


'''simple docstring'''
from ...configuration_utils import PretrainedConfig


lowerCAmelCase						=					{
    """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        lowerCAmelCase_  (     UpperCAmelCase	):
       __UpperCAmelCase					='tapas'






       def __init__( self			,     _UpperCamelCase=3_0522			,     _UpperCamelCase=768			,     _UpperCamelCase=12			,     _UpperCamelCase=12			,     _UpperCamelCase=3072			,     _UpperCamelCase="gelu"			,     _UpperCamelCase=0.1			,     _UpperCamelCase=0.1			,     _UpperCamelCase=1024			,     _UpperCamelCase=[3, 256, 256, 2, 256, 256, 10]			,     _UpperCamelCase=0.02			,     _UpperCamelCase=1e-12			,     _UpperCamelCase=0			,     _UpperCamelCase=10.0			,     _UpperCamelCase=0			,     _UpperCamelCase=1.0			,     _UpperCamelCase=None			,     _UpperCamelCase=1.0			,     _UpperCamelCase=False			,     _UpperCamelCase=None			,     _UpperCamelCase=1.0			,     _UpperCamelCase=1.0			,     _UpperCamelCase=False			,     _UpperCamelCase=False			,     _UpperCamelCase="ratio"			,     _UpperCamelCase=None			,     _UpperCamelCase=None			,     _UpperCamelCase=64			,     _UpperCamelCase=32			,     _UpperCamelCase=False			,     _UpperCamelCase=True			,     _UpperCamelCase=False			,     _UpperCamelCase=False			,     _UpperCamelCase=True			,     _UpperCamelCase=False			,     _UpperCamelCase=None			,     _UpperCamelCase=None			,     **_UpperCamelCase			,     )->      List[str]:
            super().__init__(pad_token_id=_UpperCamelCase			,     **_UpperCamelCase   )

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

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

            # Aggregation hyperparameters
            _A				=							aggregation_labels
            _A				=							no_aggregation_label_index

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









'''simple docstring'''
def 					lowerCamelCase_ ( __UpperCamelCase					:       int		)					->	bool:







     """simple docstring"""
     if num < 0:
          return False

     _A				=							num
     _A				=							0
     while num > 0:
          _A				=							rev_num * 1_0 + (num % 1_0)
          num //= 1_0

     return num_copy == rev_num


if __name__ == "__main__":
    import doctest

    doctest.testmod()





