


def       UpperCAmelCase__						(UpperCamelCase_    ):



     """simple docstring"""






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


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








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


_SCREAMING_SNAKE_CASE      :			Dict      				=   logging.get_logger(__name__)

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

class   A__ (   snake_case__     ):







    """simple docstring"""

    __magic_name__        =		'mgp-str'
    def __init__(	self      , __snake_case=[3_2, 1_2_8]      , __snake_case=4      , __snake_case=3      , __snake_case=2_7      , __snake_case=3_8      , __snake_case=5_0_2_5_7      , __snake_case=3_0_5_2_2      , __snake_case=7_6_8      , __snake_case=1_2      , __snake_case=1_2      , __snake_case=4.0      , __snake_case=True      , __snake_case=False      , __snake_case=1E-5      , __snake_case=0.0      , __snake_case=0.0      , __snake_case=0.0      , __snake_case=False      , __snake_case=0.02      , **__snake_case      , ):
         super().__init__(**__snake_case   )

         snake_case					=    image_size
         snake_case					=    patch_size
         snake_case					=    num_channels
         snake_case					=    max_token_length
         snake_case					=    num_character_labels
         snake_case					=    num_bpe_labels
         snake_case					=    num_wordpiece_labels
         snake_case					=    hidden_size
         snake_case					=    num_hidden_layers
         snake_case					=    num_attention_heads
         snake_case					=    mlp_ratio
         snake_case					=    distilled
         snake_case					=    layer_norm_eps
         snake_case					=    drop_rate
         snake_case					=    qkv_bias
         snake_case					=    attn_drop_rate
         snake_case					=    drop_path_rate
         snake_case					=    output_aa_attentions
         snake_case					=    initializer_range




