


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


snake_case				:    Tuple       				=     logging.get_logger(__name__)

snake_case				:    Dict       				=     {
    '''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/config.json''',
}







class 		_snake_case  (      _snake_case							):
 SCREAMING_SNAKE_CASE__      =       'transfo-xl'
 SCREAMING_SNAKE_CASE__      =       ['mems']
 SCREAMING_SNAKE_CASE__      =       {
     'n_token': 'vocab_size',
     'hidden_size': 'd_model',
     'num_attention_heads': 'n_head',
     'num_hidden_layers': 'n_layer',
 }




 def __init__(		self					,  _lowerCamelCase=26_7735					,  _lowerCamelCase=[2_0000, 4_0000, 20_0000]					,  _lowerCamelCase=1024					,  _lowerCamelCase=1024					,  _lowerCamelCase=16					,  _lowerCamelCase=64					,  _lowerCamelCase=4096					,  _lowerCamelCase=4					,  _lowerCamelCase=False					,  _lowerCamelCase=18					,  _lowerCamelCase=1600					,  _lowerCamelCase=1000					,  _lowerCamelCase=True					,  _lowerCamelCase=True					,  _lowerCamelCase=0					,  _lowerCamelCase=-1					,  _lowerCamelCase=True					,  _lowerCamelCase=0.1					,  _lowerCamelCase=0.0					,  _lowerCamelCase=True					,  _lowerCamelCase="normal"					,  _lowerCamelCase=0.01					,  _lowerCamelCase=0.01					,  _lowerCamelCase=0.02					,  _lowerCamelCase=1e-5					,  _lowerCamelCase=0					,  **_lowerCamelCase					,  ):
       a						:List[str] 							=       vocab_size
       a						:Union[str, Any] 							=       []
       self.cutoffs.extend(_lowerCamelCase    )
       if proj_share_all_but_first:
             a						:Optional[int] 							=       [False] + [True] * len(self.cutoffs    )
       else:
             a						:Any 							=       [False] + [False] * len(self.cutoffs    )
       a						:Optional[int] 							=       d_model
       a						:Union[str, Any] 							=       d_embed
       a						:str 							=       d_head
       a						:Optional[Any] 							=       d_inner
       a						:Optional[Any] 							=       div_val
       a						:int 							=       pre_lnorm
       a						:Dict 							=       n_layer
       a						:List[Any] 							=       n_head
       a						:Any 							=       mem_len
       a						:Any 							=       same_length
       a						:str 							=       attn_type
       a						:Optional[Any] 							=       clamp_len
       a						:Optional[int] 							=       sample_softmax
       a						:Optional[int] 							=       adaptive
       a						:Optional[int] 							=       dropout
       a						:Tuple 							=       dropatt
       a						:Dict 							=       untie_r
       a						:List[Any] 							=       init
       a						:int 							=       init_range
       a						:Optional[int] 							=       proj_init_std
       a						:Optional[Any] 							=       init_std
       a						:Optional[Any] 							=       layer_norm_epsilon
       super().__init__(eos_token_id=_lowerCamelCase					,  **_lowerCamelCase    )




 @property
 def        SCREAMING_SNAKE_CASE__				(		self    ):
       # Message copied from Transformer-XL documentation
       logger.info(F'''The model {self.model_type} is one of the few models that has no sequence length limit.'''    )
       return -1




 @max_position_embeddings.setter
 def        SCREAMING_SNAKE_CASE__				(		self					,  _lowerCamelCase    ):
       # Message copied from Transformer-XL documentation
       raise NotImplementedError(
           F'''The model {self.model_type} is one of the few models that has no sequence length limit.'''    )









import sys

snake_case				:    int       				=     (
    '''73167176531330624919225119674426574742355349194934'''
    '''96983520312774506326239578318016984801869478851843'''
    '''85861560789112949495459501737958331952853208805511'''
    '''12540698747158523863050715693290963295227443043557'''
    '''66896648950445244523161731856403098711121722383113'''
    '''62229893423380308135336276614282806444486645238749'''
    '''30358907296290491560440772390713810515859307960866'''
    '''70172427121883998797908792274921901699720888093776'''
    '''65727333001053367881220235421809751254540594752243'''
    '''52584907711670556013604839586446706324415722155397'''
    '''53697817977846174064955149290862569321978468622482'''
    '''83972241375657056057490261407972968652414535100474'''
    '''82166370484403199890008895243450658541227588666881'''
    '''16427171479924442928230863465674813919123162824586'''
    '''17866458359124566529476545682848912883142607690042'''
    '''24219022671055626321111109370544217506941658960408'''
    '''07198403850962455444362981230987879927244284909188'''
    '''84580156166097919133875499200524063689912560717606'''
    '''05886116467109405077541002256983155200055935729725'''
    '''71636269561882670428252483600823257530420752963450'''
)
def 				__lowerCamelCase						( UpperCAmelCase_						:		str = N						):




      """simple docstring"""





      a						:Optional[Any] 							=       -sys.maxsize - 1
      for i in range(len(UpperCAmelCase_						) - 12						):
            a						:Dict 							=       1
            for j in range(13						):
                  product *= int(n[i + j]						)
            if product > largest_product:
                  a						:str 							=       product
      return largest_product


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





