

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					(			snake_case_				):




      """simple docstring"""

      _lowerCamelCase       :			int      		=       'tapas'





      def __init__(   self							:				Optional[Any]						,			UpperCAmelCase							:				Dict=30522						,			UpperCAmelCase							:				List[str]=768						,			UpperCAmelCase							:				Tuple=12						,			UpperCAmelCase							:				List[Any]=12						,			UpperCAmelCase							:				Dict=3072						,			UpperCAmelCase							:				Tuple="gelu"						,			UpperCAmelCase							:				List[Any]=0.1						,			UpperCAmelCase							:				int=0.1						,			UpperCAmelCase							:				Tuple=1024						,			UpperCAmelCase							:				Dict=[3, 256, 256, 2, 256, 256, 10]						,			UpperCAmelCase							:				str=0.02						,			UpperCAmelCase							:				Union[str, Any]=1E-12						,			UpperCAmelCase							:				List[str]=0						,			UpperCAmelCase							:				Optional[int]=10.0						,			UpperCAmelCase							:				int=0						,			UpperCAmelCase							:				Any=1.0						,			UpperCAmelCase							:				List[Any]=None						,			UpperCAmelCase							:				Union[str, Any]=1.0						,			UpperCAmelCase							:				List[Any]=False						,			UpperCAmelCase							:				int=None						,			UpperCAmelCase							:				List[str]=1.0						,			UpperCAmelCase							:				Optional[int]=1.0						,			UpperCAmelCase							:				List[Any]=False						,			UpperCAmelCase							:				Tuple=False						,			UpperCAmelCase							:				List[str]="ratio"						,			UpperCAmelCase							:				List[str]=None						,			UpperCAmelCase							:				List[str]=None						,			UpperCAmelCase							:				Union[str, Any]=64						,			UpperCAmelCase							:				Optional[Any]=32						,			UpperCAmelCase							:				Tuple=False						,			UpperCAmelCase							:				List[str]=True						,			UpperCAmelCase							:				Optional[int]=False						,			UpperCAmelCase							:				Union[str, Any]=False						,			UpperCAmelCase							:				Tuple=True						,			UpperCAmelCase							:				Union[str, Any]=False						,			UpperCAmelCase							:				List[Any]=None						,			UpperCAmelCase							:				int=None						,			**UpperCAmelCase							:				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()}



__a	 =      256
# Modulus to hash a string
__a	 =      100_0003
def 	_UpperCamelCase					(    lowerCAmelCase_	,    lowerCAmelCase_ )    ->bool:
   UpperCAmelCase      					=  len(lowerCAmelCase_ )
   UpperCAmelCase      					=  len(lowerCAmelCase_ )
   if p_len > t_len:
      return False

   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  1

   # Calculating the hash of pattern and substring of text
   for i in range(lowerCAmelCase_ ):
      UpperCAmelCase      					=  (ord(pattern[i] ) + p_hash * alphabet_size) % modulus
      UpperCAmelCase      					=  (ord(text[i] ) + text_hash * alphabet_size) % modulus
      if i == p_len - 1:
         continue
      UpperCAmelCase      					=  (modulus_power * alphabet_size) % modulus

   for i in range(0	,    t_len - p_len + 1 ):
      if text_hash == p_hash and text[i : i + p_len] == pattern:
         return True
      if i == t_len - p_len:
         continue
      # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
      UpperCAmelCase      					=  (
          (text_hash - ord(text[i] ) * modulus_power) * alphabet_size
          + ord(text[i + p_len] )
      ) % modulus
   return False
def 	_UpperCamelCase					(    )    ->None:
   UpperCAmelCase      					=  """abc1abc12"""
   UpperCAmelCase      					=  """alskfjaldsabc1abc1abc12k23adsfabcabc"""
   UpperCAmelCase      					=  """alskfjaldsk23adsfabcabc"""
   assert rabin_karp(lowerCAmelCase_	,    lowerCAmelCase_ ) and not rabin_karp(lowerCAmelCase_	,    lowerCAmelCase_ )

   # Test 2)
   UpperCAmelCase      					=  """ABABX"""
   UpperCAmelCase      					=  """ABABZABABYABABX"""
   assert rabin_karp(lowerCAmelCase_	,    lowerCAmelCase_ )

   # Test 3)
   UpperCAmelCase      					=  """AAAB"""
   UpperCAmelCase      					=  """ABAAAAAB"""
   assert rabin_karp(lowerCAmelCase_	,    lowerCAmelCase_ )

   # Test 4)
   UpperCAmelCase      					=  """abcdabcy"""
   UpperCAmelCase      					=  """abcxabcdabxabcdabcdabcy"""
   assert rabin_karp(lowerCAmelCase_	,    lowerCAmelCase_ )

   # Test 5)
   UpperCAmelCase      					=  """Lü"""
   UpperCAmelCase      					=  """Lüsai"""
   assert rabin_karp(lowerCAmelCase_	,    lowerCAmelCase_ )
   UpperCAmelCase      					=  """Lue"""
   assert not rabin_karp(lowerCAmelCase_	,    lowerCAmelCase_ )
   print("""Success.""" )


if __name__ == "__main__":
 test_rabin_karp()



