| | |
| | | if badcase_flag: |
| | | continue |
| | | input_ids = torch.tensor(input_ids, dtype=torch.int64) # [: self.max_token_length] |
| | | attention_mask = torch.tensor([len(input_ids)], dtype=torch.int32) |
| | | attention_mask = torch.tensor([1] * len(input_ids), dtype=torch.int32) |
| | | labels = torch.tensor(labels, dtype=torch.int64) # [: self.max_token_length] |
| | | |
| | | fbank = speech[0, :, :] |
| | |
| | | if b < 2: |
| | | beg = 0 |
| | | logging.info( |
| | | f"Warning, b * t: {b * t} > {self.batch_size}, b: {b}, t: {t}, drop half data {idx}th, beg:{beg}" |
| | | f"Warning, b * t: {b * t} > {self.batch_size_scale_ratio_max} * {self.batch_size}, b: {b}, t: {t}, drop half data {idx}th, beg:{beg}" |
| | | ) |
| | | samples = samples[beg : beg + b : 2] |
| | | continue |