| | |
| | | import numpy as np |
| | | import torch |
| | | import yaml |
| | | from typeguard import check_argument_types |
| | | from typeguard import check_return_type |
| | | |
| | | from funasr.datasets.collate_fn import CommonCollateFn |
| | | from funasr.layers.abs_normalize import AbsNormalize |
| | |
| | | [Collection[Tuple[str, Dict[str, np.ndarray]]]], |
| | | Tuple[List[str], Dict[str, torch.Tensor]], |
| | | ]: |
| | | assert check_argument_types() |
| | | # NOTE(kamo): int value = 0 is reserved by CTC-blank symbol |
| | | return CommonCollateFn(float_pad_value=0.0, int_pad_value=-1) |
| | | |
| | |
| | | def build_preprocess_fn( |
| | | cls, args: argparse.Namespace, train: bool |
| | | ) -> Optional[Callable[[str, Dict[str, np.array]], Dict[str, np.ndarray]]]: |
| | | assert check_argument_types() |
| | | # if args.use_preprocessor: |
| | | # retval = CommonPreprocessor( |
| | | # train=train, |
| | |
| | | # else: |
| | | # retval = None |
| | | retval = None |
| | | assert check_return_type(retval) |
| | | return retval |
| | | |
| | | @classmethod |
| | |
| | | cls, train: bool = True, inference: bool = False |
| | | ) -> Tuple[str, ...]: |
| | | retval = () |
| | | assert check_return_type(retval) |
| | | return retval |
| | | |
| | | @classmethod |
| | | def build_model(cls, args: argparse.Namespace): |
| | | assert check_argument_types() |
| | | # 4. Encoder |
| | | encoder_class = encoder_choices.get_class(args.encoder) |
| | | encoder = encoder_class(**args.encoder_conf) |
| | |
| | | device: Device type, "cpu", "cuda", or "cuda:N". |
| | | |
| | | """ |
| | | assert check_argument_types() |
| | | if config_file is None: |
| | | assert model_file is not None, ( |
| | | "The argument 'model_file' must be provided " |