
"""simple docstring"""







import math
from datetime import datetime, timedelta
def 					__lowerCAmelCase       (_UpperCamelCase	):
	__lowerCAmelCase    :		Tuple		    =   year % 19
	__lowerCAmelCase    :		Dict		    =   year % 4
	__lowerCAmelCase    :		int		    =   year % 7
	__lowerCAmelCase    :		Tuple		    =   math.floor(year / 100	)
	__lowerCAmelCase    :		Optional[Any]		    =   math.floor((13 + 8 * leap_day_inhibits) / 25	)
	__lowerCAmelCase    :		Any		    =   leap_day_inhibits / 4
	__lowerCAmelCase    :		Tuple		    =   (
	    15 - lunar_orbit_correction + leap_day_inhibits - leap_day_reinstall_number
	) % 30
	__lowerCAmelCase    :		Union[str, Any]		    =   (4 + leap_day_inhibits - leap_day_reinstall_number) % 7

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

	# PHM -> Paschal Full Moon
	__lowerCAmelCase    :		List[str]		    =   (
	    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(_UpperCamelCase ,						4 ,						19	)
	elif days_to_add == 28 and days_from_phm_to_sunday == 6:
		return datetime(_UpperCamelCase ,						4 ,						18	)
	else:
		return datetime(_UpperCamelCase ,						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):
														lowerCamelCase__           =	"""will be""" if year > datetime.now().year else """was"""
														print(f'Easter in {year} {tense} {gauss_easter(year)}')

"""simple docstring"""







from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def 					__lowerCAmelCase       ():
	__lowerCAmelCase    :		Tuple		    =   HfArgumentParser(_UpperCamelCase	)
	__lowerCAmelCase    :		Optional[Any]		    =   parser.parse_args_into_dataclasses()[0]
	__lowerCAmelCase    :		int		    =   TensorFlowBenchmark(args=_UpperCamelCase	)
	try:
		__lowerCAmelCase    :		Dict		    =   parser.parse_args_into_dataclasses()[0]
	except ValueError as e:
		__lowerCAmelCase    :		List[Any]		    =   'Arg --no_{0} is no longer used, please use --no-{0} instead.'
		__lowerCAmelCase    :		Union[str, Any]		    =   ' '.join(str(_UpperCamelCase	).split(' '	)[:-1]	)
		__lowerCAmelCase    :		List[str]		    =   ''
		__lowerCAmelCase    :		Any		    =   eval(str(_UpperCamelCase	).split(' '	)[-1]	)
		__lowerCAmelCase    :		Dict		    =   []
		for arg in depreciated_args:
			# arg[2:] removes '--'
			if arg[2:] in TensorFlowBenchmark.deprecated_args:
				# arg[5:] removes '--no_'
				full_error_msg += arg_error_msg.format(arg[5:]	)
			else:
				wrong_args.append(_UpperCamelCase	)
		if len(_UpperCamelCase	) > 0:
			__lowerCAmelCase    :		Any		    =   full_error_msg + begin_error_msg + str(_UpperCamelCase	)
		raise ValueError(_UpperCamelCase	)
	benchmark.run()


if __name__ == "__main__":
							main()