






from dataclasses import dataclass
from typing import Callable, Optional

import datasets




@dataclass
class 							__A	(     datasets.BuilderConfig					):





				"""simple docstring"""







				UpperCamelCase__					: Optional[Callable]     					=None
				UpperCamelCase__					: Optional[dict]     					=None
				UpperCamelCase__					: Optional[datasets.Features]     					=None


				def  __lowercase				(					self       ):




									"""simple docstring"""

									assert self.generator is not None, "generator must be specified"

									if self.gen_kwargs is None:
														__UpperCamelCase :   Dict									={}




class 							__A	(     datasets.GeneratorBasedBuilder					):





				"""simple docstring"""







				UpperCamelCase__					: int     					=GeneratorConfig


				def  __lowercase				(					self       ):




									"""simple docstring"""

									return datasets.DatasetInfo(features=self.config.features       )


				def  __lowercase				(					self				,    lowerCamelCase__       ):




									"""simple docstring"""

									return [datasets.SplitGenerator(name=datasets.Split.TRAIN				,    gen_kwargs=self.config.gen_kwargs       )]







				def  __lowercase				(					self				,    **lowerCamelCase__       ):




									"""simple docstring"""

									for idx, ex in enumerate(self.config.generator(**lowerCamelCase__       )       ):
														yield idx, ex









from __future__ import annotations






def 				A	(			a_				,a_   )	->		list[int]:
					__UpperCamelCase :   dict[int, int]									={}
					for index, val in enumerate(a_   ):
										__UpperCamelCase :   Union[str, Any]									=target - val
										if compl in chk_map:
															return [chk_map[compl], index]
										__UpperCamelCase :   List[Any]									=index
					return []


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							print(f"{two_sum([2, 7, 11, 15], 9) = }")

