





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


snake_case_           =      logging.get_logger(__name__)

snake_case_           =      {
    'YituTech/conv-bert-base': 'https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json',
    'YituTech/conv-bert-medium-small': (
        'https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json'
    ),
    'YituTech/conv-bert-small': 'https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json',
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}

class 		SCREAMING_SNAKE_CASE__    (	_UpperCAmelCase  ):
      A_						:    Any							=   'convbert'


      def __init__(self	:				Tuple    ,      a__	:				int=3_0522    ,      a__	:				Union[str, Any]=768    ,      a__	:				Any=12    ,      a__	:				Any=12    ,      a__	:				Optional[Any]=3072    ,      a__	:				List[str]="gelu"    ,      a__	:				Optional[int]=0.1    ,      a__	:				Tuple=0.1    ,      a__	:				List[Any]=512    ,      a__	:				Dict=2    ,      a__	:				Tuple=0.0_2    ,      a__	:				Tuple=1E-12    ,      a__	:				Optional[int]=1    ,      a__	:				List[str]=0    ,      a__	:				int=2    ,      a__	:				Tuple=768    ,      a__	:				List[Any]=2    ,      a__	:				Optional[int]=9    ,      a__	:				List[str]=1    ,      a__	:				Dict=None    ,      **a__	:				str    ,      ):





         """simple docstring"""



         super().__init__(
             pad_token_id=a__    ,      bos_token_id=a__    ,      eos_token_id=a__    ,      **a__    ,      )

         __snake_case								=       vocab_size
         __snake_case								=       hidden_size
         __snake_case								=       num_hidden_layers
         __snake_case								=       num_attention_heads
         __snake_case								=       intermediate_size
         __snake_case								=       hidden_act
         __snake_case								=       hidden_dropout_prob
         __snake_case								=       attention_probs_dropout_prob
         __snake_case								=       max_position_embeddings
         __snake_case								=       type_vocab_size
         __snake_case								=       initializer_range
         __snake_case								=       layer_norm_eps
         __snake_case								=       embedding_size
         __snake_case								=       head_ratio
         __snake_case								=       conv_kernel_size
         __snake_case								=       num_groups
         __snake_case								=       classifier_dropout






class 		SCREAMING_SNAKE_CASE__    (	_UpperCAmelCase  ):


      @property
      def        a			(self	:				str				):





         """simple docstring"""



         if self.task == "multiple-choice":
            __snake_case								=       {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
            __snake_case								=       {0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
                 ('''token_type_ids''', dynamic_axis),
             ]				)








def lowerCamelCase__   (							snake_case_     :  int = 1000	)				->    int:
   __snake_case								=       2**power
   __snake_case								=       str(snake_case_	)
   __snake_case								=       list(snake_case_	)
   __snake_case								=       0

   for i in list_num:
      sum_of_num += int(snake_case_	)

   return sum_of_num


if __name__ == "__main__":
    snake_case_           =      int(input('Enter the power of 2: ').strip())
    print('2 ^ ', power, ' = ', 2**power)
    snake_case_           =      solution(power)
    print('Sum of the digits is: ', result)

