import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig






class     __UpperCAmelCase(    A__				):






 """simple docstring"""




 __magic_name__          =   CustomConfig
 def __init__(    self ,       __magic_name__      ):

        """simple docstring"""

        super().__init__(__magic_name__      )
        A_							:       List[Any]	      =				torch.nn.Linear(config.hidden_size ,       config.hidden_size      )
 def  UpperCAmelCase   (    self ,       __magic_name__      ):

        """simple docstring"""

        return self.linear(__magic_name__      )
 def  UpperCAmelCase   (    self ,       __magic_name__      ):

        """simple docstring"""

        pass






class     __UpperCAmelCase(    A__				):






 """simple docstring"""




 __magic_name__          =   NoSuperInitConfig
 def __init__(    self ,       __magic_name__      ):

        """simple docstring"""

        super().__init__(__magic_name__      )
        A_							:       Any	      =				torch.nn.Linear(config.attribute ,       config.attribute      )
 def  UpperCAmelCase   (    self ,       __magic_name__      ):

        """simple docstring"""

        return self.linear(__magic_name__      )
 def  UpperCAmelCase   (    self ,       __magic_name__      ):

        """simple docstring"""

        pass



from transformers import ProcessorMixin






class     __UpperCAmelCase(    A__				):






 """simple docstring"""




 __magic_name__          =   """AutoFeatureExtractor"""
 __magic_name__          =   """AutoTokenizer"""


