[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 832.00 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 802.00 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 826.00 MiB memory in use. Process 3595952 has 850.00 MiB memory in use. Including non-PyTorch memory, this process has 9.38 GiB memory in use. Of the allocated memory 9.19 GiB is allocated by PyTorch, and 13.48 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 246.00 MiB memory in use. Process 3437459 has 1.57 GiB memory in use. Process 3437461 has 1.40 GiB memory in use. Process 3437456 has 1.33 GiB memory in use. Process 3437458 has 1.29 GiB memory in use. Process 3437454 has 1.57 GiB memory in use. Process 3437463 has 1.20 GiB memory in use. Process 3437467 has 1.35 GiB memory in use. Process 3437453 has 1.37 GiB memory in use. Process 3437449 has 1.37 GiB memory in use. Process 3437452 has 842.00 MiB memory in use. Process 3437450 has 232.00 MiB memory in use. Including non-PyTorch memory, this process has 9.44 GiB memory in use. Process 3529744 has 484.00 MiB memory in use. Of the allocated memory 9.15 GiB is allocated by PyTorch, and 121.96 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)]