code: 
  
  
  
  
  
  
  class 					snake_case_							:
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
     class 					snake_case_							:
  
  
  
  
  
  
  
        """simple docstring"""
  
  
  
        __lowerCAmelCase      =						"""_prev""", """_data""", """_next"""
  
        def __init__(    self:	Dict   ,       snake_case__:	Optional[int]   ,       snake_case__:	Dict   ,       snake_case__:	Tuple	)  ->		List[Any]:
  
  
            """simple docstring"""
  
  
  
            _lowercase     =	link_p
            _lowercase     =	element
            _lowercase     =	link_n
  
        def 			SCREAMING_SNAKE_CASE__				(    self:	Dict	)  ->		Dict:
  
  
            """simple docstring"""
  
  
  
            return (
                f''' Prev -> {self._prev is not None}, Next -> {self._next is not None}'''
            )
  
  
  
  
  
  
     def __init__(    self:	Union[str, Any]	)  ->		List[Any]:
  
  
         """simple docstring"""
  
  
  
         _lowercase     =	self._Node(snake_case__   ,       snake_case__   ,       snake_case__	)
         _lowercase     =	self._Node(snake_case__   ,       snake_case__   ,       snake_case__	)
         _lowercase     =	self._trailer
         _lowercase     =	self._header
         _lowercase     =	0
  
     def __len__(    self:	Any	)  ->		Union[str, Any]:
  
  
         """simple docstring"""
  
  
  
         return self._size
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	Optional[Any]	)  ->		str:
  
  
         """simple docstring"""
  
  
  
         return self.__len__() == 0
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	Union[str, Any]   ,       snake_case__:	Optional[int]   ,       snake_case__:	Any   ,       snake_case__:	Dict	)  ->		Union[str, Any]:
  
  
         """simple docstring"""
  
  
  
         _lowercase     =	self._Node(snake_case__   ,       snake_case__   ,       snake_case__	)
         _lowercase     =	new_node
         _lowercase     =	new_node
         self._size += 1
         return self
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	List[str]   ,       snake_case__:	Any	)  ->		Any:
  
  
         """simple docstring"""
  
  
  
         _lowercase     =	node._prev
         _lowercase     =	node._next
  
         _lowercase     =	successor
         _lowercase     =	predecessor
         self._size -= 1
         _lowercase     =	node._data
         _lowercase     =	_lowercase     =	_lowercase     =	None
         del node
         return temp
  
  
  
  
  
  
  class 					snake_case_							(       _DoublyLinkedBase      ):
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	Union[str, Any]	)  ->		Optional[int]:
  
  
         """simple docstring"""
  
  
  
         if self.is_empty():
             raise Exception('List is empty'	)
         return self._header._next._data
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	Any	)  ->		Any:
  
  
         """simple docstring"""
  
  
  
         if self.is_empty():
             raise Exception('List is empty'	)
         return self._trailer._prev._data
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	Optional[int]   ,       snake_case__:	List[Any]	)  ->		Dict:
  
  
         """simple docstring"""
  
  
  
         return self._insert(self._header   ,       snake_case__   ,       self._header._next	)
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	str   ,       snake_case__:	Union[str, Any]	)  ->		int:
  
  
         """simple docstring"""
  
  
  
         return self._insert(self._trailer._prev   ,       snake_case__   ,       self._trailer	)
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	Dict	)  ->		Any:
  
  
         """simple docstring"""
  
  
  
         if self.is_empty():
             raise IndexError('remove_first from empty list'	)
         return self._delete(self._header._next	)
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	Union[str, Any]	)  ->		str:
  
  
         """simple docstring"""
  
  
  
         if self.is_empty():
             raise IndexError('remove_first from empty list'	)
         return self._delete(self._trailer._prev	)
  
style_context: 
  
  
  
  
  
  
  import argparse
  
  import torch
  
  from transformers import HubertConfig, HubertForSequenceClassification, WavaVecaFeatureExtractor, logging
  
  
  logging.set_verbosity_info()
  lowerCamelCase										=  logging.get_logger(__name__)
  
  lowerCamelCase										=  ['''UtteranceLevel''']
  @torch.no_grad()
  def        UpperCAmelCase      (   _lowercase,      _lowercase,      _lowercase,      _lowercase      ):
  
  
      '''simple docstring'''
  
  
  
      _lowercase     =	torch.load(_lowercase,      map_location='cpu'      )
      if checkpoint["Config"]["downstream_expert"]["modelrc"]["select"] not in SUPPORTED_MODELS:
          raise NotImplementedError(f'''The supported s3prl models are {SUPPORTED_MODELS}'''      )
  
      _lowercase     =	checkpoint['Downstream']
  
      _lowercase     =	HubertConfig.from_pretrained(_lowercase      )
      _lowercase     =	HubertForSequenceClassification.from_pretrained(_lowercase,      config=_lowercase      )
      _lowercase     =	WavaVecaFeatureExtractor.from_pretrained(
          _lowercase,      return_attention_mask=_lowercase,      do_normalize=_lowercase      )
  
      if hf_congfig.use_weighted_layer_sum:
          _lowercase     =	checkpoint['Featurizer']['weights']
  
      _lowercase     =	downstream_dict['projector.weight']
      _lowercase     =	downstream_dict['projector.bias']
      _lowercase     =	downstream_dict['model.post_net.linear.weight']
      _lowercase     =	downstream_dict['model.post_net.linear.bias']
  
      hf_feature_extractor.save_pretrained(_lowercase      )
      hf_model.save_pretrained(_lowercase      )
  
  
  if __name__ == "__main__":
     lowerCamelCase										=  argparse.ArgumentParser()
     parser.add_argument(
         '''--base_model_name''', default=None, type=str, help='''Name of the huggingface pretrained base model.'''
     )
     parser.add_argument('''--config_path''', default=None, type=str, help='''Path to the huggingface classifier config.''')
     parser.add_argument('''--checkpoint_path''', default=None, type=str, help='''Path to the s3prl checkpoint.''')
     parser.add_argument('''--model_dump_path''', default=None, type=str, help='''Path to the final converted model.''')
     lowerCamelCase										=  parser.parse_args()
     convert_saprl_checkpoint(args.base_model_name, args.config_path, args.checkpoint_path, args.model_dump_path)
  