






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


__lowerCamelCase :      List[Any]										=				logging.get_logger(__name__)

__lowerCamelCase :      List[Any]										=				{
    """weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}



class 							SCREAMING_SNAKE_CASE__						(    UpperCamelCase_						):





					"""simple docstring"""






					a_     =		"roc_bert"



					def __init__( self					:  List[str]							,		__A					:  Optional[int]=3_0_5_2_2							,		__A					:  Any=7_6_8							,		__A					:  Any=1_2							,		__A					:  Any=1_2							,		__A					:  Tuple=3_0_7_2							,		__A					:  Optional[int]="gelu"							,		__A					:  str=0.1							,		__A					:  str=0.1							,		__A					:  Optional[Any]=5_1_2							,		__A					:  Optional[int]=2							,		__A					:  Optional[int]=0.0_2							,		__A					:  Any=1e-1_2							,		__A					:  Optional[int]=True							,		__A					:  List[Any]=0							,		__A					:  List[str]="absolute"							,		__A					:  Dict=None							,		__A					:  str=True							,		__A					:  List[Any]=True							,		__A					:  Dict=7_6_8							,		__A					:  Any=9_1_0							,		__A					:  List[Any]=5_1_2							,		__A					:  int=2_4_8_5_8							,		__A					:  List[Any]=True							,		**__A					:  Dict							,		):
						snake_case__			:				str       =  vocab_size
						snake_case__			:				int       =  max_position_embeddings
						snake_case__			:				Dict       =  hidden_size
						snake_case__			:				Optional[int]       =  num_hidden_layers
						snake_case__			:				Optional[Any]       =  num_attention_heads
						snake_case__			:				int       =  intermediate_size
						snake_case__			:				str       =  hidden_act
						snake_case__			:				Optional[Any]       =  hidden_dropout_prob
						snake_case__			:				Tuple       =  attention_probs_dropout_prob
						snake_case__			:				Any       =  initializer_range
						snake_case__			:				Dict       =  type_vocab_size
						snake_case__			:				Union[str, Any]       =  layer_norm_eps
						snake_case__			:				Optional[Any]       =  use_cache
						snake_case__			:				Dict       =  enable_pronunciation
						snake_case__			:				Optional[Any]       =  enable_shape
						snake_case__			:				Dict       =  pronunciation_embed_dim
						snake_case__			:				List[str]       =  pronunciation_vocab_size
						snake_case__			:				Tuple       =  shape_embed_dim
						snake_case__			:				List[Any]       =  shape_vocab_size
						snake_case__			:				List[str]       =  concat_input
						snake_case__			:				List[str]       =  position_embedding_type
						snake_case__			:				Optional[Any]       =  classifier_dropout
						super().__init__(pad_token_id=__A							,		**__A	)











__lowerCamelCase :      Optional[int]										=				"""Tobias Carryer"""

from time import time



class 							SCREAMING_SNAKE_CASE__						:





					"""simple docstring"""






					def __init__( self					:  List[Any]							,		__A					:  List[Any]							,		__A					:  Optional[int]							,		__A					:  List[str]							,		__A					:  Dict=int(time()	)	):  # noqa: B008
						snake_case__			:				List[Any]       =  multiplier
						snake_case__			:				Optional[int]       =  increment
						snake_case__			:				Optional[int]       =  modulo
						snake_case__			:				Union[str, Any]       =  seed






					def 	_lowercase					( self					:  str	):
						snake_case__			:				Union[str, Any]       =  (self.multiplier * self.seed + self.increment) % self.modulo
						return self.seed


if __name__ == "__main__":
	# Show the LCG in action.
	__lowerCamelCase :      int										=				LinearCongruentialGenerator(166_4525, 10_1390_4223, 2 << 31)
	while True:
		print(lcg.next_number())



