bins_per_octave = 12
n_octaves=9
hop_length=1148
cqt_transform = features.cqt.CQT2010v2(
sr=self.fs * 2,
hop_length=hop_length,
n_bins=bins_per_octave * n_octaves,
bins_per_octave=bins_per_octave,
output_format="Complex",
pad_mode="constant",
)
cqt_transform(torch.randn([4, 1, 24000*4]))