


"""simple docstring"""







from ...configuration_utils import PretrainedConfig


a__				:							Optional[int]						=     {
    '''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  UpperCamelCase_	( UpperCamelCase):

	"""simple docstring"""





	snake_case__				:  List[str]    					=			"tapas"




	def __init__( self			:				int			,			UpperCAmelCase__			:				Any=3_0_5_2_2			,			UpperCAmelCase__			:				Dict=7_6_8			,			UpperCAmelCase__			:				Optional[Any]=1_2			,			UpperCAmelCase__			:				Optional[int]=1_2			,			UpperCAmelCase__			:				Any=3_0_7_2			,			UpperCAmelCase__			:				List[Any]="gelu"			,			UpperCAmelCase__			:				List[Any]=0.1			,			UpperCAmelCase__			:				List[str]=0.1			,			UpperCAmelCase__			:				str=1_0_2_4			,			UpperCAmelCase__			:				Dict=[3, 2_5_6, 2_5_6, 2, 2_5_6, 2_5_6, 1_0]			,			UpperCAmelCase__			:				Union[str, Any]=0.02			,			UpperCAmelCase__			:				Tuple=1E-12			,			UpperCAmelCase__			:				Any=0			,			UpperCAmelCase__			:				Any=10.0			,			UpperCAmelCase__			:				Dict=0			,			UpperCAmelCase__			:				str=1.0			,			UpperCAmelCase__			:				Union[str, Any]=None			,			UpperCAmelCase__			:				str=1.0			,			UpperCAmelCase__			:				Union[str, Any]=False			,			UpperCAmelCase__			:				Optional[int]=None			,			UpperCAmelCase__			:				Tuple=1.0			,			UpperCAmelCase__			:				Any=1.0			,			UpperCAmelCase__			:				Optional[int]=False			,			UpperCAmelCase__			:				str=False			,			UpperCAmelCase__			:				List[str]="ratio"			,			UpperCAmelCase__			:				Union[str, Any]=None			,			UpperCAmelCase__			:				List[Any]=None			,			UpperCAmelCase__			:				Optional[int]=6_4			,			UpperCAmelCase__			:				Any=3_2			,			UpperCAmelCase__			:				Optional[Any]=False			,			UpperCAmelCase__			:				List[Any]=True			,			UpperCAmelCase__			:				List[str]=False			,			UpperCAmelCase__			:				int=False			,			UpperCAmelCase__			:				Any=True			,			UpperCAmelCase__			:				List[Any]=False			,			UpperCAmelCase__			:				Optional[int]=None			,			UpperCAmelCase__			:				Any=None			,			**UpperCAmelCase__			:				Optional[int]			,			)       ->	List[str]:
						super().__init__(pad_token_id=UpperCAmelCase__			,			**UpperCAmelCase__   )

						# BERT hyperparameters (with updated max_position_embeddings and type_vocab_sizes)
						__SCREAMING_SNAKE_CASE						   =				vocab_size
						__SCREAMING_SNAKE_CASE						   =				hidden_size
						__SCREAMING_SNAKE_CASE						   =				num_hidden_layers
						__SCREAMING_SNAKE_CASE						   =				num_attention_heads
						__SCREAMING_SNAKE_CASE						   =				hidden_act
						__SCREAMING_SNAKE_CASE						   =				intermediate_size
						__SCREAMING_SNAKE_CASE						   =				hidden_dropout_prob
						__SCREAMING_SNAKE_CASE						   =				attention_probs_dropout_prob
						__SCREAMING_SNAKE_CASE						   =				max_position_embeddings
						__SCREAMING_SNAKE_CASE						   =				type_vocab_sizes
						__SCREAMING_SNAKE_CASE						   =				initializer_range
						__SCREAMING_SNAKE_CASE						   =				layer_norm_eps

