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[Error: All translation engines failed for batch: MADLAD batch translation failed: CUDA out of memory. Tried to allocate 2.00 MiB. GPU 0 has a total capacity of 23.87 GiB of which 3.62 MiB is free. Process 3280094 has 228.00 MiB memory in use. Process 2050901 has 248.00 MiB memory in use. Process 3546551 has 828.00 MiB memory in use. Process 3546472 has 1.17 GiB memory in use. Process 3558261 has 2.10 GiB memory in use. Process 3546477 has 1.82 GiB memory in use. Process 3546475 has 1.20 GiB memory in use. Process 3546473 has 806.00 MiB memory in use. Process 3546553 has 1.13 GiB memory in use. Process 3557107 has 984.00 MiB memory in use. Process 3546545 has 1.19 GiB memory in use. Process 3546548 has 1.19 GiB memory in use. Process 3546476 has 778.00 MiB memory in use. Process 3595952 has 802.00 MiB memory in use. Including non-PyTorch memory, this process has 9.50 GiB memory in use. Of the allocated memory 9.26 GiB is allocated by PyTorch, and 70.67 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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[Error: All translation engines failed for batch: MADLAD batch translation failed: CUDA out of memory. Tried to allocate 2.00 MiB. GPU 0 has a total capacity of 23.87 GiB of which 3.62 MiB is free. Process 3280094 has 228.00 MiB memory in use. Process 2050901 has 248.00 MiB memory in use. Process 3546551 has 828.00 MiB memory in use. Process 3546472 has 1.17 GiB memory in use. Process 3558261 has 2.10 GiB memory in use. Process 3546477 has 1.82 GiB memory in use. Process 3546475 has 1.20 GiB memory in use. Process 3546473 has 806.00 MiB memory in use. Process 3546553 has 1.13 GiB memory in use. Process 3557107 has 984.00 MiB memory in use. Process 3546545 has 1.22 GiB memory in use. Process 3546548 has 1.19 GiB memory in use. Process 3546476 has 778.00 MiB memory in use. Process 3595952 has 802.00 MiB memory in use. Including non-PyTorch memory, this process has 9.47 GiB memory in use. Of the allocated memory 9.29 GiB is allocated by PyTorch, and 9.78 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)] [Error: All translation engines failed for batch: MADLAD batch translation failed: CUDA out of memory. Tried to allocate 2.00 MiB. GPU 0 has a total capacity of 23.87 GiB of which 3.62 MiB is free. Process 3280094 has 228.00 MiB memory in use. Process 2050901 has 248.00 MiB memory in use. Process 3546551 has 828.00 MiB memory in use. Process 3546472 has 1.17 GiB memory in use. Process 3558261 has 2.10 GiB memory in use. Process 3546477 has 1.82 GiB memory in use. Process 3546475 has 1.20 GiB memory in use. Process 3546473 has 842.00 MiB memory in use. Process 3546553 has 1.13 GiB memory in use. Process 3557107 has 984.00 MiB memory in use. Process 3546545 has 1.22 GiB memory in use. Process 3546548 has 1.19 GiB memory in use. Process 3546476 has 778.00 MiB memory in use. Process 3595952 has 802.00 MiB memory in use. Including non-PyTorch memory, this process has 9.44 GiB memory in use. Of the allocated memory 9.25 GiB is allocated by PyTorch, and 11.96 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)]

[Error: All translation engines failed for batch: MADLAD batch translation failed: CUDA out of memory. Tried to allocate 2.00 MiB. GPU 0 has a total capacity of 23.87 GiB of which 3.62 MiB is free. Process 3280094 has 228.00 MiB memory in use. Process 2050901 has 248.00 MiB memory in use. Process 3546551 has 828.00 MiB memory in use. Process 3546472 has 1.17 GiB memory in use. Process 3558261 has 2.10 GiB memory in use. Process 3546477 has 1.82 GiB memory in use. Process 3546475 has 1.20 GiB memory in use. Process 3546473 has 806.00 MiB memory in use. Process 3546553 has 1.13 GiB memory in use. Process 3557107 has 984.00 MiB memory in use. Process 3546545 has 1.19 GiB memory in use. Process 3546548 has 1.19 GiB memory in use. Process 3546476 has 778.00 MiB memory in use. Process 3595952 has 802.00 MiB memory in use. Including non-PyTorch memory, this process has 9.50 GiB memory in use. Of the allocated memory 9.31 GiB is allocated by PyTorch, and 18.08 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)]