

def      a      (			A__	:   int = 1000     )    ->      int:





      """simple docstring"""



      _lowercase	       =2**power
      _lowercase	       =str(A__     )
      _lowercase	       =list(A__     )
      _lowercase	       =0

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

      return sum_of_num


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





import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin





class  __lowerCAmelCase     (					SCREAMING_SNAKE_CASE			,			SCREAMING_SNAKE_CASE			,			SCREAMING_SNAKE_CASE							):




  @register_to_config
  def __init__(				self							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase							,   lowerCAmelCase = False							,   )  -> Tuple:
        '''simple docstring'''






        super().__init__()

        _lowercase	       =nn.Embedding(lowerCAmelCase							,   lowerCAmelCase					)

        _lowercase	       =nn.Embedding(lowerCAmelCase							,   lowerCAmelCase					)
        _lowercase	       =False

        _lowercase	       =nn.Dropout(p=lowerCAmelCase					)

        _lowercase	       =TaConfig(
            vocab_size=lowerCAmelCase							,   d_model=lowerCAmelCase							,   num_heads=lowerCAmelCase							,   d_kv=lowerCAmelCase							,   d_ff=lowerCAmelCase							,   dropout_rate=lowerCAmelCase							,   feed_forward_proj=lowerCAmelCase							,   is_decoder=lowerCAmelCase							,   is_encoder_decoder=lowerCAmelCase							,   )

        _lowercase	       =nn.ModuleList()
        for lyr_num in range(lowerCAmelCase					):
              _lowercase	       =TaBlock(lowerCAmelCase					)
              self.encoders.append(lowerCAmelCase					)

        _lowercase	       =TaLayerNorm(lowerCAmelCase					)
        _lowercase	       =nn.Dropout(p=lowerCAmelCase					)




  def   A__     (				self							,   lowerCAmelCase							,   lowerCAmelCase					)  -> Dict:
        '''simple docstring'''






        _lowercase	       =self.token_embedder(lowerCAmelCase					)

        _lowercase	       =encoder_input_tokens.shape[1]
        _lowercase	       =torch.arange(lowerCAmelCase							,   device=encoder_input_tokens.device					)
        x += self.position_encoding(lowerCAmelCase					)

        _lowercase	       =self.dropout_pre(lowerCAmelCase					)

        # inverted the attention mask
        _lowercase	       =encoder_input_tokens.size()
        _lowercase	       =self.get_extended_attention_mask(lowerCAmelCase							,   lowerCAmelCase					)

        for lyr in self.encoders:
              _lowercase	       =lyr(lowerCAmelCase							,   lowerCAmelCase					)[0]
        _lowercase	       =self.layer_norm(lowerCAmelCase					)

        return self.dropout_post(lowerCAmelCase					), encoder_inputs_mask


