Compose sox_effects and torchaudio.transforms #889
Description
I'd like to suggest a way of composing sox_effects with torchaudio.transforms. The latter is made of torch.nn.Module so they can be composed using torch.nn.Sequential. This would also follow the design pattern we established in torchaudio with transforms/functionals.
class SoxEffectsTransform(torch.nn.Module):
def __init__(self, effects, sample_rate):
self.effects = effects
self.sample_rate = sample_rate
def forward(self, tensor):
data, _ = torchaudio.sox_effects.apply_effects_tensor(tensor, self.sample_rate, self.effects)
return data
tensor, sample_rate = ...
effects = [
['gain', '-n', '-10'],
['speed', '0.5'], # duration of data is 0.5 seconds
['rate', f'{sample_rate}'],
['pad', '0', '1.5'], # add 1.5 seconds silence at the end
['trim', '0', '2'], # get the first 2 seconds
]
sox_effects_transform = SoxEffectsTransform(effects, sample_rate)
transform = torchaudio.transforms.Spectrogram()
torch.nn.Sequential(sox_effects_transform, transform)Would it be valuable to offer something like SoxEffectsTransform directly in torchaudio? It is currently in the docstring.