





def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__						):
		return x if y == 0 else greatest_common_divisor(lowerCAmelCase__							,x % y						)


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__						):
		return (x * y) // greatest_common_divisor(lowerCAmelCase__							,lowerCAmelCase__						)


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__ = 20						):
		lowerCamelCase_	:     Optional[int] 						=      1
		for i in range(1							,n + 1						):
				lowerCamelCase_	:     List[str] 						=      lcm(lowerCAmelCase__							,lowerCAmelCase__						)
		return g


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







_lowercase		:  Optional[Any]			       ="""
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

_lowercase		:  Union[str, Any]			       =[{"""type""": """code""", """content""": INSTALL_CONTENT}]
_lowercase		:  List[Any]			       ={
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}
