training, momentum, eps, torch.backends.cudnn.enabled

本文探讨了在使用CUDA 10.0时遇到的内存溢出问题(cuda_outofmemory),着重讲述了如何通过在DataParallel层添加BN层处理和调整batch size为1的解决方案,以及可能的原因——兼容性问题。

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出现cuda_out of memory,batch size 已设为1.

搜索可能是cuda10.0对8.0兼容性不好

根据网上修改的步骤

1. netG = nn.DataParallel(netG)

netG = netG.cuda() 在cuda()前添加torch.nn.DataParallel()

2. BN层问题,在报错代码添加

with torch.no_grad(): 
File "/home/zrb/anaconda3/envs/open-mmlab/bin/mmskl", line 7, in <module> exec(compile(f.read(), __file__, 'exec')) File "/home/zrb/mmskeleton/tools/mmskl", line 123, in <module> main() File "/home/zrb/mmskeleton/tools/mmskl", line 117, in main call_obj(**cfg.processor_cfg) File "/home/zrb/mmskeleton/mmskeleton/utils/importer.py", line 24, in call_obj return import_obj(type)(**kwargs) File "/home/zrb/mmskeleton/mmskeleton/processor/recognition.py", line 47, in test output = model(data) File "/home/zrb/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in __call__ result = self.forward(*input, **kwargs) File "/home/zrb/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 150, in forward return self.module(*inputs[0], **kwargs[0]) File "/home/zrb/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in __call__ result = self.forward(*input, **kwargs) File "/home/zrb/mmskeleton/mmskeleton/models/backbones/st_gcn_aaai18.py", line 94, in forward x = self.data_bn(x) File "/home/zrb/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in __call__ result = self.forward(*input, **kwargs) File "/home/zrb/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/batchnorm.py", line 81, in forward exponential_average_factor, self.eps) File "/home/zrb/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/functional.py", line 1656, in batch_norm training, momentum, eps, torch.backends.cudnn.enabled RuntimeError: running_mean should contain 60 elements not 54
07-25
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