



"""simple docstring"""






from collections import deque

from .hash_table import HashTable



class     A__     (						__SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	def __init__(  self:	Union[str, Any] ,    *_SCREAMING_SNAKE_CASE:	str ,    **_SCREAMING_SNAKE_CASE:	List[str])       -> List[Any]:

				"""simple docstring"""

				super().__init__(*_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE     (  self:	str ,    _SCREAMING_SNAKE_CASE:	str ,    _SCREAMING_SNAKE_CASE:	Optional[Any])       -> Optional[int]:

				"""simple docstring"""

				__lowerCAmelCase   :						int				= deque([]) if self.values[key] is None else self.values[key]
				self.values[key].appendleft(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Any				= self.values[key]

	def 							_SCREAMING_SNAKE_CASE     (  self:	int)       -> str:

				"""simple docstring"""

				return (
				    sum(self.charge_factor - len(_SCREAMING_SNAKE_CASE) for slot in self.values)
				    / self.size_table
				    * self.charge_factor
				)







	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any] ,    _SCREAMING_SNAKE_CASE:	str ,    _SCREAMING_SNAKE_CASE:	int=None)       -> Any:

				"""simple docstring"""

				if not (
				    len(self.values[key]) == self.charge_factor and self.values.count(_SCREAMING_SNAKE_CASE) == 0
				):
							return key
				return super()._collision_resolution(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)




"""simple docstring"""






import logging

from transformers.configuration_utils import PretrainedConfig


__snake_case							:     Tuple   =					logging.getLogger(__name__)



class     A__     (						__SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE					   =			'masked_bert'

	def __init__(  self:	str ,    _SCREAMING_SNAKE_CASE:	Tuple=3_0522 ,    _SCREAMING_SNAKE_CASE:	Optional[int]=768 ,    _SCREAMING_SNAKE_CASE:	List[str]=12 ,    _SCREAMING_SNAKE_CASE:	Any=12 ,    _SCREAMING_SNAKE_CASE:	Optional[int]=3072 ,    _SCREAMING_SNAKE_CASE:	List[str]="gelu" ,    _SCREAMING_SNAKE_CASE:	List[str]=0.1 ,    _SCREAMING_SNAKE_CASE:	str=0.1 ,    _SCREAMING_SNAKE_CASE:	Dict=512 ,    _SCREAMING_SNAKE_CASE:	List[Any]=2 ,    _SCREAMING_SNAKE_CASE:	Tuple=0.02 ,    _SCREAMING_SNAKE_CASE:	int=1e-12 ,    _SCREAMING_SNAKE_CASE:	int=0 ,    _SCREAMING_SNAKE_CASE:	Tuple="topK" ,    _SCREAMING_SNAKE_CASE:	Any="constant" ,    _SCREAMING_SNAKE_CASE:	int=0.0 ,    **_SCREAMING_SNAKE_CASE:	Any ,    )       -> List[str]:

				"""simple docstring"""

				super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						Union[str, Any]				= vocab_size
				__lowerCAmelCase   :						List[str]				= hidden_size
				__lowerCAmelCase   :						Any				= num_hidden_layers
				__lowerCAmelCase   :						Dict				= num_attention_heads
				__lowerCAmelCase   :						Union[str, Any]				= hidden_act
				__lowerCAmelCase   :						Optional[Any]				= intermediate_size
				__lowerCAmelCase   :						int				= hidden_dropout_prob
				__lowerCAmelCase   :						List[Any]				= attention_probs_dropout_prob
				__lowerCAmelCase   :						int				= max_position_embeddings
				__lowerCAmelCase   :						str				= type_vocab_size
				__lowerCAmelCase   :						Any				= initializer_range
				__lowerCAmelCase   :						Optional[int]				= layer_norm_eps
				__lowerCAmelCase   :						Tuple				= pruning_method
				__lowerCAmelCase   :						Union[str, Any]				= mask_init
				__lowerCAmelCase   :						str				= mask_scale