
'''simple docstring'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__					:						List[str]											=     logging.get_logger(__name__)

UpperCamelCase__					:						Dict											=     {
    "dandelin/vilt-b32-mlm": "https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"
}

class       _a (_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE					=     'vilt'






       def __init__(							self				,							A__=3_05_22				,							A__=2				,							A__=2				,							A__=40				,							A__=7_68				,							A__=12				,							A__=12				,							A__=30_72				,							A__="gelu"				,							A__=0.0				,							A__=0.0				,							A__=0.02				,							A__=1E-12				,							A__=3_84				,							A__=32				,							A__=3				,							A__=True				,							A__=-1				,							A__=False				,							A__=-1				,							**A__				,							)			->	Union[str, Any]:
          super().__init__(tie_word_embeddings=A__				,							**A__					)

          _SCREAMING_SNAKE_CASE          = vocab_size
          _SCREAMING_SNAKE_CASE          = type_vocab_size
          _SCREAMING_SNAKE_CASE          = modality_type_vocab_size
          _SCREAMING_SNAKE_CASE          = max_position_embeddings

          _SCREAMING_SNAKE_CASE          = hidden_size
          _SCREAMING_SNAKE_CASE          = num_hidden_layers
          _SCREAMING_SNAKE_CASE          = num_attention_heads
          _SCREAMING_SNAKE_CASE          = intermediate_size
          _SCREAMING_SNAKE_CASE          = hidden_act
          _SCREAMING_SNAKE_CASE          = hidden_dropout_prob
          _SCREAMING_SNAKE_CASE          = attention_probs_dropout_prob
          _SCREAMING_SNAKE_CASE          = initializer_range
          _SCREAMING_SNAKE_CASE          = layer_norm_eps

          _SCREAMING_SNAKE_CASE          = image_size
          _SCREAMING_SNAKE_CASE          = patch_size
          _SCREAMING_SNAKE_CASE          = num_channels
          _SCREAMING_SNAKE_CASE          = qkv_bias
          _SCREAMING_SNAKE_CASE          = max_image_length
          _SCREAMING_SNAKE_CASE          = num_images








'''simple docstring'''

from __future__ import annotations







def __A  (    lowerCAmelCase_       ):
     _UpperCAmelCase					:  Optional[int]         =    {1}
     _UpperCAmelCase					:  Union[str, Any]         =    [1]
     for _ in range(2 ,       depth + 1       ):
          _UpperCAmelCase					:  Dict         =    [*previous_coefficients, 0]
          _UpperCAmelCase					:  int         =    [0, *previous_coefficients]
          _UpperCAmelCase					:  List[Any]         =    []
          for x, y in zip(lowerCAmelCase_ ,       lowerCAmelCase_       ):
               coefficients.add(x + y       )
               previous_coefficients.append(x + y       )
     return coefficients







def __A  (    lowerCAmelCase_       ):
     _UpperCAmelCase					:  Dict         =    set()
     for number in unique_coefficients:
          _UpperCAmelCase					:  Tuple         =    2
          _UpperCAmelCase					:  List[str]         =    number
          while divisor**2 <= copy_number:
               _UpperCAmelCase					:  Tuple         =    0
               while copy_number % divisor == 0:
                    copy_number //= divisor
                    multiplicity += 1
               if multiplicity >= 2:
                    non_squarefrees.add(lowerCAmelCase_       )
                    break
               divisor += 1

     return unique_coefficients.difference(lowerCAmelCase_       )







def __A  (    lowerCAmelCase_ = 51       ):
     _UpperCAmelCase					:  List[str]         =    get_pascal_triangle_unique_coefficients(lowerCAmelCase_       )
     _UpperCAmelCase					:  Optional[Any]         =    get_squarefrees(lowerCAmelCase_       )
     return sum(lowerCAmelCase_       )


if __name__ == "__main__":
   print(F"{solution() = }")


