pytorch-image-models/wandb/run-20250114_215233-jyi2f0ub/files/output.log

Scheduled epochs: 150 (epochs + cooldown_epochs). Warmup within epochs when warmup_prefix=False. LR stepped per epoch.
Traceback (most recent call last):
  File "/app/pytorch-image-models/train.py", line 1236, in <module>
    main()
  File "/app/pytorch-image-models/train.py", line 889, in main
    train_metrics = train_one_epoch(
  File "/app/pytorch-image-models/train.py", line 1084, in train_one_epoch
    loss = _forward()
  File "/app/pytorch-image-models/train.py", line 1051, in _forward
    output = model(input)
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 1643, in forward
    else self._run_ddp_forward(*inputs, **kwargs)
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 1459, in _run_ddp_forward
    return self.module(*inputs, **kwargs)  # type: ignore[index]
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
    return forward_call(*args, **kwargs)
  File "/app/pytorch-image-models/timm/models/resnet.py", line 637, in forward
    x = self.forward_head(x)
  File "/app/pytorch-image-models/timm/models/resnet.py", line 633, in forward_head
    return x if pre_logits else self.fc(x)
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 125, in forward
    return F.linear(input, self.weight, self.bias)
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 21.95 GiB of which 20.75 MiB is free. Process 196 has 0 bytes memory in use. Process 191 has 0 bytes memory in use. Process 2862 has 0 bytes memory in use. Including non-PyTorch memory, this process has 0 bytes memory in use. Of the allocated memory 5.20 GiB is allocated by PyTorch, and 81.85 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[rank0]: Traceback (most recent call last):
[rank0]:   File "/app/pytorch-image-models/train.py", line 1236, in <module>
[rank0]:     main()
[rank0]:   File "/app/pytorch-image-models/train.py", line 889, in main
[rank0]:     train_metrics = train_one_epoch(
[rank0]:   File "/app/pytorch-image-models/train.py", line 1084, in train_one_epoch
[rank0]:     loss = _forward()
[rank0]:   File "/app/pytorch-image-models/train.py", line 1051, in _forward
[rank0]:     output = model(input)
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 1643, in forward
[rank0]:     else self._run_ddp_forward(*inputs, **kwargs)
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 1459, in _run_ddp_forward
[rank0]:     return self.module(*inputs, **kwargs)  # type: ignore[index]
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/app/pytorch-image-models/timm/models/resnet.py", line 637, in forward
[rank0]:     x = self.forward_head(x)
[rank0]:   File "/app/pytorch-image-models/timm/models/resnet.py", line 633, in forward_head
[rank0]:     return x if pre_logits else self.fc(x)
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/home/user/.local/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 125, in forward
[rank0]:     return F.linear(input, self.weight, self.bias)
[rank0]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 21.95 GiB of which 20.75 MiB is free. Process 196 has 0 bytes memory in use. Process 191 has 0 bytes memory in use. Process 2862 has 0 bytes memory in use. Including non-PyTorch memory, this process has 0 bytes memory in use. Of the allocated memory 5.20 GiB is allocated by PyTorch, and 81.85 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)