Keras和GPU的使用

我使用的是Theano后端的keras 1.1.0。为了使用GPU，我将os.envorn设置为：Keras和GPU的使用

os.environ['THEANO_FLAGS'] = "device=gpu0"

在导入keras之前。导入keras给我以下信息：

Using gpu device 0: TITAN X (Pascal) (CNMeM is disabled, cuDNN 5105) 
/home/library_python/lib/python/Theano-0.8.2-py2.7.egg/theano/sandbox/cuda/__init__.py:600: UserWarning: Your cuDNN version is more recent than the one Theano officially supports. If you see any problems, try updating Theano or downgrading cuDNN to version 5. 
    warnings.warn(warn)

所以我认为我正确设置设备。但是，当我用keras训练模型时，nvidia-smi显示以下消息：

Fri May 5 13:05:33 2017 
+-----------------------------------------------------------------------------+ 
| NVIDIA-SMI 375.51     Driver Version: 375.51     | 
|-------------------------------+----------------------+----------------------+ 
| 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 GT 730  On | 0000:01:00.0  N/A |     N/A | 
| 30% 38C P8 N/A/N/A |  56MiB/ 980MiB |  N/A  Default | 
+-------------------------------+----------------------+----------------------+ 
| 1 TITAN X (Pascal) On | 0000:02:00.0  Off |     N/A | 
| 36% 63C P2 87W/250W | 373MiB/12189MiB |  35%  Default | 
+-------------------------------+----------------------+----------------------+ 
| 2 TITAN X (Pascal) On | 0000:03:00.0  Off |     N/A | 
| 23% 42C P8 18W/250W |  3MiB/12189MiB |  0%  Default | 
+-------------------------------+----------------------+----------------------+ 

+-----------------------------------------------------------------------------+ 
| Processes:              GPU Memory | 
| GPU  PID Type Process name        Usage  | 
|=============================================================================| 
| 0     Not Supported           | 
| 1  1520 C /usr/bin/python        155MiB | 
| 1  14996 C python           215MiB | 
+-----------------------------------------------------------------------------+

它说我只使用215MB的GPU内存。我期待更像10GB的使用。你能告诉我我做错了什么吗？我的GPU设备设置是否正确？

os.environ['THEANO_FLAGS'] = "device=gpu0,floatX=float32,lib.cnmem=1"

我现在用的11.7内存预期：

来源

2017-05-05 ThePrincess

的问题是改变Theano_flag为以后解决。

+-----------------------------------------------------------------------------+ 
| NVIDIA-SMI 375.51     Driver Version: 375.51     | 
|-------------------------------+----------------------+----------------------+ 
| 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 GT 730  On | 0000:01:00.0  N/A |     N/A | 
| 30% 38C P8 N/A/N/A |  56MiB/ 980MiB |  N/A  Default | 
+-------------------------------+----------------------+----------------------+ 
| 1 TITAN X (Pascal) On | 0000:02:00.0  Off |     N/A | 
| 28% 47C P2 78W/250W | 11923MiB/12189MiB |  0%  Default | 
+-------------------------------+----------------------+----------------------+ 
| 2 TITAN X (Pascal) On | 0000:03:00.0  Off |     N/A | 
| 23% 42C P8 18W/250W |  3MiB/12189MiB |  0%  Default | 
+-------------------------------+----------------------+----------------------+ 

+-----------------------------------------------------------------------------+ 
| Processes:              GPU Memory | 
| GPU  PID Type Process name        Usage  | 
|=============================================================================| 
| 0     Not Supported           | 
| 1  1520 C /usr/bin/python        155MiB | 
| 1  15543 C python          11765MiB | 
+-----------------------------------------------------------------------------+

来源

2017-05-05 20:27:51 ThePrincess

建议将cnmem剪切到'0.95'。 –

其实，我可以问一下，cnmem = 1在做什么？ – ThePrincess

它基本上预先分配GPU内存。它[观察]（https://datascience.stackexchange.com/questions/13381/how-does-the-cnmem-library-work-and-which-types-of-theano-models-does-it-speed）设置'cnmem'可以提高速度。但是，您不希望阻止GPU的所有内存，因此惯例是将其修剪为0.95。 –

Keras和GPU的使用

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