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Hello, I am using nnAudio to extract the CQT features of the audio in the following way
from nnAudio import features
cqt_layer = features.CQT2010v2(sr=16000).to(torch.device('cuda'))
data, sr = librosa.load(audio_file, sr=None)
with torch.no_grad():
data = torch.tensor(data, dtype=torch.float32).to(torch.device('cuda'))
cqt = cqt_layer(data)[0].cpu().numpy()
However, the problem is that when the amount of data requested is fixed, increasing concurrency causes memory to keep growing
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