


from __future__ import annotations

import math
def      _a					( SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		if depth < 0:
				raise ValueError('''Depth cannot be less than 0'''	)

		if len(SCREAMING_SNAKE_CASE	) == 0:
				raise ValueError('''Scores cannot be empty'''	)

		if depth == height:
				return scores[node_index]

		if is_max:
				return max(
				    minimax(depth + 1		,							node_index * 2		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	)		,							minimax(depth + 1		,							node_index * 2 + 1		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	)		,							)

		return min(
		    minimax(depth + 1		,							node_index * 2		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	)		,							minimax(depth + 1		,							node_index * 2 + 1		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	)		,							)
def      _a					( ):


		"""simple docstring"""




		lowercase__				= [90, 23, 6, 33, 21, 65, 1_23, 3_44_23]
		lowercase__				= math.log(len(SCREAMING_SNAKE_CASE	)		,							2	)
		print('''Optimal value : '''		,							end=''''''	)
		print(minimax(0		,							0		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE	)	)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			main()




import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer



def   __lowerCAmelCase    (				UpperCAmelCase__					:   str      ,					UpperCAmelCase__					:   str      ,					**UpperCAmelCase__					:   List[str]							)	->     Tuple:
							lowerCamelCase_					=       AutoConfig.from_pretrained(UpperCAmelCase__      ,					**UpperCAmelCase__							)
							lowerCamelCase_					=       AutoModelForSeqaSeqLM.from_config(UpperCAmelCase__							)
							model.save_pretrained(UpperCAmelCase__							)
							AutoTokenizer.from_pretrained(UpperCAmelCase__							).save_pretrained(UpperCAmelCase__							)
							return model


if __name__ == "__main__":
		fire.Fire(save_randomly_initialized_version)





