




from ...configuration_utils import PretrainedConfig


__a          =			{
    '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       ):






    """simple docstring"""





    lowerCAmelCase        =				'''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=0.02       ,_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       ,)			->		int:
         super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE       ,**_SCREAMING_SNAKE_CASE  )

         # BERT hyperparameters (with updated max_position_embeddings and type_vocab_sizes)
         UpperCAmelCase_      :							List[Any]       =      vocab_size
         UpperCAmelCase_      :							int       =      hidden_size
         UpperCAmelCase_      :							List[Any]       =      num_hidden_layers
         UpperCAmelCase_      :							Tuple       =      num_attention_heads
         UpperCAmelCase_      :							int       =      hidden_act
         UpperCAmelCase_      :							Optional[Any]       =      intermediate_size
         UpperCAmelCase_      :							Union[str, Any]       =      hidden_dropout_prob
         UpperCAmelCase_      :							List[str]       =      attention_probs_dropout_prob
         UpperCAmelCase_      :							List[Any]       =      max_position_embeddings
         UpperCAmelCase_      :							str       =      type_vocab_sizes
         UpperCAmelCase_      :							List[str]       =      initializer_range
         UpperCAmelCase_      :							Dict       =      layer_norm_eps

         # Fine-tuning task hyperparameters
         UpperCAmelCase_      :							Optional[Any]       =      positive_label_weight
         UpperCAmelCase_      :							str       =      num_aggregation_labels
         UpperCAmelCase_      :							List[Any]       =      aggregation_loss_weight
         UpperCAmelCase_      :							Dict       =      use_answer_as_supervision
         UpperCAmelCase_      :							Dict       =      answer_loss_importance
         UpperCAmelCase_      :							Any       =      use_normalized_answer_loss
         UpperCAmelCase_      :							Dict       =      huber_loss_delta
         UpperCAmelCase_      :							Dict       =      temperature
         UpperCAmelCase_      :							Optional[int]       =      aggregation_temperature
         UpperCAmelCase_      :							int       =      use_gumbel_for_cells
         UpperCAmelCase_      :							Dict       =      use_gumbel_for_aggregation
         UpperCAmelCase_      :							int       =      average_approximation_function
         UpperCAmelCase_      :							str       =      cell_selection_preference
         UpperCAmelCase_      :							Tuple       =      answer_loss_cutoff
         UpperCAmelCase_      :							Dict       =      max_num_rows
         UpperCAmelCase_      :							Any       =      max_num_columns
         UpperCAmelCase_      :							str       =      average_logits_per_cell
         UpperCAmelCase_      :							int       =      select_one_column
         UpperCAmelCase_      :							Tuple       =      allow_empty_column_selection
         UpperCAmelCase_      :							Tuple       =      init_cell_selection_weights_to_zero
         UpperCAmelCase_      :							List[Any]       =      reset_position_index_per_cell
         UpperCAmelCase_      :							Dict       =      disable_per_token_loss

         # Aggregation hyperparameters
         UpperCAmelCase_      :							List[str]       =      aggregation_labels
         UpperCAmelCase_      :							Tuple       =      no_aggregation_label_index

         if isinstance(self.aggregation_labels       ,_SCREAMING_SNAKE_CASE  ):
              UpperCAmelCase_      :							Union[str, Any]       =      {int(_SCREAMING_SNAKE_CASE  ): v for k, v in aggregation_labels.items()}





from collections import defaultdict







def lowerCamelCase__       (      _lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							Optional[int]       =      first_str.lower().strip()
     UpperCAmelCase_      :							Any       =      second_str.lower().strip()

     # Remove whitespace
     UpperCAmelCase_      :							Any       =      first_str.replace(''' '''			,						''''''				)
     UpperCAmelCase_      :							int       =      second_str.replace(''' '''			,						''''''				)

     # Strings of different lengths are not anagrams
     if len(_lowercase				) != len(_lowercase				):
          return False

     # Default values for count should be 0
     UpperCAmelCase_      :							defaultdict[str, int]       =      defaultdict(_lowercase				)

     # For each character in input strings,
     # increment count in the corresponding
     for i in range(len(_lowercase				)				):
          count[first_str[i]] += 1
          count[second_str[i]] -= 1

     return all(_count == 0 for _count in count.values()				)


if __name__ == "__main__":
     from doctest import testmod

     testmod()
     __a          =			input('Enter the first string ').strip()
     __a          =			input('Enter the second string ').strip()

     __a          =			check_anagrams(input_a, input_b)
     print(F"""{input_a} and {input_b} are {"" if status else "not "}anagrams.""")