嘉渊
2023-05-25 cefa8ff17e3e2f4a7745d15a59beef0a255fabfd
funasr/datasets/small_datasets/dataset.py
@@ -9,8 +9,7 @@
from typing import Collection
from typing import Dict
from typing import Mapping
from typing import Tuple
from typing import Union
from typing import Union, List, Tuple
import kaldiio
import numpy as np
@@ -110,7 +109,7 @@
            float_dtype: str = "float32",
            int_dtype: str = "long",
            dest_sample_rate: int = 16000,
            speed_perturb: tuple = None,
            speed_perturb: Union[list, tuple] = None,
            mode: str = "train",
    ):
        assert check_argument_types()
@@ -144,7 +143,7 @@
    def _build_loader(
            self, path: str, loader_type: str
    ) -> Mapping[str, Union[np.ndarray, torch.Tensor, str, numbers.Number]]:
    ) -> Mapping[str, Union[np.ndarray, torch.Tensor, str, List[int], numbers.Number]]:
        """Helper function to instantiate Loader.
        Args:
@@ -174,6 +173,19 @@
                        raise RuntimeError(f"{k} is duplicated ({path}:{linenum})")
                    text_loader[k] = v
            return text_loader
        elif loader_type == "text_int":
            text_int_loader = {}
            with open(path, "r", encoding="utf-8") as f:
                for linenum, line in enumerate(f, 1):
                    sps = line.rstrip().split(maxsplit=1)
                    if len(sps) == 1:
                        k, v = sps[0], ""
                    else:
                        k, v = sps
                    if k in text_int_loader:
                        raise RuntimeError(f"{k} is duplicated ({path}:{linenum})")
                    text_int_loader[k] = [int(i) for i in v.split()]
            return text_int_loader
        else:
            raise RuntimeError(f"Not supported: loader_type={loader_type}")