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I have added a training module and I noticed when forwarding the hourglass88 with torch.no_grad it works just fine but when removing torch.no_grad the gpu (12GB) run out of memory just by forwarding one image sample. I get this message:
RuntimeError: CUDA out of memory. Tried to allocate 46.00 MiB (GPU 0; 10.91 GiB total capacity; 10.21 GiB already allocated; 44.75 MiB free; 92.41 MiB cached).
It seems by the paper that you training not 1 but 4 images per mini-batch.
The text was updated successfully, but these errors were encountered:
I have added a training module and I noticed when forwarding the hourglass88 with torch.no_grad it works just fine but when removing torch.no_grad the gpu (12GB) run out of memory just by forwarding one image sample. I get this message:
RuntimeError: CUDA out of memory. Tried to allocate 46.00 MiB (GPU 0; 10.91 GiB total capacity; 10.21 GiB already allocated; 44.75 MiB free; 92.41 MiB cached).
It seems by the paper that you training not 1 but 4 images per mini-batch.
The text was updated successfully, but these errors were encountered: