


"""simple docstring"""







from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowercase    =				logging.get_logger(__name__)

__lowercase    =				{
    """microsoft/trocr-base-handwritten""": (
        """https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"""
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}






class 						_A  (  lowercase__  ):







    """simple docstring"""




    UpperCAmelCase	:							Dict     =	"""trocr"""
    UpperCAmelCase	:							str     =	["""past_key_values"""]
    UpperCAmelCase	:							str     =	{
        """num_attention_heads""": """decoder_attention_heads""",
        """hidden_size""": """d_model""",
        """num_hidden_layers""": """decoder_layers""",
    }






    def __init__( self    :   List[str]    ,			__UpperCAmelCase    :   str=50265    ,			__UpperCAmelCase    :   Dict=1024    ,			__UpperCAmelCase    :   Optional[Any]=12    ,			__UpperCAmelCase    :   Optional[Any]=16    ,			__UpperCAmelCase    :   str=4096    ,			__UpperCAmelCase    :   Optional[int]="gelu"    ,			__UpperCAmelCase    :   Union[str, Any]=512    ,			__UpperCAmelCase    :   List[str]=0.1    ,			__UpperCAmelCase    :   List[Any]=0.0    ,			__UpperCAmelCase    :   Optional[int]=0.0    ,			__UpperCAmelCase    :   Optional[Any]=2    ,			__UpperCAmelCase    :   Tuple=0.02    ,			__UpperCAmelCase    :   Union[str, Any]=0.0    ,			__UpperCAmelCase    :   int=True    ,			__UpperCAmelCase    :   int=False    ,			__UpperCAmelCase    :   List[str]=True    ,			__UpperCAmelCase    :   Any=True    ,			__UpperCAmelCase    :   Optional[int]=1    ,			__UpperCAmelCase    :   List[str]=0    ,			__UpperCAmelCase    :   str=2    ,			**__UpperCAmelCase    :   Optional[Any]    ,			):
      a						:		Optional[Any]											=      vocab_size
      a						:		Optional[Any]											=      d_model
      a						:		Optional[int]											=      decoder_layers
      a						:		Any											=      decoder_attention_heads
      a						:		Optional[int]											=      decoder_ffn_dim
      a						:		Any											=      activation_function
      a						:		int											=      max_position_embeddings
      a						:		Union[str, Any]											=      dropout
      a						:		List[Any]											=      attention_dropout
      a						:		List[Any]											=      activation_dropout
      a						:		List[str]											=      init_std
      a						:		Tuple											=      decoder_layerdrop
      a						:		Any											=      use_cache
      a						:		Union[str, Any]											=      scale_embedding
      a						:		Dict											=      use_learned_position_embeddings
      a						:		List[str]											=      layernorm_embedding

      super().__init__(
          pad_token_id=lowercase_    ,			bos_token_id=lowercase_    ,			eos_token_id=lowercase_    ,			decoder_start_token_id=lowercase_    ,			**lowercase_    ,			)










"""simple docstring"""







from __future__ import annotations






class 						_A  :







    """simple docstring"""




    def __init__( self    :   Tuple    ,			__UpperCAmelCase    :   List[Any]=None):
      a						:		int											=      data
      a						:		Dict											=      None






    def __repr__( self    :   Dict):
      a						:		List[Any]											=      []
      a						:		str											=      self
      while temp:
        string_rep.append(f'''{temp.data}''')
        a						:		Tuple											=      temp.next
      return "->".join(__UpperCAmelCase)






def 					lowercase      (    A_	)->				Any:
  '''simple docstring'''







  if not elements_list:
    raise Exception("The Elements List is empty"	)

  a						:		Any											=      Node(elements_list[0]	)
  for i in range(1  ,       len(A_	)	):
    a						:		int											=      Node(elements_list[i]	)
    a						:		Optional[Any]											=      current.next
  return head


def 					lowercase      (    A_	)->				None:
  '''simple docstring'''







  if head_node is not None and isinstance(A_  ,       A_	):
    print_reverse(head_node.next	)
    print(head_node.data	)


def 					lowercase      (    )->				List[Any]:
  '''simple docstring'''







  from doctest import testmod

  testmod()

  a						:		Union[str, Any]											=      make_linked_list([14, 52, 14, 12, 43]	)
  print("Linked List:"	)
  print(A_	)
  print("Elements in Reverse:"	)
  print_reverse(A_	)


if __name__ == "__main__":
 main()






