




import math
from datetime import datetime, timedelta
def 		a_							( __lowerCAmelCase				):
  lowerCAmelCase__										=      year % 19
  lowerCAmelCase__										=      year % 4
  lowerCAmelCase__										=      year % 7
  lowerCAmelCase__										=      math.floor(year / 1_00				)
  lowerCAmelCase__										=      math.floor((13 + 8 * leap_day_inhibits) / 25				)
  lowerCAmelCase__										=      leap_day_inhibits / 4
  lowerCAmelCase__										=      (
      15 - lunar_orbit_correction + leap_day_inhibits - leap_day_reinstall_number
  ) % 30
  lowerCAmelCase__										=      (4 + leap_day_inhibits - leap_day_reinstall_number) % 7

  # days to be added to March 21
  lowerCAmelCase__										=      (19 * metonic_cycle + secular_moon_shift) % 30

  # PHM -> Paschal Full Moon
  lowerCAmelCase__										=      (
      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(__lowerCAmelCase   , 4   , 19				)
  elif days_to_add == 28 and days_from_phm_to_sunday == 6:
    return datetime(__lowerCAmelCase   , 4   , 18				)
  else:
    return datetime(__lowerCAmelCase   , 3   , 22				) + timedelta(
        days=int(days_to_add + days_from_phm_to_sunday				)				)


if __name__ == "__main__":
      for year in (19_94, 20_00, 20_10, 20_21, 20_23):
            __magic_name__  :  Dict					=       """will be""" if year > datetime.now().year else """was"""
            print(F"Easter in {year} {tense} {gauss_easter(year)}")







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

