




"""simple docstring"""







import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig

class 							snake_case_ (				lowerCamelCase_ ):







   """simple docstring"""




   A_										=					CustomConfig







   def __init__(		self					,				lowerCamelCase_)							->      List[Any]:
       super().__init__(lowerCamelCase_)
       UpperCamelCase										=  torch.nn.Linear(config.hidden_size					,				config.hidden_size)







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_)							->      Optional[Any]:
       return self.linear(lowerCamelCase_)







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_)							->      List[str]:
       pass

class 							snake_case_ (				lowerCamelCase_ ):







   """simple docstring"""




   A_										=					NoSuperInitConfig







   def __init__(		self					,				lowerCamelCase_)							->      Optional[int]:
       super().__init__(lowerCamelCase_)
       UpperCamelCase										=  torch.nn.Linear(config.attribute					,				config.attribute)







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_)							->      int:
       return self.linear(lowerCamelCase_)







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_)							->      Any:
       pass





"""simple docstring"""







from math import pi





def     __snake_case   (							_lowercase						):


    """simple docstring"""







    return degree / (180 / pi)


if __name__ == "__main__":
  from doctest import testmod

  testmod()