





from ...configuration_utils import PretrainedConfig


__A				:    str       =   {
    "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_			):
	UpperCAmelCase__					=			'''tapas'''
	def __init__(    self							,					_A=3_0_5_2_2							,					_A=7_6_8							,					_A=1_2							,					_A=1_2							,					_A=3_0_7_2							,					_A="gelu"							,					_A=0.1							,					_A=0.1							,					_A=1_0_2_4							,					_A=[3, 2_5_6, 2_5_6, 2, 2_5_6, 2_5_6, 1_0]							,					_A=0.02							,					_A=1E-12							,					_A=0							,					_A=10.0							,					_A=0							,					_A=1.0							,					_A=None							,					_A=1.0							,					_A=False							,					_A=None							,					_A=1.0							,					_A=1.0							,					_A=False							,					_A=False							,					_A="ratio"							,					_A=None							,					_A=None							,					_A=6_4							,					_A=3_2							,					_A=False							,					_A=True							,					_A=False							,					_A=False							,					_A=True							,					_A=False							,					_A=None							,					_A=None							,					**_A							,					):






				'''simple docstring'''







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

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

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

				# Aggregation hyperparameters
				UpperCAmelCase   		=				aggregation_labels
				UpperCAmelCase   		=				no_aggregation_label_index

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










def 						__SCREAMING_SNAKE_CASE  (				UpperCamelCase__			,			UpperCamelCase__			,			UpperCamelCase__ )  ->				int:







			'''simple docstring'''

			if exponent == 1:
						return base
			if exponent % 2 == 0:
						UpperCAmelCase   		=				_modexpt(UpperCamelCase__			,			exponent // 2			,			UpperCamelCase__ ) % modulo_value
						return (x * x) % modulo_value
			else:
						return (base * _modexpt(UpperCamelCase__			,			exponent - 1			,			UpperCamelCase__ )) % modulo_value





def 						__SCREAMING_SNAKE_CASE  (				UpperCamelCase__ = 1777			,			UpperCamelCase__ = 1855			,			UpperCamelCase__ = 8 )  ->				int:







			'''simple docstring'''

			UpperCAmelCase   		=				base
			for _ in range(1			,			UpperCamelCase__ ):
						UpperCAmelCase   		=				_modexpt(UpperCamelCase__			,			UpperCamelCase__			,			10**digits )

			return result


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



