| | |
| | | from funasr.modules.add_sos_eos import add_sos_eos |
| | | from funasr.modules.nets_utils import make_pad_mask, pad_list |
| | | from funasr.torch_utils.device_funcs import force_gatherable |
| | | from funasr.train.abs_espnet_model import AbsESPnetModel |
| | | from funasr.models.base_model import FunASRModel |
| | | from funasr.models.predictor.cif import CifPredictorV3 |
| | | |
| | | |
| | | if LooseVersion(torch.__version__) >= LooseVersion("1.6.0"): |
| | | from torch.cuda.amp import autocast |
| | |
| | | yield |
| | | |
| | | |
| | | class TimestampPredictor(AbsESPnetModel): |
| | | class TimestampPredictor(FunASRModel): |
| | | """ |
| | | Author: Speech Lab of DAMO Academy, Alibaba Group |
| | | """ |
| | |
| | | text_lengths: torch.Tensor, |
| | | ) -> Tuple[torch.Tensor, Dict[str, torch.Tensor], torch.Tensor]: |
| | | """Frontend + Encoder + Decoder + Calc loss |
| | | |
| | | Args: |
| | | speech: (Batch, Length, ...) |
| | | speech_lengths: (Batch, ) |
| | |
| | | self, speech: torch.Tensor, speech_lengths: torch.Tensor |
| | | ) -> Tuple[torch.Tensor, torch.Tensor]: |
| | | """Frontend + Encoder. Note that this method is used by asr_inference.py |
| | | |
| | | Args: |
| | | speech: (Batch, Length, ...) |
| | | speech_lengths: (Batch, ) |