'''simple docstring'''




__lowercase          =  [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__lowercase          =  [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__lowercase          =  {
    0: '''Sunday''',
    1: '''Monday''',
    2: '''Tuesday''',
    3: '''Wednesday''',
    4: '''Thursday''',
    5: '''Friday''',
    6: '''Saturday''',
}






def 				snake_case__							(			_A:					int      ,   _A:					int      ,   _A:					int )    ->	str:

		'''simple docstring'''


		assert len(str(_A ) ) > 2, "year should be in YYYY format"
		assert 1 <= month <= 12, "month should be between 1 to 12"
		assert 1 <= day <= 31, "day should be between 1 to 31"

		# Doomsday algorithm:
		lowerCAmelCase   					=  year // 100
		lowerCAmelCase   					=  (5 * (century % 4) + 2) % 7
		lowerCAmelCase   					=  year % 100
		lowerCAmelCase   					=  centurian % 12
		lowerCAmelCase   					=  (
		    (centurian // 12) + centurian_m + (centurian_m // 4) + century_anchor
		) % 7
		lowerCAmelCase   					=  (
		    DOOMSDAY_NOT_LEAP[month - 1]
		    if (year % 4 != 0) or (centurian == 0 and (year % 400) == 0)
		    else DOOMSDAY_LEAP[month - 1]
		)
		lowerCAmelCase   					=  (dooms_day + day - day_anchor) % 7
		return WEEK_DAY_NAMES[week_day]


if __name__ == "__main__":
						import doctest

						doctest.testmod()





'''simple docstring'''




from typing import TYPE_CHECKING

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


__lowercase          =  {
    '''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''NezhaForNextSentencePrediction''',
						    '''NezhaForMaskedLM''',
						    '''NezhaForPreTraining''',
						    '''NezhaForMultipleChoice''',
						    '''NezhaForQuestionAnswering''',
						    '''NezhaForSequenceClassification''',
						    '''NezhaForTokenClassification''',
						    '''NezhaModel''',
						    '''NezhaPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_nezha import (
												    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
												    NezhaForMaskedLM,
												    NezhaForMultipleChoice,
												    NezhaForNextSentencePrediction,
												    NezhaForPreTraining,
												    NezhaForQuestionAnswering,
												    NezhaForSequenceClassification,
												    NezhaForTokenClassification,
												    NezhaModel,
												    NezhaPreTrainedModel,
												)


else:
						import sys

						__lowercase          =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




