


import math
from datetime import datetime, timedelta



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

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

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


if __name__ == "__main__":
    for year in (1994, 2000, 2010, 2021, 2023):
        UpperCamelCase					:       Tuple			    =     """will be""" if year > datetime.now().year else """was"""
        print(f"""Easter in {year} {tense} {gauss_easter(year)}""")






'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A__    :   Optional[Any]           =					{
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   Tuple           =					['''SqueezeBertTokenizerFast''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   str           =					[
        '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''SqueezeBertForMaskedLM''',
        '''SqueezeBertForMultipleChoice''',
        '''SqueezeBertForQuestionAnswering''',
        '''SqueezeBertForSequenceClassification''',
        '''SqueezeBertForTokenClassification''',
        '''SqueezeBertModel''',
        '''SqueezeBertModule''',
        '''SqueezeBertPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_squeezebert import (
        SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        SqueezeBertConfig,
        SqueezeBertOnnxConfig,
    )
    from .tokenization_squeezebert import SqueezeBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_squeezebert import (
            SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            SqueezeBertForMaskedLM,
            SqueezeBertForMultipleChoice,
            SqueezeBertForQuestionAnswering,
            SqueezeBertForSequenceClassification,
            SqueezeBertForTokenClassification,
            SqueezeBertModel,
            SqueezeBertModule,
            SqueezeBertPreTrainedModel,
        )

else:
    import sys

    A__    :   List[Any]           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



