



"""simple docstring"""






import math
from datetime import datetime, timedelta


def     _lowercase       (						__snake_case			)		->     datetime:
			__lowerCAmelCase   :						Dict				= year % 19
			__lowerCAmelCase   :						List[Any]				= year % 4
			__lowerCAmelCase   :						Any				= year % 7
			__lowerCAmelCase   :						List[str]				= math.floor(year / 100			)
			__lowerCAmelCase   :						Optional[Any]				= math.floor((13 + 8 * leap_day_inhibits) / 25			)
			__lowerCAmelCase   :						Optional[int]				= leap_day_inhibits / 4
			__lowerCAmelCase   :						Dict				= (
			    15 - lunar_orbit_correction + leap_day_inhibits - leap_day_reinstall_number
			) % 30
			__lowerCAmelCase   :						Any				= (4 + leap_day_inhibits - leap_day_reinstall_number) % 7

			# days to be added to March 21
			__lowerCAmelCase   :						List[Any]				= (19 * metonic_cycle + secular_moon_shift) % 30

			# PHM -> Paschal Full Moon
			__lowerCAmelCase   :						Any				= (
			    2 * julian_leap_year
			    + 4 * non_leap_year
			    + 6 * days_to_add
			    + century_starting_point
			) % 7

			if days_to_add == 29 and days_from_phm_to_sunday == 6:
						return datetime(__snake_case      ,4      ,19			)
			elif days_to_add == 28 and days_from_phm_to_sunday == 6:
						return datetime(__snake_case      ,4      ,18			)
			else:
						return datetime(__snake_case      ,3      ,22			) + timedelta(
						    days=int(days_to_add + days_from_phm_to_sunday			)			)


if __name__ == "__main__":
	for year in (1_994, 2_000, 2_010, 2_021, 2_023):
		__snake_case							:     Tuple   =					'will be' if year > datetime.now().year else 'was'
		print(F"""Easter in {year} {tense} {gauss_easter(year)}""")




"""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