

import copy

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


_lowerCamelCase								=logging.get_logger(__name__)

_lowerCamelCase								={}



class 		a_	(							lowerCamelCase_					):



      """simple docstring"""







      __UpperCAmelCase      		=				'fsmt_decoder'
      def __init__(				self					:							Dict      ,snake_case					:							Dict=0      ,snake_case					:							Tuple=0    ):
           super().__init__()
           SCREAMING_SNAKE_CASE										=vocab_size
           SCREAMING_SNAKE_CASE										=bos_token_id







class 		a_	(							lowerCamelCase_					):



      """simple docstring"""







      __UpperCAmelCase      		=				'fsmt'
      __UpperCAmelCase      		=				{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}
      def __init__(				self					:							Optional[int]      ,snake_case					:							Optional[Any]=["en", "de"]      ,snake_case					:							Dict=42024      ,snake_case					:							Union[str, Any]=42024      ,snake_case					:							Optional[int]="relu"      ,snake_case					:							str=1024      ,snake_case					:							List[str]=200      ,snake_case					:							Optional[int]=1024      ,snake_case					:							Optional[int]=4096      ,snake_case					:							int=12      ,snake_case					:							Tuple=16      ,snake_case					:							Optional[Any]=0.0      ,snake_case					:							Tuple=4096      ,snake_case					:							Union[str, Any]=12      ,snake_case					:							Optional[int]=16      ,snake_case					:							int=0.0      ,snake_case					:							Dict=0.0      ,snake_case					:							Optional[int]=0.1      ,snake_case					:							Any=0.0      ,snake_case					:							Optional[int]=0.02      ,snake_case					:							int=2      ,snake_case					:							Union[str, Any]=True      ,snake_case					:							str=True      ,snake_case					:							Dict=False      ,snake_case					:							List[str]=5      ,snake_case					:							List[str]=1.0      ,snake_case					:							Any=False      ,snake_case					:							Any=True      ,snake_case					:							Any=1      ,snake_case					:							Any=0      ,snake_case					:							Dict=2      ,snake_case					:							Optional[int]=2      ,**snake_case					:							Tuple      ,):
           SCREAMING_SNAKE_CASE										=langs
           SCREAMING_SNAKE_CASE										=src_vocab_size
           SCREAMING_SNAKE_CASE										=tgt_vocab_size
           SCREAMING_SNAKE_CASE										=d_model  # encoder_embed_dim and decoder_embed_dim

           SCREAMING_SNAKE_CASE										=encoder_ffn_dim
           SCREAMING_SNAKE_CASE										=SCREAMING_SNAKE_CASE										=encoder_layers
           SCREAMING_SNAKE_CASE										=encoder_attention_heads
           SCREAMING_SNAKE_CASE										=encoder_layerdrop
           SCREAMING_SNAKE_CASE										=decoder_layerdrop
           SCREAMING_SNAKE_CASE										=decoder_ffn_dim
           SCREAMING_SNAKE_CASE										=decoder_layers
           SCREAMING_SNAKE_CASE										=decoder_attention_heads
           SCREAMING_SNAKE_CASE										=max_position_embeddings
           SCREAMING_SNAKE_CASE										=init_std  # Normal(0, this parameter)
           SCREAMING_SNAKE_CASE										=activation_function

           SCREAMING_SNAKE_CASE										=DecoderConfig(vocab_size=snake_case      ,bos_token_id=snake_case    )
           if "decoder" in common_kwargs:
                del common_kwargs["decoder"]

           SCREAMING_SNAKE_CASE										=scale_embedding  # scale factor will be sqrt(d_model) if True

           # 3 Types of Dropout
           SCREAMING_SNAKE_CASE										=attention_dropout
           SCREAMING_SNAKE_CASE										=activation_dropout
           SCREAMING_SNAKE_CASE										=dropout

           SCREAMING_SNAKE_CASE										=use_cache
           super().__init__(
               pad_token_id=snake_case      ,bos_token_id=snake_case      ,eos_token_id=snake_case      ,decoder_start_token_id=snake_case      ,is_encoder_decoder=snake_case      ,tie_word_embeddings=snake_case      ,forced_eos_token_id=snake_case      ,max_length=snake_case      ,num_beams=snake_case      ,length_penalty=snake_case      ,early_stopping=snake_case      ,**snake_case      ,)


      def 	_lowerCAmelCase					(				self					:							Any    ):
           SCREAMING_SNAKE_CASE										=copy.deepcopy(self.__dict__    )
           SCREAMING_SNAKE_CASE										=self.decoder.to_dict()
           SCREAMING_SNAKE_CASE										=self.__class__.model_type
           return output




import decimal







def       snake_case__    (       ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE										=0
     SCREAMING_SNAKE_CASE										=decimal.Context(prec=105      )
     for i in range(2,   100      ):
          SCREAMING_SNAKE_CASE										=decimal.Decimal(lowerCAmelCase_      )
          SCREAMING_SNAKE_CASE										=number.sqrt(lowerCAmelCase_      )
          if len(str(lowerCAmelCase_      )      ) > 1:
               answer += int(str(lowerCAmelCase_      )[0]      )
               SCREAMING_SNAKE_CASE										=str(lowerCAmelCase_      )[2:101]
               answer += sum(int(lowerCAmelCase_      ) for x in sqrt_number_str      )
     return answer


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(f'{solution() = }')

