





import warnings

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


__UpperCAmelCase								=			logging.get_logger(__name__)

__UpperCAmelCase								=			{
    """xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/config.json""",
    """xlnet-large-cased""": """https://huggingface.co/xlnet-large-cased/resolve/main/config.json""",
}



class SCREAMING_SNAKE_CASE     (  _UpperCamelCase			):
  """simple docstring"""






  lowerCamelCase   :      Optional[Any]										='xlnet'
  lowerCamelCase   :      int										=['mems']
  lowerCamelCase   :      Optional[int]										={
      'n_token': 'vocab_size',  # Backward compatibility
      'hidden_size': 'd_model',
      'num_attention_heads': 'n_head',
      'num_hidden_layers': 'n_layer',
  }







  def __init__(      self			:   Optional[Any]	,							lowerCAmelCase			:   List[Any]=3_20_00	,							lowerCAmelCase			:   int=10_24	,							lowerCAmelCase			:   Optional[Any]=24	,							lowerCAmelCase			:   str=16	,							lowerCAmelCase			:   int=40_96	,							lowerCAmelCase			:   int="gelu"	,							lowerCAmelCase			:   Any=True	,							lowerCAmelCase			:   Dict="bi"	,							lowerCAmelCase			:   List[str]=0.02	,							lowerCAmelCase			:   str=1e-12	,							lowerCAmelCase			:   Union[str, Any]=0.1	,							lowerCAmelCase			:   int=5_12	,							lowerCAmelCase			:   List[str]=None	,							lowerCAmelCase			:   List[Any]=True	,							lowerCAmelCase			:   Optional[int]=False	,							lowerCAmelCase			:   Tuple=False	,							lowerCAmelCase			:   List[Any]=-1	,							lowerCAmelCase			:   Optional[Any]=False	,							lowerCAmelCase			:   List[str]="last"	,							lowerCAmelCase			:   Dict=True	,							lowerCAmelCase			:   Tuple="tanh"	,							lowerCAmelCase			:   str=0.1	,							lowerCAmelCase			:   List[Any]=5	,							lowerCAmelCase			:   str=5	,							lowerCAmelCase			:   Dict=5	,							lowerCAmelCase			:   Optional[int]=1	,							lowerCAmelCase			:   List[Any]=2	,							**lowerCAmelCase			:   Optional[Any]	,							)							->     Union[str, Any]:






     """simple docstring"""







     __lowerCAmelCase  :      Dict    =						vocab_size
     __lowerCAmelCase  :      Union[str, Any]    =						d_model
     __lowerCAmelCase  :      Optional[int]    =						n_layer
     __lowerCAmelCase  :      Union[str, Any]    =						n_head
     if d_model % n_head != 0:
        raise ValueError(f'''\'d_model % n_head\' ({d_model % n_head}) should be equal to 0'''   )
     if "d_head" in kwargs:
        if kwargs["d_head"] != d_model // n_head:
           raise ValueError(
               f'''`d_head` ({kwargs['d_head']}) should be equal to `d_model // n_head` ({d_model // n_head})'''   )
     __lowerCAmelCase  :      List[Any]    =						d_model // n_head
     __lowerCAmelCase  :      Dict    =						ff_activation
     __lowerCAmelCase  :      int    =						d_inner
     __lowerCAmelCase  :      int    =						untie_r
     __lowerCAmelCase  :      Dict    =						attn_type

     __lowerCAmelCase  :      Tuple    =						initializer_range
     __lowerCAmelCase  :      Tuple    =						layer_norm_eps

     __lowerCAmelCase  :      Union[str, Any]    =						dropout
     __lowerCAmelCase  :      int    =						mem_len
     __lowerCAmelCase  :      str    =						reuse_len
     __lowerCAmelCase  :      List[Any]    =						bi_data
     __lowerCAmelCase  :      Dict    =						clamp_len
     __lowerCAmelCase  :      int    =						same_length

     __lowerCAmelCase  :      int    =						summary_type
     __lowerCAmelCase  :      Any    =						summary_use_proj
     __lowerCAmelCase  :      Dict    =						summary_activation
     __lowerCAmelCase  :      Tuple    =						summary_last_dropout
     __lowerCAmelCase  :      Any    =						start_n_top
     __lowerCAmelCase  :      Optional[Any]    =						end_n_top

     __lowerCAmelCase  :      List[str]    =						bos_token_id
     __lowerCAmelCase  :      Dict    =						pad_token_id
     __lowerCAmelCase  :      List[Any]    =						eos_token_id

     if "use_cache" in kwargs:
        warnings.warn(
            """The `use_cache` argument is deprecated and will be removed in a future version, use `use_mems_eval`"""
            """ instead."""	,							_UpperCAmelCase	,							)
        __lowerCAmelCase  :      List[Any]    =						kwargs['use_cache']

     __lowerCAmelCase  :      Optional[Any]    =						use_mems_eval
     __lowerCAmelCase  :      List[Any]    =						use_mems_train
     super().__init__(pad_token_id=_UpperCAmelCase	,							bos_token_id=_UpperCAmelCase	,							eos_token_id=_UpperCAmelCase	,							**_UpperCAmelCase   )







  @property
  def 	SCREAMING_SNAKE_CASE   (      self			:   Optional[Any]   )							->     List[str]:






     """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			:   List[str]	,							lowerCAmelCase			:   List[str]   )							->     Union[str, Any]:






     """simple docstring"""







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





from pathlib import Path

import fire





def      snake_case_				(__A					:						str ,       __A					:						str ,       __A					:						int					)      ->     Any:
   __lowerCAmelCase  :      Tuple    =						Path(__A					)
   __lowerCAmelCase  :      Tuple    =						Path(__A					)
   dest_dir.mkdir(exist_ok=__A					)
   for path in src_dir.iterdir():
      __lowerCAmelCase  :      str    =						[x.rstrip() for x in list(path.open().readlines()					)][:n]
      __lowerCAmelCase  :      Dict    =						dest_dir.joinpath(path.name					)
      print(__A					)
      dest_path.open("""w"""					).write("""\n""".join(__A					)					)


if __name__ == "__main__":
   fire.Fire(minify)


