code: 
  """simple docstring"""
  
  
  
  
  
  
  
  class     __a			:
  
  
  
  
  
  
  
         def __init__(					self							,lowerCamelCase_		):
  
  
  
            '''simple docstring'''
  
            _UpperCAmelCase   	=					data
            _UpperCAmelCase   	=					None
            _UpperCAmelCase   	=					None
  
  
  
  
  
  
  
         def __str__(					self		):
  
  
  
            '''simple docstring'''
  
            return f'''{self.data}'''
  
  
  
  
  
  
  class     __a			:
  
  
  
  
  
  
  
         def __init__(					self		):
  
  
  
            '''simple docstring'''
  
            _UpperCAmelCase   	=					None
            _UpperCAmelCase   	=					None
  
  
  
  
  
  
  
         def __iter__(					self		):
  
  
  
            '''simple docstring'''
  
            _UpperCAmelCase   	=					self.head
            while node:
               yield node.data
               _UpperCAmelCase   	=					node.next
  
  
  
  
  
  
  
         def __str__(					self		):
  
  
  
            '''simple docstring'''
  
            return "->".join([str(lowerCamelCase_		) for item in self]		)
  
  
  
  
  
  
  
         def __len__(					self		):
  
  
  
            '''simple docstring'''
  
            return sum(1 for _ in self		)
  
  
  
  
  
  
  
         def    _snake_case			(					self							,lowerCamelCase_		):
  
  
  
            '''simple docstring'''
  
            self.insert_at_nth(0							,lowerCamelCase_		)
  
  
  
  
  
  
  
         def    _snake_case			(					self							,lowerCamelCase_		):
  
  
  
            '''simple docstring'''
  
            self.insert_at_nth(len(self		)							,lowerCamelCase_		)
  
  
  
  
  
  
  
         def    _snake_case			(					self							,lowerCamelCase_							,lowerCamelCase_		):
  
  
  
            '''simple docstring'''
  
            _UpperCAmelCase   	=					len(self		)
  
            if not 0 <= index <= length:
               raise IndexError("list index out of range"		)
            _UpperCAmelCase   	=					Node(lowerCamelCase_		)
            if self.head is None:
               _UpperCAmelCase   	=					_UpperCAmelCase   	=					new_node
            elif index == 0:
               _UpperCAmelCase   	=					new_node
               _UpperCAmelCase   	=					self.head
               _UpperCAmelCase   	=					new_node
            elif index == length:
               _UpperCAmelCase   	=					new_node
               _UpperCAmelCase   	=					self.tail
               _UpperCAmelCase   	=					new_node
            else:
               _UpperCAmelCase   	=					self.head
               for _ in range(0							,lowerCamelCase_		):
                  _UpperCAmelCase   	=					temp.next
               _UpperCAmelCase   	=					new_node
               _UpperCAmelCase   	=					temp.previous
               _UpperCAmelCase   	=					temp
               _UpperCAmelCase   	=					new_node
  
  
  
  
  
  
  
         def    _snake_case			(					self		):
  
  
  
            '''simple docstring'''
  
            return self.delete_at_nth(0		)
  
  
  
  
  
  
  
         def    _snake_case			(					self		):
  
  
  
            '''simple docstring'''
  
            return self.delete_at_nth(len(self		) - 1		)
  
  
  
  
  
  
  
         def    _snake_case			(					self							,lowerCamelCase_		):
  
  
  
            '''simple docstring'''
  
            _UpperCAmelCase   	=					len(self		)
  
            if not 0 <= index <= length - 1:
               raise IndexError("list index out of range"		)
            _UpperCAmelCase   	=					self.head  # default first node
            if length == 1:
               _UpperCAmelCase   	=					_UpperCAmelCase   	=					None
            elif index == 0:
               _UpperCAmelCase   	=					self.head.next
               _UpperCAmelCase   	=					None
            elif index == length - 1:
               _UpperCAmelCase   	=					self.tail
               _UpperCAmelCase   	=					self.tail.previous
               _UpperCAmelCase   	=					None
            else:
               _UpperCAmelCase   	=					self.head
               for _ in range(0							,lowerCamelCase_		):
                  _UpperCAmelCase   	=					temp.next
               _UpperCAmelCase   	=					temp
               _UpperCAmelCase   	=					temp.previous
               _UpperCAmelCase   	=					temp.next
            return delete_node.data
  
  
  
  
  
  
  
         def    _snake_case			(					self							,lowerCamelCase_		):
  
  
  
            '''simple docstring'''
  
            _UpperCAmelCase   	=					self.head
  
            while current.data != data:  # Find the position to delete
               if current.next:
                  _UpperCAmelCase   	=					current.next
               else:  # We have reached the end an no value matches
                  raise ValueError("No data matching given value"		)
  
            if current == self.head:
               self.delete_head()
  
            elif current == self.tail:
               self.delete_tail()
  
            else:  # Before: 1 <--> 2(current) <--> 3
               _UpperCAmelCase   	=					current.next  # 1 --> 3
               _UpperCAmelCase   	=					current.previous  # 1 <--> 3
            return data
  
  
  
  
  
