


"""simple docstring"""







from ...configuration_utils import PretrainedConfig


__lowercase    =				{
    """google/tapas-base-finetuned-sqa""": (
        """https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
    ),
    """google/tapas-base-finetuned-wtq""": (
        """https://huggingface.co/google/tapas-base-finetuned-wtq/resolve/main/config.json"""
    ),
    """google/tapas-base-finetuned-wikisql-supervised""": (
        """https://huggingface.co/google/tapas-base-finetuned-wikisql-supervised/resolve/main/config.json"""
    ),
    """google/tapas-base-finetuned-tabfact""": (
        """https://huggingface.co/google/tapas-base-finetuned-tabfact/resolve/main/config.json"""
    ),
}






class 						_A  (  _a  ):







    """simple docstring"""




    UpperCAmelCase	:							str     =	"""tapas"""






    def __init__( self    :   Optional[Any]    ,			__UpperCAmelCase    :   Any=30522    ,			__UpperCAmelCase    :   List[str]=768    ,			__UpperCAmelCase    :   Optional[int]=12    ,			__UpperCAmelCase    :   List[str]=12    ,			__UpperCAmelCase    :   List[str]=3072    ,			__UpperCAmelCase    :   Union[str, Any]="gelu"    ,			__UpperCAmelCase    :   Optional[int]=0.1    ,			__UpperCAmelCase    :   Union[str, Any]=0.1    ,			__UpperCAmelCase    :   Optional[int]=1024    ,			__UpperCAmelCase    :   Optional[Any]=[3, 256, 256, 2, 256, 256, 10]    ,			__UpperCAmelCase    :   Any=0.02    ,			__UpperCAmelCase    :   Dict=1e-12    ,			__UpperCAmelCase    :   Dict=0    ,			__UpperCAmelCase    :   Any=10.0    ,			__UpperCAmelCase    :   int=0    ,			__UpperCAmelCase    :   List[str]=1.0    ,			__UpperCAmelCase    :   Optional[Any]=None    ,			__UpperCAmelCase    :   Any=1.0    ,			__UpperCAmelCase    :   Any=False    ,			__UpperCAmelCase    :   Optional[Any]=None    ,			__UpperCAmelCase    :   Union[str, Any]=1.0    ,			__UpperCAmelCase    :   Optional[int]=1.0    ,			__UpperCAmelCase    :   Optional[Any]=False    ,			__UpperCAmelCase    :   List[str]=False    ,			__UpperCAmelCase    :   List[str]="ratio"    ,			__UpperCAmelCase    :   Tuple=None    ,			__UpperCAmelCase    :   Optional[int]=None    ,			__UpperCAmelCase    :   List[str]=64    ,			__UpperCAmelCase    :   Union[str, Any]=32    ,			__UpperCAmelCase    :   str=False    ,			__UpperCAmelCase    :   List[Any]=True    ,			__UpperCAmelCase    :   List[Any]=False    ,			__UpperCAmelCase    :   List[Any]=False    ,			__UpperCAmelCase    :   int=True    ,			__UpperCAmelCase    :   int=False    ,			__UpperCAmelCase    :   List[Any]=None    ,			__UpperCAmelCase    :   Optional[int]=None    ,			**__UpperCAmelCase    :   List[Any]    ,			):
      super().__init__(pad_token_id=__UpperCAmelCase    ,			**__UpperCAmelCase)

      # BERT hyperparameters (with updated max_position_embeddings and type_vocab_sizes)
      a						:		List[str]											=      vocab_size
      a						:		int											=      hidden_size
      a						:		int											=      num_hidden_layers
      a						:		Any											=      num_attention_heads
      a						:		Optional[int]											=      hidden_act
      a						:		Optional[int]											=      intermediate_size
      a						:		Optional[int]											=      hidden_dropout_prob
      a						:		Dict											=      attention_probs_dropout_prob
      a						:		Optional[Any]											=      max_position_embeddings
      a						:		Tuple											=      type_vocab_sizes
      a						:		Optional[int]											=      initializer_range
      a						:		List[str]											=      layer_norm_eps

      # Fine-tuning task hyperparameters
      a						:		List[Any]											=      positive_label_weight
      a						:		List[Any]											=      num_aggregation_labels
      a						:		Tuple											=      aggregation_loss_weight
      a						:		Union[str, Any]											=      use_answer_as_supervision
      a						:		Tuple											=      answer_loss_importance
      a						:		List[Any]											=      use_normalized_answer_loss
      a						:		Optional[Any]											=      huber_loss_delta
      a						:		int											=      temperature
      a						:		Optional[Any]											=      aggregation_temperature
      a						:		Dict											=      use_gumbel_for_cells
      a						:		Tuple											=      use_gumbel_for_aggregation
      a						:		List[str]											=      average_approximation_function
      a						:		List[Any]											=      cell_selection_preference
      a						:		int											=      answer_loss_cutoff
      a						:		Optional[Any]											=      max_num_rows
      a						:		List[str]											=      max_num_columns
      a						:		int											=      average_logits_per_cell
      a						:		Union[str, Any]											=      select_one_column
      a						:		Optional[Any]											=      allow_empty_column_selection
      a						:		List[Any]											=      init_cell_selection_weights_to_zero
      a						:		List[str]											=      reset_position_index_per_cell
      a						:		Optional[Any]											=      disable_per_token_loss

      # Aggregation hyperparameters
      a						:		int											=      aggregation_labels
      a						:		str											=      no_aggregation_label_index

      if isinstance(self.aggregation_labels    ,			__UpperCAmelCase):
        a						:		Tuple											=      {int(__UpperCAmelCase): v for k, v in aggregation_labels.items()}










"""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()






