TOLD/SOND: remove typeguard dependency. (#801)

funasr/datasets/collate_fn.py

@@ -6,8 +6,6 @@ from typing import Union
 
 import numpy as np
 import torch
-from typeguard import check_argument_types
-from typeguard import check_return_type
 from funasr.modules.nets_utils import pad_list, pad_list_all_dim
 
 
@@ -89,7 +87,6 @@ class DiarCollateFn:
             not_sequence: Collection[str] = (),
             max_sample_size=None
     ):
-        assert check_argument_types()
         self.float_pad_value = float_pad_value
         self.int_pad_value = int_pad_value
         self.not_sequence = set(not_sequence)
@@ -120,7 +117,6 @@ def diar_collate_fn(
 ) -> Tuple[List[str], Dict[str, torch.Tensor]]:
     """Concatenate ndarray-list to an array and convert to torch.Tensor.
     """
-    assert check_argument_types()
     uttids = [u for u, _ in data]
     data = [d for _, d in data]
 
@@ -146,7 +142,6 @@ def diar_collate_fn(
             output[key + "_lengths"] = lens
 
     output = (uttids, output)
-    assert check_return_type(output)
     return output
 
 

funasr/layers/label_aggregation.py

@@ -1,7 +1,6 @@
 import torch
 from typing import Optional
 from typing import Tuple
-from typeguard import check_argument_types
 from torch.nn import functional as F
 from funasr.modules.nets_utils import make_pad_mask
 
@@ -86,7 +85,6 @@ class LabelAggregateMaxPooling(torch.nn.Module):
         self,
         hop_length: int = 8,
     ):
-        assert check_argument_types()
         super().__init__()
 
         self.hop_length = hop_length

funasr/models/e2e_diar_sond.py

@@ -13,7 +13,6 @@ from typing import Tuple, List
 import numpy as np
 import torch
 from torch.nn import functional as F
-from typeguard import check_argument_types
 
 from funasr.modules.nets_utils import to_device
 from funasr.modules.nets_utils import make_pad_mask
@@ -69,7 +68,6 @@ class DiarSondModel(FunASRModel):
         freeze_encoder: bool = False,
         onfly_shuffle_speaker: bool = True,
     ):
-        assert check_argument_types()
 
         super().__init__()
 

funasr/tasks/diar.py

@@ -13,8 +13,6 @@ from typing import Union
 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 DiarCollateFn
 from funasr.datasets.preprocessor import CommonPreprocessor
@@ -341,7 +339,6 @@ class DiarTask(AbsTask):
         [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 DiarCollateFn(float_pad_value=0.0, int_pad_value=-1)
 
@@ -349,7 +346,6 @@ class DiarTask(AbsTask):
     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,
@@ -379,7 +375,6 @@ class DiarTask(AbsTask):
             )
         else:
             retval = None
-        assert check_return_type(retval)
         return retval
 
     @classmethod
@@ -398,7 +393,6 @@ class DiarTask(AbsTask):
             cls, train: bool = True, inference: bool = False
     ) -> Tuple[str, ...]:
         retval = ()
-        assert check_return_type(retval)
         return retval
 
     @classmethod
@@ -438,7 +432,6 @@ class DiarTask(AbsTask):
 
     @classmethod
     def build_model(cls, args: argparse.Namespace):
-        assert check_argument_types()
         if isinstance(args.token_list, str):
             with open(args.token_list, encoding="utf-8") as f:
                 token_list = [line.rstrip() for line in f]
@@ -546,7 +539,6 @@ class DiarTask(AbsTask):
             initialize(model, args.init)
             logging.info(f"Init model parameters with {args.init}.")
 
-        assert check_return_type(model)
         return model
 
     # ~~~~~~~~~ The methods below are mainly used for inference ~~~~~~~~~
@@ -569,7 +561,6 @@ class DiarTask(AbsTask):
             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 "