




"""simple docstring"""

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


_lowerCamelCase     :	Any         =				logging.get_logger(__name__)

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

class 				lowercase					(			__snake_case):
				__lowerCAmelCase			:			str     				=      """transfo-xl"""
				__lowerCAmelCase			:			Union[str, Any]     				=      ["""mems"""]
				__lowerCAmelCase			:			Optional[Any]     				=      {
				    """n_token""": """vocab_size""",
				    """hidden_size""": """d_model""",
				    """num_attention_heads""": """n_head""",
				    """num_hidden_layers""": """n_layer""",
				}







				def __init__(							self      :    Optional[int]					,   _lowerCamelCase      :    int=26_77_35					,   _lowerCamelCase      :    Any=[2_00_00, 4_00_00, 20_00_00]					,   _lowerCamelCase      :    str=10_24					,   _lowerCamelCase      :    Any=10_24					,   _lowerCamelCase      :    Optional[Any]=16					,   _lowerCamelCase      :    List[Any]=64					,   _lowerCamelCase      :    Tuple=40_96					,   _lowerCamelCase      :    Union[str, Any]=4					,   _lowerCamelCase      :    Dict=False					,   _lowerCamelCase      :    Union[str, Any]=18					,   _lowerCamelCase      :    List[str]=16_00					,   _lowerCamelCase      :    Dict=10_00					,   _lowerCamelCase      :    Dict=True					,   _lowerCamelCase      :    int=True					,   _lowerCamelCase      :    str=0					,   _lowerCamelCase      :    Union[str, Any]=-1					,   _lowerCamelCase      :    List[str]=True					,   _lowerCamelCase      :    Optional[Any]=0.1					,   _lowerCamelCase      :    Optional[Any]=0.0					,   _lowerCamelCase      :    Optional[int]=True					,   _lowerCamelCase      :    Optional[int]="normal"					,   _lowerCamelCase      :    Optional[Any]=0.01					,   _lowerCamelCase      :    Any=0.01					,   _lowerCamelCase      :    List[Any]=0.02					,   _lowerCamelCase      :    Tuple=1E-5					,   _lowerCamelCase      :    Any=0					,   **_lowerCamelCase      :    List[str]					,   ):



					"""simple docstring"""

					A_     : Optional[Any]		      =						vocab_size
					A_     : Optional[int]		      =						[]
					self.cutoffs.extend(__SCREAMING_SNAKE_CASE				)
					if proj_share_all_but_first:
						A_     : Union[str, Any]		      =						[False] + [True] * len(self.cutoffs				)
					else:
						A_     : List[str]		      =						[False] + [False] * len(self.cutoffs				)
					A_     : str		      =						d_model
					A_     : Optional[Any]		      =						d_embed
					A_     : Dict		      =						d_head
					A_     : List[Any]		      =						d_inner
					A_     : int		      =						div_val
					A_     : Optional[Any]		      =						pre_lnorm
					A_     : List[str]		      =						n_layer
					A_     : Optional[Any]		      =						n_head
					A_     : Optional[Any]		      =						mem_len
					A_     : Dict		      =						same_length
					A_     : Tuple		      =						attn_type
					A_     : Any		      =						clamp_len
					A_     : Optional[int]		      =						sample_softmax
					A_     : str		      =						adaptive
					A_     : List[str]		      =						dropout
					A_     : Union[str, Any]		      =						dropatt
					A_     : Any		      =						untie_r
					A_     : int		      =						init
					A_     : Union[str, Any]		      =						init_range
					A_     : Union[str, Any]		      =						proj_init_std
					A_     : int		      =						init_std
					A_     : Any		      =						layer_norm_epsilon
					super().__init__(eos_token_id=__SCREAMING_SNAKE_CASE					,   **__SCREAMING_SNAKE_CASE				)







				@property
				def     a_     (							self      :    Optional[Any]				):



					"""simple docstring"""

					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     a_     (							self      :    str					,   _lowerCamelCase      :    Dict				):



					"""simple docstring"""

					raise NotImplementedError(
					    F"""The model {self.model_type} is one of the few models that has no sequence length limit."""				)













"""simple docstring"""





import string







def      lowerCamelCase__       (							_lowerCamelCase       :		str )      ->				None:
  for key in range(len(string.ascii_uppercase ) ):
    lowerCamelCase_         =						''
    for symbol in message:
      if symbol in string.ascii_uppercase:
        lowerCamelCase_         =						string.ascii_uppercase.find(_lowerCamelCase )
        lowerCamelCase_         =						num - key
        if num < 0:
          lowerCamelCase_         =						num + len(string.ascii_uppercase )
        lowerCamelCase_         =						translated + string.ascii_uppercase[num]
      else:
        lowerCamelCase_         =						translated + symbol
    print(F'''Decryption using Key #{key}: {translated}''' )







def      lowerCamelCase__       (							)      ->				None:
  lowerCamelCase_         =						input('Encrypted message: ' )
  lowerCamelCase_         =						message.upper()
  decrypt(_lowerCamelCase )


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()




