Hi, I'M Using Clearml'S Hosted Free Saas Offering. I'M Running Model Training In Pytorch On A Server And Pushing Metrics To Cml. I'Ve Noticed That Anytime My Training Job Fails Due To Gpu Oom Issues, Cml Marks The Job As

Unanswered

Sorry for the delay CostlyOstrich36 here's the relevant lines from the console:
... File "/home/binoyloaner/miniconda3/envs/DS974/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/home/binoyloaner/miniconda3/envs/DS974/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 103, in forward return F.linear(input, self.weight, self.bias) File "/home/binoyloaner/miniconda3/envs/DS974/lib/python3.8/site-packages/torch/nn/functional.py", line 1848, in linear return torch._C._nn.linear(input, weight, bias) RuntimeError: CUDA out of memory. Tried to allocate 748.00 MiB (GPU 0; 39.59 GiB total capacity; 34.67 GiB already allocated; 584.19 MiB free; 36.79 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONFThis is how my application crashes when I use a batch size too big for example.
This particular server is on Ubuntu 20.04

  				
Posted 
	2 years ago

					More
				  		
  Report
		
					JumpyClams73
				
					0
					 × 1

162 Views

0 Answers

2 years ago

one year ago