'''simple docstring'''




from __future__ import annotations





class        __magic_name__		:







			def __init__(      self							:    Tuple							,     lowercase_							:    int = 0       ):
										lowercase_   :     Dict									=			value
										lowercase_   :     Node | None									=			None
										lowercase_   :     Node | None									=			None




def 				lowerCamelCase      ( UpperCAmelCase__			:   Node | None , UpperCAmelCase__			:   Node | None					)     -> Node | None:
							if treea is None:
														return treea
							if treea is None:
														return treea

							lowercase_   :     Optional[int]									=			treea.value + treea.value
							lowercase_   :     int									=			merge_two_binary_trees(treea.left , treea.left					)
							lowercase_   :     List[Any]									=			merge_two_binary_trees(treea.right , treea.right					)
							return treea




def 				lowerCamelCase      ( UpperCAmelCase__			:   Node | None					)     -> None:
							if root:
														print(root.value					)
														print_preorder(root.left					)
														print_preorder(root.right					)


if __name__ == "__main__":
						_lowercase		:					Dict													=		Node(1)
						_lowercase		:					List[str]													=		Node(2)
						_lowercase		:					int													=		Node(3)
						_lowercase		:					str													=		Node(4)

						_lowercase		:					Optional[int]													=		Node(2)
						_lowercase		:					Any													=		Node(4)
						_lowercase		:					Union[str, Any]													=		Node(6)
						_lowercase		:					Optional[int]													=		Node(9)
						_lowercase		:					Dict													=		Node(5)

						print("Tree1 is: ")
						print_preorder(treea)
						print("Tree2 is: ")
						print_preorder(treea)
						_lowercase		:					int													=		merge_two_binary_trees(treea, treea)
						print("Merged Tree is: ")
						print_preorder(merged_tree)






'''simple docstring'''




from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments




def 				lowerCamelCase      ( )     -> List[Any]:
							lowercase_   :     Tuple									=			HfArgumentParser(UpperCAmelCase__					)
							try:
														lowercase_   :     List[Any]									=			parser.parse_args_into_dataclasses()[0]
							except ValueError as e:
														lowercase_   :     int									=			"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
														lowercase_   :     Any									=			""" """.join(str(UpperCAmelCase__					).split(""" """					)[:-1]					)
														lowercase_   :     Optional[Any]									=			""""""
														lowercase_   :     List[str]									=			eval(str(UpperCAmelCase__					).split(""" """					)[-1]					)
														lowercase_   :     Dict									=			[]
														for arg in depreciated_args:
																					# arg[2:] removes '--'
																					if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
																												# arg[5:] removes '--no_'
																												full_error_msg += arg_error_msg.format(arg[5:]					)
																					else:
																												wrong_args.append(UpperCAmelCase__					)
														if len(UpperCAmelCase__					) > 0:
																					lowercase_   :     Dict									=			full_error_msg + begin_error_msg + str(UpperCAmelCase__					)
														raise ValueError(UpperCAmelCase__					)

							lowercase_   :     Optional[int]									=			PyTorchBenchmark(args=UpperCAmelCase__					)
							benchmark.run()


if __name__ == "__main__":
						main()