						# Fine-tuning task hyperparameters
						__SCREAMING_SNAKE_CASE						   =				positive_label_weight
						__SCREAMING_SNAKE_CASE						   =				num_aggregation_labels
						__SCREAMING_SNAKE_CASE						   =				aggregation_loss_weight
						__SCREAMING_SNAKE_CASE						   =				use_answer_as_supervision
						__SCREAMING_SNAKE_CASE						   =				answer_loss_importance
						__SCREAMING_SNAKE_CASE						   =				use_normalized_answer_loss
						__SCREAMING_SNAKE_CASE						   =				huber_loss_delta
						__SCREAMING_SNAKE_CASE						   =				temperature
						__SCREAMING_SNAKE_CASE						   =				aggregation_temperature
						__SCREAMING_SNAKE_CASE						   =				use_gumbel_for_cells
						__SCREAMING_SNAKE_CASE						   =				use_gumbel_for_aggregation
						__SCREAMING_SNAKE_CASE						   =				average_approximation_function
						__SCREAMING_SNAKE_CASE						   =				cell_selection_preference
						__SCREAMING_SNAKE_CASE						   =				answer_loss_cutoff
						__SCREAMING_SNAKE_CASE						   =				max_num_rows
						__SCREAMING_SNAKE_CASE						   =				max_num_columns
						__SCREAMING_SNAKE_CASE						   =				average_logits_per_cell
						__SCREAMING_SNAKE_CASE						   =				select_one_column
						__SCREAMING_SNAKE_CASE						   =				allow_empty_column_selection
						__SCREAMING_SNAKE_CASE						   =				init_cell_selection_weights_to_zero
						__SCREAMING_SNAKE_CASE						   =				reset_position_index_per_cell
						__SCREAMING_SNAKE_CASE						   =				disable_per_token_loss

						# Aggregation hyperparameters
						__SCREAMING_SNAKE_CASE						   =				aggregation_labels
						__SCREAMING_SNAKE_CASE						   =				no_aggregation_label_index

						if isinstance(self.aggregation_labels			,			UpperCAmelCase__   ):
											__SCREAMING_SNAKE_CASE						   =				{int(UpperCAmelCase__   ): v for k, v in aggregation_labels.items()}


"""simple docstring"""





import os

_a		       =							{'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1_000}







def 	__a     (		__lowerCamelCase  ):
   UpperCAmelCase_					:					Union[str, Any]			     =    0

   UpperCAmelCase_					:					List[str]			     =    0
   while index < len(__lowerCamelCase  ) - 1:
      UpperCAmelCase_					:					Tuple			     =    SYMBOLS[numerals[index]]
      UpperCAmelCase_					:					List[str]			     =    SYMBOLS[numerals[index + 1]]
      if current_value < next_value:
         total_value -= current_value
      else:
         total_value += current_value
      index += 1
   total_value += SYMBOLS[numerals[index]]

   return total_value







def 	__a     (		__lowerCamelCase  ):
   UpperCAmelCase_					:					List[str]			     =    ""

   UpperCAmelCase_					:					Any			     =    num // 1000
   numerals += m_count * "M"
   num %= 1000

   UpperCAmelCase_					:					Any			     =    num // 100
   if c_count == 9:
      numerals += "CM"
      c_count -= 9
   elif c_count == 4:
      numerals += "CD"
      c_count -= 4
   if c_count >= 5:
      numerals += "D"
      c_count -= 5
   numerals += c_count * "C"
   num %= 100

   UpperCAmelCase_					:					str			     =    num // 10
   if x_count == 9:
      numerals += "XC"
      x_count -= 9
   elif x_count == 4:
      numerals += "XL"
      x_count -= 4
   if x_count >= 5:
      numerals += "L"
      x_count -= 5
   numerals += x_count * "X"
   num %= 10

   if num == 9:
      numerals += "IX"
      num -= 9
   elif num == 4:
      numerals += "IV"
      num -= 4
   if num >= 5:
      numerals += "V"
      num -= 5
   numerals += num * "I"

   return numerals







def 	__a     (		__lowerCamelCase = "/p089_roman.txt"  ):
   UpperCAmelCase_					:					int			     =    0

   with open(os.path.dirname(__lowerCamelCase  ) + roman_numerals_filename  ) as filea:
      UpperCAmelCase_					:					Optional[Any]			     =    filea.readlines()

   for line in lines:
      UpperCAmelCase_					:					Tuple			     =    line.strip()
      UpperCAmelCase_					:					Optional[Any]			     =    parse_roman_numerals(__lowerCamelCase  )
      UpperCAmelCase_					:					Tuple			     =    generate_roman_numerals(__lowerCamelCase  )
      savings += len(__lowerCamelCase  ) - len(__lowerCamelCase  )

   return savings


if __name__ == "__main__":
    print(f"""{solution() = }""")


