





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


lowercase				:	Tuple      						=					logging.get_logger(__name__)

lowercase				:	List[str]      						=					{
    """alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}





class 			A__   (							__UpperCAmelCase     ):




   """simple docstring"""



   __A       :    int	  =  '''mgp-str'''

   def __init__( self ,  lowercase=[32, 128] ,  lowercase=4 ,  lowercase=3 ,  lowercase=27 ,  lowercase=38 ,  lowercase=5_0257 ,  lowercase=3_0522 ,  lowercase=768 ,  lowercase=12 ,  lowercase=12 ,  lowercase=4.0 ,  lowercase=True ,  lowercase=False ,  lowercase=1e-5 ,  lowercase=0.0 ,  lowercase=0.0 ,  lowercase=0.0 ,  lowercase=False ,  lowercase=0.02 ,  **lowercase ,  )      ->						Optional[int]:







          '''simple docstring'''

          super().__init__(**__a)

          a__						:     int			=    image_size
          a__						:     str			=    patch_size
          a__						:     str			=    num_channels
          a__						:     Tuple			=    max_token_length
          a__						:     Optional[Any]			=    num_character_labels
          a__						:     Any			=    num_bpe_labels
          a__						:     Union[str, Any]			=    num_wordpiece_labels
          a__						:     Optional[Any]			=    hidden_size
          a__						:     int			=    num_hidden_layers
          a__						:     Any			=    num_attention_heads
          a__						:     Optional[int]			=    mlp_ratio
          a__						:     Dict			=    distilled
          a__						:     Tuple			=    layer_norm_eps
          a__						:     Union[str, Any]			=    drop_rate
          a__						:     Dict			=    qkv_bias
          a__						:     int			=    attn_drop_rate
          a__						:     Optional[Any]			=    drop_path_rate
          a__						:     Union[str, Any]			=    output_aa_attentions
          a__						:     Dict			=    initializer_range









def A_     (		A__    )  ->		int:

       if not isinstance(A__		,				A__    ):
              raise TypeError('only integers accepted as input'    )
       else:
              a__						:     List[Any]			=    str(abs(A__    )    )
              a__						:     Optional[int]			=    [list(A__    ) for char in range(len(A__    )    )]
              for index in range(len(A__    )    ):
                     num_transpositions[index].pop(A__    )
              return max(
                  int(''.join(list(A__    )    )    ) for transposition in num_transpositions    )


if __name__ == "__main__":
    __import__("""doctest""").testmod()


