Collect feats. Args: speech: Speech audio tensor, shape (batch, time). speech_lengths: Length of each speech sample.
(
self, speech: torch.Tensor, speech_lengths: torch.Tensor
)
| 103 | return loss, stats, weight |
| 104 | |
| 105 | def collect_feats( |
| 106 | self, speech: torch.Tensor, speech_lengths: torch.Tensor |
| 107 | ) -> Dict[str, torch.Tensor]: |
| 108 | """Collect feats. |
| 109 | |
| 110 | Args: |
| 111 | speech: Speech audio tensor, shape (batch, time). |
| 112 | speech_lengths: Length of each speech sample. |
| 113 | """ |
| 114 | feats, feats_lengths = self._extract_feats(speech, speech_lengths) |
| 115 | return {"feats": feats, "feats_lengths": feats_lengths} |
| 116 | |
| 117 | def encode( |
| 118 | self, |
nothing calls this directly
no test coverage detected