




from collections import deque

from .hash_table import HashTable





class     SCREAMING_SNAKE_CASE__		(_a			):
     def __init__(						self	:		List[str]       ,						*__lowerCamelCase	:		List[str]       ,						**__lowerCamelCase	:		List[str]						):



       """simple docstring"""
       super().__init__(*__lowerCamelCase       ,						**__lowerCamelCase						)
     def        A__      (						self	:		Any       ,						__lowerCamelCase	:		Tuple       ,						__lowerCamelCase	:		List[str]						):



       """simple docstring"""
       lowerCAmelCase__										=      deque([]						) if self.values[key] is None else self.values[key]
       self.values[key].appendleft(__lowerCamelCase						)
       lowerCAmelCase__										=      self.values[key]
     def        A__      (						self	:		str						):



       """simple docstring"""
       return (
           sum(self.charge_factor - len(__lowerCamelCase						) for slot in self.values						)
           / self.size_table
           * self.charge_factor
       )



     def        A__      (						self	:		int       ,						__lowerCamelCase	:		str       ,						__lowerCamelCase	:		Union[str, Any]=None						):



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







import logging

from transformers.configuration_utils import PretrainedConfig


__magic_name__  :  Tuple					=       logging.getLogger(__name__)





class     SCREAMING_SNAKE_CASE__		(_a			):
     lowercase_ :      Tuple				= "masked_bert"
     def __init__(						self	:		List[Any]       ,						__lowerCamelCase	:		Optional[Any]=3_05_22       ,						__lowerCamelCase	:		Dict=7_68       ,						__lowerCamelCase	:		Tuple=12       ,						__lowerCamelCase	:		int=12       ,						__lowerCamelCase	:		Tuple=30_72       ,						__lowerCamelCase	:		List[Any]="gelu"       ,						__lowerCamelCase	:		Union[str, Any]=0.1       ,						__lowerCamelCase	:		Dict=0.1       ,						__lowerCamelCase	:		Optional[int]=5_12       ,						__lowerCamelCase	:		List[Any]=2       ,						__lowerCamelCase	:		Union[str, Any]=0.02       ,						__lowerCamelCase	:		Optional[int]=1e-12       ,						__lowerCamelCase	:		Optional[int]=0       ,						__lowerCamelCase	:		List[str]="topK"       ,						__lowerCamelCase	:		Union[str, Any]="constant"       ,						__lowerCamelCase	:		Union[str, Any]=0.0       ,						**__lowerCamelCase	:		Tuple       ,						):



       """simple docstring"""
       super().__init__(pad_token_id=__lowerCamelCase       ,						**__lowerCamelCase						)

       lowerCAmelCase__										=      vocab_size
       lowerCAmelCase__										=      hidden_size
       lowerCAmelCase__										=      num_hidden_layers
       lowerCAmelCase__										=      num_attention_heads
       lowerCAmelCase__										=      hidden_act
       lowerCAmelCase__										=      intermediate_size
       lowerCAmelCase__										=      hidden_dropout_prob
       lowerCAmelCase__										=      attention_probs_dropout_prob
       lowerCAmelCase__										=      max_position_embeddings
       lowerCAmelCase__										=      type_vocab_size
       lowerCAmelCase__										=      initializer_range
       lowerCAmelCase__										=      layer_norm_eps
       lowerCAmelCase__										=      pruning_method
       lowerCAmelCase__										=      mask_init
       lowerCAmelCase__										=      mask_scale

