from ...configuration_utils import PretrainedConfig


lowerCAmelCase			:							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 	__snake_case	( __lowerCAmelCase		):





      '''simple docstring'''






      _snake_case    		=       'tapas'



      def __init__(					self     :				Optional[Any]    ,  _UpperCamelCase     :				Dict=3_0522    ,  _UpperCamelCase     :				int=768    ,  _UpperCamelCase     :				int=12    ,  _UpperCamelCase     :				List[Any]=12    ,  _UpperCamelCase     :				List[Any]=3072    ,  _UpperCamelCase     :				int="gelu"    ,  _UpperCamelCase     :				Tuple=0.1    ,  _UpperCamelCase     :				Union[str, Any]=0.1    ,  _UpperCamelCase     :				Tuple=1024    ,  _UpperCamelCase     :				str=[3, 256, 256, 2, 256, 256, 10]    ,  _UpperCamelCase     :				Tuple=0.0_2    ,  _UpperCamelCase     :				Union[str, Any]=1E-1_2    ,  _UpperCamelCase     :				Dict=0    ,  _UpperCamelCase     :				int=1_0.0    ,  _UpperCamelCase     :				Dict=0    ,  _UpperCamelCase     :				List[Any]=1.0    ,  _UpperCamelCase     :				Optional[int]=None    ,  _UpperCamelCase     :				str=1.0    ,  _UpperCamelCase     :				Union[str, Any]=False    ,  _UpperCamelCase     :				Any=None    ,  _UpperCamelCase     :				Optional[Any]=1.0    ,  _UpperCamelCase     :				Any=1.0    ,  _UpperCamelCase     :				Tuple=False    ,  _UpperCamelCase     :				List[Any]=False    ,  _UpperCamelCase     :				Any="ratio"    ,  _UpperCamelCase     :				Optional[Any]=None    ,  _UpperCamelCase     :				int=None    ,  _UpperCamelCase     :				Dict=64    ,  _UpperCamelCase     :				int=32    ,  _UpperCamelCase     :				List[Any]=False    ,  _UpperCamelCase     :				List[str]=True    ,  _UpperCamelCase     :				int=False    ,  _UpperCamelCase     :				Dict=False    ,  _UpperCamelCase     :				List[str]=True    ,  _UpperCamelCase     :				List[str]=False    ,  _UpperCamelCase     :				str=None    ,  _UpperCamelCase     :				List[Any]=None    ,  **_UpperCamelCase     :				int    ,  )				->Optional[Any]:


          """simple docstring"""


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

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

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

          # Aggregation hyperparameters
          _lowerCamelCase     :		Optional[int] 						=						aggregation_labels
          _lowerCamelCase     :		Any 						=						no_aggregation_label_index

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





import math







def 						A__  (					__A	):







    '''simple docstring'''
    assert isinstance(__A   , __A	) and (
        number >= 0
    ), "'number' must been an int and positive"

    if 1 < number < 4:
        # 2 and 3 are primes
        return True
    elif number < 2 or not number % 2:
        # Negatives, 0, 1 and all even numbers are not primes
        return False

    _lowerCamelCase     :		List[Any] 						=						range(3   , int(math.sqrt(__A	) + 1	)   , 2	)
    return not any(not number % i for i in odd_numbers	)







def 						A__  (					__A   , __A=1   , **__A	):







    '''simple docstring'''
    _lowerCamelCase     :		Dict 						=						factor * value
    _lowerCamelCase     :		str 						=						value

    while not is_prime(__A	):
        value += 1 if not ("desc" in kwargs and kwargs["desc"] is True) else -1

    if value == first_value_val:
        return next_prime(value + 1   , **__A	)
    return value




