in svoice/data/audio.py [0:0]
def __getitem__(self, index):
for (file, _), examples in zip(self.files, self.num_examples):
if index >= examples:
index -= examples
continue
num_frames = 0
offset = 0
if self.length is not None:
offset = self.stride * index
num_frames = self.length
# out = th.Tensor(sf.read(str(file), start=offset, frames=num_frames)[0]).unsqueeze(0)
out = torchaudio.load(str(file), offset=offset,
num_frames=num_frames)[0]
if self.augment:
out = self.augment(out.squeeze(0).numpy()).unsqueeze(0)
if num_frames:
out = F.pad(out, (0, num_frames - out.shape[-1]))
return out[0]