  
  
         def    _snake_case			(					self		):
  
  
  
            '''simple docstring'''
  
            return len(self		) == 0
  
  
  
  def 			__UpperCAmelCase		(		)     ->       None:
     _UpperCAmelCase   	=					DoublyLinkedList()
     assert linked_list.is_empty() is True
     assert str(a_				) == ""
  
     try:
        linked_list.delete_head()
        raise AssertionError  # This should not happen.
     except IndexError:
        assert True  # This should happen.
  
     try:
        linked_list.delete_tail()
        raise AssertionError  # This should not happen.
     except IndexError:
        assert True  # This should happen.
  
     for i in range(10				):
        assert len(a_				) == i
        linked_list.insert_at_nth(a_    ,  i + 1				)
     assert str(a_				) == "->".join(str(a_				) for i in range(1    ,  11				)				)
  
     linked_list.insert_at_head(0				)
     linked_list.insert_at_tail(11				)
     assert str(a_				) == "->".join(str(a_				) for i in range(0    ,  12				)				)
  
     assert linked_list.delete_head() == 0
     assert linked_list.delete_at_nth(9				) == 10
     assert linked_list.delete_tail() == 11
     assert len(a_				) == 9
     assert str(a_				) == "->".join(str(a_				) for i in range(1    ,  10				)				)
  
  
  if __name__ == "__main__":
    from doctest import testmod
  
    testmod()
  
  
style_context: 
  """simple docstring"""
  
  
  
  
  
  
  
  import argparse
  
  import torch
  
  from transformers import MraConfig, MraForMaskedLM
  def 			__UpperCAmelCase		(		a_			:		Any				)     ->       List[str]:
     if "model" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("model."    ,  ""				)
     if "norm1" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("norm1"    ,  "attention.output.LayerNorm"				)
     if "norm2" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("norm2"    ,  "output.LayerNorm"				)
     if "norm" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("norm"    ,  "LayerNorm"				)
     if "transformer" in orig_key:
        _UpperCAmelCase   	=					orig_key.split("."				)[0].split("_"				)[-1]
        _UpperCAmelCase   	=					orig_key.replace(F'''transformer_{layer_num}'''    ,  F'''encoder.layer.{layer_num}'''				)
     if "mha.attn" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("mha.attn"    ,  "attention.self"				)
     if "mha" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("mha"    ,  "attention"				)
     if "W_q" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("W_q"    ,  "self.query"				)
     if "W_k" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("W_k"    ,  "self.key"				)
     if "W_v" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("W_v"    ,  "self.value"				)
     if "ff.0" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("ff.0"    ,  "intermediate.dense"				)
     if "ff.2" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("ff.2"    ,  "output.dense"				)
     if "ff" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("ff"    ,  "output.dense"				)
     if "mlm_class" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("mlm.mlm_class"    ,  "cls.predictions.decoder"				)
     if "mlm" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("mlm"    ,  "cls.predictions.transform"				)
     if "backbone.backbone.encoders" in orig_key:
        _UpperCAmelCase   	=					orig_key.replace("backbone.backbone.encoders"    ,  "encoder.layer"				)
     if "cls" not in orig_key:
        _UpperCAmelCase   	=					"mra." + orig_key
  
     return orig_key
  def 			__UpperCAmelCase		(		a_			:		Any    ,  a_			:		Any				)     ->       List[str]:
     for key in orig_state_dict.copy().keys():
        _UpperCAmelCase   	=					orig_state_dict.pop(a_				)
  
        if ("pooler" in key) or ("sen_class" in key):
           continue
        else:
           _UpperCAmelCase   	=					val
  
     _UpperCAmelCase   	=					orig_state_dict["cls.predictions.decoder.bias"]
     _UpperCAmelCase   	=					torch.arange(a_				).expand((1, -1)				) + 2
  
     return orig_state_dict
  def 			__UpperCAmelCase		(		a_			:		int    ,  a_			:		Tuple    ,  a_			:		List[str]				)     ->       Any:
     _UpperCAmelCase   	=					torch.load(a_    ,  map_location="cpu"				)["model_state_dict"]
     _UpperCAmelCase   	=					MraConfig.from_json_file(a_				)
     _UpperCAmelCase   	=					MraForMaskedLM(a_				)
  
     _UpperCAmelCase   	=					convert_checkpoint_helper(config.max_position_embeddings    ,  a_				)
  
     print(model.load_state_dict(a_				)				)
     model.eval()
     model.save_pretrained(a_				)
  
     print(F'''Checkpoint successfuly converted. Model saved at {pytorch_dump_path}'''				)
  
  
  if __name__ == "__main__":
    SCREAMING_SNAKE_CASE_     				=   argparse.ArgumentParser()
    # Required parameters
    parser.add_argument(
        '--pytorch_model_path', default=None, type=str, required=True, help='Path to Mra pytorch checkpoint.'
    )
    parser.add_argument(
        '--config_file',
        default=None,
        type=str,
        required=True,
        help='The json file for Mra model config.',
    )
    parser.add_argument(
        '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
    )
    SCREAMING_SNAKE_CASE_     				=   parser.parse_args()
    convert_mra_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)
  
  