from __future__ import annotations

import math
def  snake_case						(__lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase						)	->	int:

						'''simple docstring'''



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

						if len(__lowercase						) == 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 ,      __lowercase ,      __lowercase ,      __lowercase						) ,      minimax(depth + 1 ,      node_index * 2 + 1 ,      __lowercase ,      __lowercase ,      __lowercase						) ,      )

						return min(
						    minimax(depth + 1 ,      node_index * 2 ,      __lowercase ,      __lowercase ,      __lowercase						) ,      minimax(depth + 1 ,      node_index * 2 + 1 ,      __lowercase ,      __lowercase ,      __lowercase						) ,      )
def  snake_case						()	->	None:

						'''simple docstring'''



						_snake_case						:					str    =   [90, 23, 6, 33, 21, 65, 123, 34_423]
						_snake_case						:					Union[str, Any]    =   math.log(len(__lowercase						) ,      2						)
						print("Optimal value : " ,      end=""						)
						print(minimax(0 ,      0 ,      __lowercase ,      __lowercase ,      __lowercase						)						)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()
import logging

from transformers import PretrainedConfig


__SCREAMING_SNAKE_CASE						:   Any         =			logging.getLogger(__name__)


__SCREAMING_SNAKE_CASE						:   int         =			{
    'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json',
}



class        lowercase_   (					__snake_case		):
							_lowerCamelCase						=		'bertabs'



							def __init__(						self				,    lowercase_=30_522				,    lowercase_=512				,    lowercase_=6				,    lowercase_=512				,    lowercase_=8				,    lowercase_=512				,    lowercase_=0.2				,    lowercase_=6				,    lowercase_=768				,    lowercase_=8				,    lowercase_=2_048				,    lowercase_=0.2				,    **lowercase_				,    ):
													super().__init__(**lowercase_    )

													_snake_case						:					List[Any]    =   vocab_size
													_snake_case						:					int    =   max_pos

													_snake_case						:					Tuple    =   enc_layers
													_snake_case						:					Optional[Any]    =   enc_hidden_size
													_snake_case						:					Union[str, Any]    =   enc_heads
													_snake_case						:					str    =   enc_ff_size
													_snake_case						:					Any    =   enc_dropout

													_snake_case						:					Tuple    =   dec_layers
													_snake_case						:					Optional[Any]    =   dec_hidden_size
													_snake_case						:					Dict    =   dec_heads
													_snake_case						:					str    =   dec_ff_size
													_snake_case						:					List[str]    =   dec_dropout