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perf-df-bnb-1xT4.csv

@@ -456,7 +456,7 @@ ChildProcessError: Traceback (most recent call last):
     return self._quantize(device)
   File ""/usr/local/lib/python3.10/dist-packages/bitsandbytes/nn/modules.py"", line 296, in _quantize
     w = self.data.contiguous().to(device)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 280.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 232.12 MiB is free. Process 23351 has 14.51 GiB memory in use. Of the allocated memory 14.07 GiB is allocated by PyTorch, and 332.11 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)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 280.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 232.12 MiB is free. Process 23071 has 14.51 GiB memory in use. Of the allocated memory 14.07 GiB is allocated by PyTorch, and 332.11 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
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@@ -4557,7 +4557,7 @@ ChildProcessError: Traceback (most recent call last):
     return self._quantize(device)
   File ""/usr/local/lib/python3.10/dist-packages/bitsandbytes/nn/modules.py"", line 296, in _quantize
     w = self.data.contiguous().to(device)
-torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 280.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 232.12 MiB is free. Process 21681 has 14.51 GiB memory in use. Of the allocated memory 14.07 GiB is allocated by PyTorch, and 332.11 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)
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 280.00 MiB. GPU 0 has a total capacity of 14.74 GiB of which 232.12 MiB is free. Process 21326 has 14.51 GiB memory in use. Of the allocated memory 14.07 GiB is allocated by PyTorch, and 332.11 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)
 
 ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
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