Corporation\CUDA Samples\v7.0\1_Utilities\deviceQuery\../../bin/win64/Debug/deviceQuery.exe Starting...

CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "GeForce GT 630"
  CUDA Driver Version / Runtime Version          7.0 / 7.0
  CUDA Capability Major/Minor version number:    2.1
  Total amount of global memory:                 512 MBytes (536870912 bytes)
  ( 2) Multiprocessors, ( 48) CUDA Cores/MP:     96 CUDA Cores
  GPU Max Clock rate:                            1620 MHz (1.62 GHz)
  Memory Clock rate:                             1600 Mhz
  Memory Bus Width:                              128-bit
  L2 Cache Size:                                 131072 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(65536), 2D=(65536, 65535),
3D=(2048, 2048, 2048)
  Maximum Layered 1D Texture Size, (num) layers  1D=(16384), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(16384, 16384), 2048 layers
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 32768
  Warp size:                                     32
  Maximum number of threads per multiprocessor:  1536
  Maximum number of threads per block:           1024
  Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
  Max dimension size of a grid size    (x,y,z): (65535, 65535, 65535)
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 1 copy engine(s)
  Run time limit on kernels:                     Yes
  Integrated GPU sharing Host Memory:            No
  Support host page-locked memory mapping:       Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support:                        Disabled
  CUDA Device Driver Mode (TCC or WDDM):         WDDM (Windows Display Driver Model)
  Device supports Unified Addressing (UVA):      Yes
  Device PCI Domain ID / Bus ID / location ID:   0 / 1 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 7.0, CUDA Runtime Version = 7.0, NumDevs = 1, Device0 = GeForce GT 630
Result = PASS

--------------nvidia-smi.exe------ ---------

Thu May 07 20:21:50 2015
+------------------------------------------------------+
| NVIDIA-SMI 347.62     Driver Version: 347.62         |
|-------------------------------+----------------------+----------------------+
| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GT 630     WDDM  | 0000:01:00.0     N/A |                  N/A |
| 50%   31C   P12    N/A /  N/A |    476MiB /   511MiB |     N/A      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage          |
|=============================================================================|
|    0              C   Not Supported                                             |
+-----------------------------------------------------------------------------+

请帮帮我..

【问题讨论】：

我将文件 ".theanorc.txt" 更改为 ".theanorc" 。谢谢你 。但它仍然有一个错误“没有检测到CUDA设备”。

【参考方案1】：

您应该使用“.theanorc”文件，而不是“.theanorc.txt”。

您也可以在 theano-users 群中写下您的问题：https://groups.google.com/forum/#!forum/theano-users

下一个 Winpython 版本将包含 theano+mingwpy，因此它可能会降低设置的复杂性。

【讨论】：

你的意思是“.theanorc”吗？它没有用....我只是将“.theanorc.txt”文件放在winpython/setting文件夹中...

实际上，Theano 官方文档声明您可以使用“.theanorc”或“.theanorc.txt”，它声称是“让 Windows 用户的生活更轻松”deeplearning.net/software/theano/library/config.html跨度>