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

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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

  				
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2 years ago

one year ago