





import warnings

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


snake_case 				=       logging.get_logger(__name__)

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





class 				A_				(      SCREAMING_SNAKE_CASE__	):







       """simple docstring"""





       SCREAMING_SNAKE_CASE_      : int      =  '''mvp'''
       SCREAMING_SNAKE_CASE_      : Tuple      =  ['''past_key_values''']
       SCREAMING_SNAKE_CASE_      : Optional[int]      =  {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}







       def __init__(    self	:	Tuple						,__A	:	Optional[Any]=5_0267						,__A	:	Any=1024						,__A	:	List[Any]=12						,__A	:	Tuple=4096						,__A	:	Optional[int]=16						,__A	:	List[Any]=12						,__A	:	Optional[int]=4096						,__A	:	List[str]=16						,__A	:	Tuple=0.0						,__A	:	Tuple=0.0						,__A	:	Tuple="gelu"						,__A	:	Optional[int]=1024						,__A	:	List[str]=0.1						,__A	:	Optional[int]=0.0						,__A	:	Tuple=0.0						,__A	:	str=0.02						,__A	:	str=0.0						,__A	:	int=False						,__A	:	List[str]=True						,__A	:	Union[str, Any]=1						,__A	:	Dict=0						,__A	:	List[Any]=2						,__A	:	Optional[Any]=True						,__A	:	List[str]=2						,__A	:	Tuple=2						,__A	:	str=False						,__A	:	str=100						,__A	:	List[str]=800						,**__A	:	List[str]						,)						->					Optional[Any]:
         _lowercase							= vocab_size
         _lowercase							= max_position_embeddings
         _lowercase							= d_model
         _lowercase							= encoder_ffn_dim
         _lowercase							= encoder_layers
         _lowercase							= encoder_attention_heads
         _lowercase							= decoder_ffn_dim
         _lowercase							= decoder_layers
         _lowercase							= decoder_attention_heads
         _lowercase							= dropout
         _lowercase							= attention_dropout
         _lowercase							= activation_dropout
         _lowercase							= activation_function
         _lowercase							= init_std
         _lowercase							= encoder_layerdrop
         _lowercase							= decoder_layerdrop
         _lowercase							= classifier_dropout
         _lowercase							= use_cache
         _lowercase							= encoder_layers
         _lowercase							= scale_embedding  # scale factor will be sqrt(d_model) if True
         _lowercase							= use_prompt
         _lowercase							= prompt_length
         _lowercase							= 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__  ):
           _lowercase							= 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.'  )






from itertools import count

def 							SCREAMING_SNAKE_CASE__       (  snake_case__  :int = 50     )      ->						int:
  _lowercase							= [1] * min_block_length

  for n in count(snake_case__     ):
    fill_count_functions.append(1     )

    for block_length in range(snake_case__			,							n + 1     ):
      for block_start in range(n - block_length     ):
        fill_count_functions[n] += fill_count_functions[
            n - block_start - block_length - 1
        ]

      fill_count_functions[n] += 1

    if fill_count_functions[n] > 100_0000:
      break

  return n


if __name__ == "__main__":
      print(F"""{solution() = }""")