from ... import PretrainedConfig


SCREAMING_SNAKE_CASE :	Any							     =		{
    "sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class    A_ (       lowercase__ ):
    _SCREAMING_SNAKE_CASE    				=			NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
    _SCREAMING_SNAKE_CASE    				=			"""nezha"""

    def __init__(		self :      Tuple     ,							__SCREAMING_SNAKE_CASE :      Any=2_11_28     ,							__SCREAMING_SNAKE_CASE :      List[str]=7_68     ,							__SCREAMING_SNAKE_CASE :      List[str]=12     ,							__SCREAMING_SNAKE_CASE :      Any=12     ,							__SCREAMING_SNAKE_CASE :      List[str]=30_72     ,							__SCREAMING_SNAKE_CASE :      Optional[int]="gelu"     ,							__SCREAMING_SNAKE_CASE :      Tuple=0.1     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]=0.1     ,							__SCREAMING_SNAKE_CASE :      Dict=5_12     ,							__SCREAMING_SNAKE_CASE :      Dict=64     ,							__SCREAMING_SNAKE_CASE :      Any=2     ,							__SCREAMING_SNAKE_CASE :      Any=0.02     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]=1E-12     ,							__SCREAMING_SNAKE_CASE :      str=0.1     ,							__SCREAMING_SNAKE_CASE :      List[str]=0     ,							__SCREAMING_SNAKE_CASE :      str=2     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]=3     ,							__SCREAMING_SNAKE_CASE :      Tuple=True     ,							**__SCREAMING_SNAKE_CASE :      Optional[int]     ,							):
     super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE     ,							bos_token_id=__SCREAMING_SNAKE_CASE     ,							eos_token_id=__SCREAMING_SNAKE_CASE     ,							**__SCREAMING_SNAKE_CASE       )

     __a       =  vocab_size
     __a       =  hidden_size
     __a       =  num_hidden_layers
     __a       =  num_attention_heads
     __a       =  hidden_act
     __a       =  intermediate_size
     __a       =  hidden_dropout_prob
     __a       =  attention_probs_dropout_prob
     __a       =  max_position_embeddings
     __a       =  max_relative_position
     __a       =  type_vocab_size
     __a       =  initializer_range
     __a       =  layer_norm_eps
     __a       =  classifier_dropout
     __a       =  use_cache



from ... import PretrainedConfig


SCREAMING_SNAKE_CASE :	Any							     =		{
    """sijunhe/nezha-cn-base""": """https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json""",
}
class    A_ (       a_ ):
  _SCREAMING_SNAKE_CASE    				=			NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
  _SCREAMING_SNAKE_CASE    				=			"""nezha"""

  def __init__(		self :      Any     ,							__SCREAMING_SNAKE_CASE :      List[str]=2_11_28     ,							__SCREAMING_SNAKE_CASE :      Dict=7_68     ,							__SCREAMING_SNAKE_CASE :      List[Any]=12     ,							__SCREAMING_SNAKE_CASE :      str=12     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]=30_72     ,							__SCREAMING_SNAKE_CASE :      Any="gelu"     ,							__SCREAMING_SNAKE_CASE :      int=0.1     ,							__SCREAMING_SNAKE_CASE :      List[str]=0.1     ,							__SCREAMING_SNAKE_CASE :      int=5_12     ,							__SCREAMING_SNAKE_CASE :      Union[str, Any]=64     ,							__SCREAMING_SNAKE_CASE :      List[Any]=2     ,							__SCREAMING_SNAKE_CASE :      int=0.02     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]=1E-12     ,							__SCREAMING_SNAKE_CASE :      int=0.1     ,							__SCREAMING_SNAKE_CASE :      Any=0     ,							__SCREAMING_SNAKE_CASE :      Any=2     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]=3     ,							__SCREAMING_SNAKE_CASE :      List[Any]=True     ,							**__SCREAMING_SNAKE_CASE :      List[str]     ,							):
   super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE     ,							bos_token_id=__SCREAMING_SNAKE_CASE     ,							eos_token_id=__SCREAMING_SNAKE_CASE     ,							**__SCREAMING_SNAKE_CASE       )

   __a       =  vocab_size
   __a       =  hidden_size
   __a       =  num_hidden_layers
   __a       =  num_attention_heads
   __a       =  hidden_act
   __a       =  intermediate_size
   __a       =  hidden_dropout_prob
   __a       =  attention_probs_dropout_prob
   __a       =  max_position_embeddings
   __a       =  max_relative_position
   __a       =  type_vocab_size
   __a       =  initializer_range
   __a       =  layer_norm_eps
   __a       =  classifier_dropout
   __a       =  use_cache


