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I test with 1:00 min wav file but it run out of GPU memory.
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 138.00 MiB (GPU 0; 5.93 GiB total capacity; 4.99 GiB already allocated; 126.19 MiB free; 5.08 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
How could I run with a larger file?
The text was updated successfully, but these errors were encountered:
For the large file, please try to split out your audio file (.wav) to be multi-parts(or files). In each part, should have maximum range of wav file to be 30 sec.
Then loop get the result or write into your output file, ex. :
os.environ['PYTORCH_CUDA_ALLOC_CONF'] ='max_split_size_mb:512'forfnameinos.listdir(audio_folder):
# Split your video into "temp_folder", # you should clear this directory before split the new onesplit_audio(audio_folder, fname, temp_folder)
# Loop get resultforwavfileinos.listdir(temp_folder):
torch.cuda.empty_cache()
result=asr(data=f'{temp_folder}/{wavfile}', model=model, sampling_rate=16_000)
print(result)
torch.cuda.empty_cache()
delos.environ['PYTORCH_CUDA_ALLOC_CONF']
I test with 1:00 min wav file but it run out of GPU memory.
How could I run with a larger file?
The text was updated successfully, but these errors were encountered: