





"""simple docstring"""



import warnings

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


a_					=     logging.get_logger(__name__)

a_					=     {
    '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json''',
}






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 _lowerCamelCase								=	"""mvp"""
 _lowerCamelCase								=	["""past_key_values"""]
 _lowerCamelCase								=	{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}

 def __init__(       self   ,		__lowerCamelCase=5_0267   ,		__lowerCamelCase=1024   ,		__lowerCamelCase=12   ,		__lowerCamelCase=4096   ,		__lowerCamelCase=16   ,		__lowerCamelCase=12   ,		__lowerCamelCase=4096   ,		__lowerCamelCase=16   ,		__lowerCamelCase=0.0   ,		__lowerCamelCase=0.0   ,		__lowerCamelCase="gelu"   ,		__lowerCamelCase=1024   ,		__lowerCamelCase=0.1   ,		__lowerCamelCase=0.0   ,		__lowerCamelCase=0.0   ,		__lowerCamelCase=0.0_2   ,		__lowerCamelCase=0.0   ,		__lowerCamelCase=False   ,		__lowerCamelCase=True   ,		__lowerCamelCase=1   ,		__lowerCamelCase=0   ,		__lowerCamelCase=2   ,		__lowerCamelCase=True   ,		__lowerCamelCase=2   ,		__lowerCamelCase=2   ,		__lowerCamelCase=False   ,		__lowerCamelCase=100   ,		__lowerCamelCase=800   ,		**__lowerCamelCase   ,		):



     '''simple docstring'''




     __A       :		Dict							=	vocab_size
     __A       :		int							=	max_position_embeddings
     __A       :		Optional[Any]							=	d_model
     __A       :		Any							=	encoder_ffn_dim
     __A       :		Union[str, Any]							=	encoder_layers
     __A       :		Any							=	encoder_attention_heads
     __A       :		Tuple							=	decoder_ffn_dim
     __A       :		Optional[int]							=	decoder_layers
     __A       :		Dict							=	decoder_attention_heads
     __A       :		List[str]							=	dropout
     __A       :		Any							=	attention_dropout
     __A       :		Optional[int]							=	activation_dropout
     __A       :		Dict							=	activation_function
     __A       :		Optional[Any]							=	init_std
     __A       :		Union[str, Any]							=	encoder_layerdrop
     __A       :		str							=	decoder_layerdrop
     __A       :		List[str]							=	classifier_dropout
     __A       :		Optional[Any]							=	use_cache
     __A       :		Optional[int]							=	encoder_layers
     __A       :		Any							=	scale_embedding  # scale factor will be sqrt(d_model) if True
     __A       :		List[Any]							=	use_prompt
     __A       :		str							=	prompt_length
     __A       :		List[str]							=	prompt_mid_dim

     super().__init__(
         pad_token_id=snake_case__   ,		bos_token_id=snake_case__   ,		eos_token_id=snake_case__   ,		is_encoder_decoder=snake_case__   ,		decoder_start_token_id=snake_case__   ,		forced_eos_token_id=snake_case__   ,		**snake_case__   ,		)

     if self.forced_bos_token_id is None and kwargs.get('''force_bos_token_to_be_generated'''   ,		snake_case__    ):
         __A       :		Optional[Any]							=	self.bos_token_id
         warnings.warn(
             F"""Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. """
             '''The config can simply be saved and uploaded again to be fixed.'''    )










SCREAMING_SNAKE_CASE:     Optional[int]									= {str(digit): digit**5 for digit in range(1_0)}


def 					_a							(					lowerCAmelCase )->	int:
		return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowerCAmelCase ) )


def 					_a							(					)->	int:
		return sum(
		    number
		    for number in range(1000    ,						1000000 )
		    if number == digits_fifth_powers_sum(lowerCAmelCase ) )


if __name__ == "__main__":
						print(solution())