


"""simple docstring"""






def __lowercase     (      lowerCamelCase_  :      int						,					lowerCamelCase_  :      int  ):
				return x if y == 0 else greatest_common_divisor(lowerCamelCase_						,					x % y  )


def __lowercase     (      lowerCamelCase_  :      int						,					lowerCamelCase_  :      int  ):
				return (x * y) // greatest_common_divisor(lowerCamelCase_						,					lowerCamelCase_  )


def __lowercase     (      lowerCamelCase_  :      int = 20  ):
				SCREAMING_SNAKE_CASE__     							=				1
				for i in range(1						,					n + 1  ):
								SCREAMING_SNAKE_CASE__     							=				lcm(lowerCamelCase_						,					lowerCamelCase_  )
				return g


if __name__ == "__main__":
	print(f"""{solution() = }""")




"""simple docstring"""






from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase     =  {
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase     =  [
	    'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'AutoformerForPrediction',
	    'AutoformerModel',
	    'AutoformerPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_autoformer import (
	    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    AutoformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_autoformer import (
		    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    AutoformerForPrediction,
		    AutoformerModel,
		    AutoformerPreTrainedModel,
		)

else:
	import sys

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