




'''simple docstring'''





from ...configuration_utils import PretrainedConfig


UpperCamelCase_						:      Dict       =						{
    '''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    (						__lowerCAmelCase							):
     SCREAMING_SNAKE_CASE_							:   str       =       """tapas"""






     def __init__(			self ,_SCREAMING_SNAKE_CASE=30_522 ,_SCREAMING_SNAKE_CASE=768 ,_SCREAMING_SNAKE_CASE=12 ,_SCREAMING_SNAKE_CASE=12 ,_SCREAMING_SNAKE_CASE=3_072 ,_SCREAMING_SNAKE_CASE="gelu" ,_SCREAMING_SNAKE_CASE=0.1 ,_SCREAMING_SNAKE_CASE=0.1 ,_SCREAMING_SNAKE_CASE=1_024 ,_SCREAMING_SNAKE_CASE=[3, 256, 256, 2, 256, 256, 10] ,_SCREAMING_SNAKE_CASE=0.0_2 ,_SCREAMING_SNAKE_CASE=1e-12 ,_SCREAMING_SNAKE_CASE=0 ,_SCREAMING_SNAKE_CASE=10.0 ,_SCREAMING_SNAKE_CASE=0 ,_SCREAMING_SNAKE_CASE=1.0 ,_SCREAMING_SNAKE_CASE=None ,_SCREAMING_SNAKE_CASE=1.0 ,_SCREAMING_SNAKE_CASE=False ,_SCREAMING_SNAKE_CASE=None ,_SCREAMING_SNAKE_CASE=1.0 ,_SCREAMING_SNAKE_CASE=1.0 ,_SCREAMING_SNAKE_CASE=False ,_SCREAMING_SNAKE_CASE=False ,_SCREAMING_SNAKE_CASE="ratio" ,_SCREAMING_SNAKE_CASE=None ,_SCREAMING_SNAKE_CASE=None ,_SCREAMING_SNAKE_CASE=64 ,_SCREAMING_SNAKE_CASE=32 ,_SCREAMING_SNAKE_CASE=False ,_SCREAMING_SNAKE_CASE=True ,_SCREAMING_SNAKE_CASE=False ,_SCREAMING_SNAKE_CASE=False ,_SCREAMING_SNAKE_CASE=True ,_SCREAMING_SNAKE_CASE=False ,_SCREAMING_SNAKE_CASE=None ,_SCREAMING_SNAKE_CASE=None ,**_SCREAMING_SNAKE_CASE ,)							->      Dict:
          super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE ,**_SCREAMING_SNAKE_CASE   )

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

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

          # Aggregation hyperparameters
          _snake_case							=				aggregation_labels
          _snake_case							=				no_aggregation_label_index

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








'''simple docstring'''





def      __a     (       _UpperCamelCase:   int   )						->			str:

     """simple docstring"""




     if number > 0:
          raise ValueError("input must be a negative integer"   )
     _snake_case							=				len(bin(_UpperCamelCase   )[3:]   )
     _snake_case							=				bin(abs(_UpperCamelCase   ) - (1 << binary_number_length)   )[3:]
     _snake_case							=				(
         (
             "1"
             + "0" * (binary_number_length - len(_UpperCamelCase   ))
             + twos_complement_number
         )
         if number < 0
         else "0"
     )
     return "0b" + twos_complement_number


if __name__ == "__main__":
   import doctest

   doctest.testmod()


