| | |
|---|
| | | # 0. sampler |
|---|
| | | decoder_out_1st = None |
|---|
| | | if self.sampling_ratio > 0.0: |
|---|
| | | if self.step_cur < 2: |
|---|
| | | logging.info("enable sampler in paraformer, sampling_ratio: {}".format(self.sampling_ratio)) |
|---|
| | | |
|---|
| | | sematic_embeds, decoder_out_1st = self.sampler(encoder_out, encoder_out_lens, ys_pad, ys_pad_lens, |
|---|
| | | pre_acoustic_embeds, contextual_info) |
|---|
| | | else: |
|---|
| | | if self.step_cur < 2: |
|---|
| | | logging.info("disable sampler in paraformer, sampling_ratio: {}".format(self.sampling_ratio)) |
|---|
| | | sematic_embeds = pre_acoustic_embeds |
|---|
| | | |
|---|
| | | # 1. Forward decoder |
|---|
| | |
|---|
| | | nbest_hyps = [Hypothesis(yseq=yseq, score=score)] |
|---|
| | | for nbest_idx, hyp in enumerate(nbest_hyps): |
|---|
| | | ibest_writer = None |
|---|
| | | if ibest_writer is None and kwargs.get("output_dir") is not None: |
|---|
| | | writer = DatadirWriter(kwargs.get("output_dir")) |
|---|
| | | ibest_writer = writer[f"{nbest_idx + 1}best_recog"] |
|---|
| | | if kwargs.get("output_dir") is not None: |
|---|
| | | if not hasattr(self, "writer"): |
|---|
| | | self.writer = DatadirWriter(kwargs.get("output_dir")) |
|---|
| | | ibest_writer = self.writer[f"{nbest_idx + 1}best_recog"] |
|---|
| | | |
|---|
| | | # remove sos/eos and get results |
|---|
| | | last_pos = -1 |
|---|
| | | if isinstance(hyp.yseq, list): |
|---|
