





class     SCREAMING_SNAKE_CASE       :


   def __init__(   self      :    List[str]      ,					a      :    int	)->       List[str]:





     """simple docstring"""







     lowercase__           =  n
     lowercase__           =  [None] * self.n
     lowercase__           =  0  # index of the first element
     lowercase__           =  0
     lowercase__           =  0


   def __len__(   self      :    Union[str, Any]	)->       int:





     """simple docstring"""







     return self.size


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]	)->       bool:





     """simple docstring"""







     return self.size == 0


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]	)->       Optional[int]:





     """simple docstring"""







     return False if self.is_empty() else self.array[self.front]


   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[Any]      ,					a      :    Tuple	)->       Dict:





     """simple docstring"""







     if self.size >= self.n:
       raise Exception('QUEUE IS FULL'	)

     lowercase__           =  data
     lowercase__           =  (self.rear + 1) % self.n
     self.size += 1
     return self


   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[Any]	)->       str:





     """simple docstring"""







     if self.size == 0:
       raise Exception('UNDERFLOW'	)

     lowercase__           =  self.array[self.front]
     lowercase__           =  None
     lowercase__           =  (self.front + 1) % self.n
     self.size -= 1
     return temp









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


lowercase_          =		logging.get_logger(__name__)

lowercase_          =		{
    """transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		Optional[Any]			 =	'transfo-xl'
   _UpperCamelCase   :		Any			 =	['mems']
   _UpperCamelCase   :		Any			 =	{
       'n_token': 'vocab_size',
       'hidden_size': 'd_model',
       'num_attention_heads': 'n_head',
       'num_hidden_layers': 'n_layer',
   }


   def __init__(   self      :    Optional[Any]      ,					a      :    Optional[int]=267_735      ,					a      :    str=[20_000, 40_000, 200_000]      ,					a      :    str=1_024      ,					a      :    str=1_024      ,					a      :    int=16      ,					a      :    Optional[int]=64      ,					a      :    Optional[int]=4_096      ,					a      :    int=4      ,					a      :    Tuple=False      ,					a      :    Any=18      ,					a      :    Tuple=1_600      ,					a      :    Union[str, Any]=1_000      ,					a      :    str=True      ,					a      :    Dict=True      ,					a      :    Any=0      ,					a      :    List[Any]=-1      ,					a      :    List[Any]=True      ,					a      :    Tuple=0.1      ,					a      :    List[Any]=0.0      ,					a      :    Optional[Any]=True      ,					a      :    int="normal"      ,					a      :    Optional[Any]=0.01      ,					a      :    str=0.01      ,					a      :    List[Any]=0.02      ,					a      :    List[Any]=1E-5      ,					a      :    Optional[Any]=0      ,					**a      :    Optional[int]      ,					)->       Optional[int]:





     """simple docstring"""







     lowercase__           =  vocab_size
     lowercase__           =  []
     self.cutoffs.extend(a	)
     if proj_share_all_but_first:
       lowercase__           =  [False] + [True] * len(self.cutoffs	)
     else:
       lowercase__           =  [False] + [False] * len(self.cutoffs	)
     lowercase__           =  d_model
     lowercase__           =  d_embed
     lowercase__           =  d_head
     lowercase__           =  d_inner
     lowercase__           =  div_val
     lowercase__           =  pre_lnorm
     lowercase__           =  n_layer
     lowercase__           =  n_head
     lowercase__           =  mem_len
     lowercase__           =  same_length
     lowercase__           =  attn_type
     lowercase__           =  clamp_len
     lowercase__           =  sample_softmax
     lowercase__           =  adaptive
     lowercase__           =  dropout
     lowercase__           =  dropatt
     lowercase__           =  untie_r
     lowercase__           =  init
     lowercase__           =  init_range
     lowercase__           =  proj_init_std
     lowercase__           =  init_std
     lowercase__           =  layer_norm_epsilon
     super().__init__(eos_token_id=a      ,					**a	)


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[Any]	)->       Union[str, 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 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    Optional[int]	)->       Optional[int]:





     """simple docstring"""







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


