环境使用内存的问题

[chiangandy]

我照配置使用small.json去配置，在4GPU每个GPU有8GB的环境去跑还是会出现既济体不够的问题

File "/home/ubuntu/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_transformers-1.0.0-py3.6.egg/pytorch_transformers/modeling_gpt2.py", line 100, in gelu
return 0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 * torch.pow(x, 3))))
RuntimeError: CUDA out of memory. Tried to allocate 24.00 MiB (GPU 0; 7.44 GiB total capacity; 6.88 GiB already allocated; 21.50 MiB free; 128.30 MiB cached)

我执行NVIDIA-smi
(pytorch_p36) ubuntu@ip-172-31-38-29:~/GPT2$ nvidia-smi
Wed Aug 14 06:03:59 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.67 Driver Version: 418.67 CUDA Version: 10.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla M60 On | 00000000:00:1B.0 Off | 0 |
| N/A 34C P8 23W / 150W | 0MiB / 7618MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 Tesla M60 On | 00000000:00:1C.0 Off | 0 |
| N/A 39C P8 22W / 150W | 0MiB / 7618MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 2 Tesla M60 On | 00000000:00:1D.0 Off | 0 |
| N/A 36C P8 22W / 150W | 0MiB / 7618MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 3 Tesla M60 On | 00000000:00:1E.0 Off | 0 |
| N/A 39C P8 22W / 150W | 0MiB / 7618MiB | 0% Default |
+-------------------------------+----------------------+----------------------+

确定每台有8GB GRAM, 但是为何看起来只使用到8G做配置

执行命令如下...
python3 train.py --raw --device="0,1,2,3"

这会是哪方面问题？

[Morizeyao]

把config_small.json里的参数再改小，直到可以放得下为止，现在还是太大了

[chiangandy]

我将batch_size设成4就可以过去(原先是8), 请问batch_size会影响输出的结果吗？

现在环境使用状况如下...
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.67 Driver Version: 418.67 CUDA Version: 10.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla M60 On | 00000000:00:1B.0 Off | 0 |
| N/A 61C P0 128W / 150W | 5633MiB / 7618MiB | 89% Default |
+-------------------------------+----------------------+----------------------+
| 1 Tesla M60 On | 00000000:00:1C.0 Off | 0 |
| N/A 74C P0 123W / 150W | 3857MiB / 7618MiB | 32% Default |
+-------------------------------+----------------------+----------------------+
| 2 Tesla M60 On | 00000000:00:1D.0 Off | 0 |
| N/A 65C P0 126W / 150W | 3857MiB / 7618MiB | 50% Default |
+-------------------------------+----------------------+----------------------+
| 3 Tesla M60 On | 00000000:00:1E.0 Off | 0 |
| N/A 73C P0 121W / 150W | 3857MiB / 7618MiB | 69% Default |
+-------------------------------+----------------------+----------------------+
我将batch_size调成4就可以过去
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 4291 C python3 5622MiB |
| 1 4291 C python3 3846MiB |
| 2 4291 C python3 3846MiB |
| 3 4291 C python3 3846MiB |
+-----------------------------------------------------------------------------+

[Morizeyao]

会有一点影响，但是就现在你的硬件条件看，能跑已经不错了，不用奢求太多

[chiangandy]

了解～感谢指导～