


'''simple docstring'''


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


_UpperCamelCase          =     logging.get_logger(__name__)

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







class        __magic_name__  (					lowerCAmelCase   ):

     """simple docstring"""






     lowerCamelCase__						=							'vilt'


     def __init__(      self ,    lowerCamelCase=3_0522 ,    lowerCamelCase=2 ,    lowerCamelCase=2 ,    lowerCamelCase=40 ,    lowerCamelCase=768 ,    lowerCamelCase=12 ,    lowerCamelCase=12 ,    lowerCamelCase=3072 ,    lowerCamelCase="gelu" ,    lowerCamelCase=0.0 ,    lowerCamelCase=0.0 ,    lowerCamelCase=0.02 ,    lowerCamelCase=1E-12 ,    lowerCamelCase=384 ,    lowerCamelCase=32 ,    lowerCamelCase=3 ,    lowerCamelCase=True ,    lowerCamelCase=-1 ,    lowerCamelCase=False ,    lowerCamelCase=-1 ,    **lowerCamelCase ,    ):


          '''simple docstring'''





          super().__init__(tie_word_embeddings=lowerCamelCase ,    **lowerCamelCase		)

          __A  :					Dict						     =       vocab_size
          __A  :					List[Any]						     =       type_vocab_size
          __A  :					Dict						     =       modality_type_vocab_size
          __A  :					int						     =       max_position_embeddings

          __A  :					Optional[int]						     =       hidden_size
          __A  :					Union[str, Any]						     =       num_hidden_layers
          __A  :					List[Any]						     =       num_attention_heads
          __A  :					Tuple						     =       intermediate_size
          __A  :					Any						     =       hidden_act
          __A  :					Union[str, Any]						     =       hidden_dropout_prob
          __A  :					Optional[int]						     =       attention_probs_dropout_prob
          __A  :					Any						     =       initializer_range
          __A  :					Any						     =       layer_norm_eps

          __A  :					Any						     =       image_size
          __A  :					List[str]						     =       patch_size
          __A  :					Union[str, Any]						     =       num_channels
          __A  :					str						     =       qkv_bias
          __A  :					Tuple						     =       max_image_length
          __A  :					List[str]						     =       num_images





'''simple docstring'''


from collections import defaultdict


def 		_lowercase   (SCREAMING_SNAKE_CASE = 5       ):




     '''simple docstring'''





     __A  :					int						     =       defaultdict(SCREAMING_SNAKE_CASE       )
     __A  :					Optional[Any]						     =       0

     while True:
          __A  :					List[str]						     =       get_digits(SCREAMING_SNAKE_CASE       )
          freqs[digits].append(SCREAMING_SNAKE_CASE       )

          if len(freqs[digits]       ) == max_base:
               __A  :					Optional[int]						     =       freqs[digits][0] ** 3
               return base

          num += 1


def 		_lowercase   (SCREAMING_SNAKE_CASE       ):




     '''simple docstring'''





     return "".join(sorted(str(num**3       )       )       )


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

