| | |
|---|
| | | def forward( |
|---|
| | | self, |
|---|
| | | input: torch.Tensor, |
|---|
| | | input_lengths: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]: |
|---|
| | | input_lengths) -> Tuple[torch.Tensor, torch.Tensor]: |
|---|
| | | batch_size = input.size(0) |
|---|
| | | feats = [] |
|---|
| | | feats_lens = [] |
|---|
| | |
|---|
| | | feats_lens.append(feat_length) |
|---|
| | | |
|---|
| | | feats_lens = torch.as_tensor(feats_lens) |
|---|
| | | feats_pad = pad_sequence(feats, |
|---|
| | | batch_first=True, |
|---|
| | | padding_value=0.0) |
|---|
| | | if batch_size == 1: |
|---|
| | | feats_pad = feats[0][None, :, :] |
|---|
| | | else: |
|---|
| | | feats_pad = pad_sequence(feats, |
|---|
| | | batch_first=True, |
|---|
| | | padding_value=0.0) |
|---|
| | | return feats_pad, feats_lens |
|---|
| | | |
|---|
| | | def forward_fbank( |
|---|
