zhaomingwork
2023-05-19 b63e73ae4f5df9d4ed9fb0bee12ac2cc09d7f523
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
@@ -110,6 +109,8 @@
            float_dtype: str = "float32",
            int_dtype: str = "long",
            dest_sample_rate: int = 16000,
            speed_perturb: Union[list, tuple] = None,
            mode: str = "train",
    ):
        assert check_argument_types()
        if len(path_name_type_list) == 0:
@@ -123,6 +124,10 @@
        self.float_dtype = float_dtype
        self.int_dtype = int_dtype
        self.dest_sample_rate = dest_sample_rate
        self.speed_perturb = speed_perturb
        self.mode = mode
        if self.speed_perturb is not None:
            logging.info("Using speed_perturb: {}".format(speed_perturb))
        self.loader_dict = {}
        self.debug_info = {}
@@ -138,7 +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:
@@ -146,7 +151,9 @@
            loader_type:  loader_type. sound, npy, text, etc
        """
        if loader_type == "sound":
            loader = SoundScpReader(path, self.dest_sample_rate, normalize=True, always_2d=False)
            speed_perturb = self.speed_perturb if self.mode == "train" else None
            loader = SoundScpReader(path, self.dest_sample_rate, normalize=True, always_2d=False,
                                    speed_perturb=speed_perturb)
            return AdapterForSoundScpReader(loader, self.float_dtype)
        elif loader_type == "kaldi_ark":
            loader = kaldiio.load_scp(path)
@@ -166,6 +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}")