| | |
| | | # force_gatherable: to-device and to-tensor if scalar for DataParallel |
| | | if self.length_normalized_loss: |
| | | batch_size = int((text_lengths + 1).sum()) |
| | | <<<<<<< HEAD:funasr/models/uniasr/e2e_uni_asr.py |
| | | |
| | | ======= |
| | | >>>>>>> main:funasr/models/e2e_uni_asr.py |
| | | loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device) |
| | | return loss, stats, weight |
| | | |
| | |
| | | speech_lengths: (Batch, ) |
| | | """ |
| | | # with autocast(False): |
| | | # # 1. Extract feats |
| | | # feats, feats_lengths = self._extract_feats(speech, speech_lengths) |
| | | # # 1. Extract feats |
| | | # feats, feats_lengths = self._extract_feats(speech, speech_lengths) |
| | | # |
| | | # # 2. Data augmentation |
| | | # if self.specaug is not None and self.training: |
| | | # feats, feats_lengths = self.specaug(feats, feats_lengths) |
| | | # # 2. Data augmentation |
| | | # if self.specaug is not None and self.training: |
| | | # feats, feats_lengths = self.specaug(feats, feats_lengths) |
| | | # |
| | | # # 3. Normalization for feature: e.g. Global-CMVN, Utterance-CMVN |
| | | # if self.normalize is not None: |
| | | # feats, feats_lengths = self.normalize(feats, feats_lengths) |
| | | # # 3. Normalization for feature: e.g. Global-CMVN, Utterance-CMVN |
| | | # if self.normalize is not None: |
| | | # feats, feats_lengths = self.normalize(feats, feats_lengths) |
| | | |
| | | # Pre-encoder, e.g. used for raw input data |
| | | # if self.preencoder is not None: |
| | | # feats, feats_lengths = self.preencoder(feats, feats_lengths) |
| | | # feats, feats_lengths = self.preencoder(feats, feats_lengths) |
| | | encoder_out_rm, encoder_out_lens_rm = self.encoder.overlap_chunk_cls.remove_chunk( |
| | | encoder_out, |
| | | encoder_out_lens, |
| | |
| | | |
| | | # # Post-encoder, e.g. NLU |
| | | # if self.postencoder is not None: |
| | | # encoder_out, encoder_out_lens = self.postencoder( |
| | | # encoder_out, encoder_out_lens |
| | | # ) |
| | | # encoder_out, encoder_out_lens = self.postencoder( |
| | | # encoder_out, encoder_out_lens |
| | | # ) |
| | | |
| | | assert encoder_out.size(0) == speech.size(0), ( |
| | | encoder_out.size(), |