






"""simple docstring"""





from ...configuration_utils import PretrainedConfig


UpperCamelCase_	:				List[Any]										= {
    """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      _lowercase (     lowerCAmelCase						):
      _a   :     Optional[Any]								=   '''tapas'''


      def __init__(    self				:	Tuple							,   a				:	Optional[int]=3_0_5_2_2							,   a				:	List[str]=7_6_8							,   a				:	str=1_2							,   a				:	List[str]=1_2							,   a				:	List[str]=3_0_7_2							,   a				:	Optional[int]="gelu"							,   a				:	Any=0.1							,   a				:	Optional[Any]=0.1							,   a				:	List[str]=1_0_2_4							,   a				:	List[Any]=[3, 2_5_6, 2_5_6, 2, 2_5_6, 2_5_6, 1_0]							,   a				:	Optional[Any]=0.0_2							,   a				:	List[Any]=1e-12							,   a				:	Union[str, Any]=0							,   a				:	Tuple=1_0.0							,   a				:	Any=0							,   a				:	int=1.0							,   a				:	Dict=None							,   a				:	int=1.0							,   a				:	Optional[Any]=False							,   a				:	List[str]=None							,   a				:	Dict=1.0							,   a				:	Optional[Any]=1.0							,   a				:	List[Any]=False							,   a				:	Any=False							,   a				:	Tuple="ratio"							,   a				:	List[str]=None							,   a				:	int=None							,   a				:	Tuple=6_4							,   a				:	Optional[int]=3_2							,   a				:	Optional[int]=False							,   a				:	int=True							,   a				:	Optional[Any]=False							,   a				:	Any=False							,   a				:	Tuple=True							,   a				:	List[Any]=False							,   a				:	List[Any]=None							,   a				:	Tuple=None							,   **a				:	int							,   ):





            """simple docstring"""







            super().__init__(pad_token_id=a							,   **a						)

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

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

            # Aggregation hyperparameters
            __snake_case      :    Optional[int]  			=aggregation_labels
            __snake_case      :    Dict  			=no_aggregation_label_index

            if isinstance(self.aggregation_labels							,   a						):
                  __snake_case      :    List[Any]  			={int(a						): v for k, v in aggregation_labels.items()}










"""simple docstring"""





def     __lowercase					(    a :				str       ,		a :				str )					->					str:
      __snake_case      :    int  			=len(a )
      __snake_case      :    int  			=len(a )
      __snake_case      :    int  			=(
          first_str_length if first_str_length > second_str_length else second_str_length
      )
      __snake_case      :    list  			=[]
      for char_count in range(a ):
            if char_count < first_str_length:
                  output_list.append(first_str[char_count] )
            if char_count < second_str_length:
                  output_list.append(second_str[char_count] )
      return "".join(a )


if __name__ == "__main__":
    print(alternative_string_arrange("""AB""", """XYZ"""), end=""" """)


