def __getitem__()

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]