"""simple docstring"""
def 				lowerCAmelCase__      (     _UpperCamelCase    :			int	,     _UpperCamelCase    :			int   )   ->			int:





						"""simple docstring"""






						return x if y == 0 else greatest_common_divisor(_UpperCamelCase	,     x % y   )





def 				lowerCAmelCase__      (     _UpperCamelCase    :			int	,     _UpperCamelCase    :			int   )   ->			int:





						"""simple docstring"""






						return (x * y) // greatest_common_divisor(_UpperCamelCase	,     _UpperCamelCase   )





def 				lowerCAmelCase__      (     _UpperCamelCase    :			int = 2_0   )   ->			int:





						"""simple docstring"""






						snake_case        =     1
						for i in range(1	,     n + 1   ):
												snake_case        =     lcm(_UpperCamelCase	,     _UpperCamelCase   )
						return g


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



"""simple docstring"""
import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu



@require_cpu
class 					lowerCAmelCase_      (     unittest.TestCase   ):



				"""simple docstring"""

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     torch.nn.Linear(10						,      10      )
										snake_case        =     torch.optim.SGD(model.parameters()						,      0.1      )
										snake_case        =     Accelerator()
										snake_case        =     accelerator.prepare(lowerCAmelCase      )
										try:
																pickle.loads(pickle.dumps(lowerCAmelCase      )      )
										except Exception as e:
																self.fail(F"""Accelerated optimizer pickling failed with {e}"""      )
										AcceleratorState._reset_state()


