



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


_lowerCamelCase         =	logging.get_logger(__name__)

_lowerCamelCase         =	{
    """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/config.json""",
    # QDQBERT models can be loaded from any BERT checkpoint, available at https://huggingface.co/models?filter=bert
}

class    _SCREAMING_SNAKE_CASE						(UpperCamelCase			):
     lowerCAmelCase       =      """qdqbert"""





     def __init__(							self			:				str  ,	UpperCamelCase			:				Union[str, Any]=3_0_5_2_2  ,	UpperCamelCase			:				str=7_6_8  ,	UpperCamelCase			:				int=1_2  ,	UpperCamelCase			:				List[Any]=1_2  ,	UpperCamelCase			:				str=3_0_7_2  ,	UpperCamelCase			:				Optional[int]="gelu"  ,	UpperCamelCase			:				Optional[int]=0.1  ,	UpperCamelCase			:				int=0.1  ,	UpperCamelCase			:				Tuple=5_1_2  ,	UpperCamelCase			:				str=2  ,	UpperCamelCase			:				Optional[Any]=0.0_2  ,	UpperCamelCase			:				List[str]=1E-12  ,	UpperCamelCase			:				Dict=True  ,	UpperCamelCase			:				Optional[int]=1  ,	UpperCamelCase			:				Any=0  ,	UpperCamelCase			:				Union[str, Any]=2  ,	**UpperCamelCase			:				Tuple  ,	)->Tuple:
      super().__init__(pad_token_id=UpperCamelCase  ,	bos_token_id=UpperCamelCase  ,	eos_token_id=UpperCamelCase  ,	**UpperCamelCase					)

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








"""simple docstring"""


import math



def        _lowerCamelCase(__UpperCamelCase			)							->					bool:

	if 1 < number < 4:
		# 2 and 3 are primes
		return True
	elif number < 2 or number % 2 == 0 or number % 3 == 0:
		# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
		return False

	# All primes number are in format of 6k +/- 1
	for i in range(5       ,					int(math.sqrt(__UpperCamelCase			) + 1			)       ,					6			):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True



def        _lowerCamelCase(__UpperCamelCase = 600851475143			)							->					int:

	try:
		_lowerCAmelCase								=int(__UpperCamelCase			)
	except (TypeError, ValueError):
		raise TypeError("""Parameter n must be int or castable to int."""			)
	if n <= 0:
		raise ValueError("""Parameter n must be greater than or equal to one."""			)
	_lowerCAmelCase								=0
	if is_prime(__UpperCamelCase			):
		return n
	while n % 2 == 0:
		n //= 2
	if is_prime(__UpperCamelCase			):
		return n
	for i in range(3       ,					int(math.sqrt(__UpperCamelCase			)			) + 1       ,					2			):
		if n % i == 0:
			if is_prime(n // i			):
				_lowerCAmelCase								=n // i
				break
			elif is_prime(__UpperCamelCase			):
				_lowerCAmelCase								=i
	return max_number


if __name__ == "__main__":
			print(F"""{solution() = }""")



