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
Hello, I am using nnAudio to extract the CQT features of the audio in the following way
However, the problem is that when the amount of data requested is fixed, increasing concurrency causes memory to keep growing
