"""simple docstring"""
from __future__ import annotations







def 						__a   (	_SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE   )	->list[tuple[int, int]]:
  a__:     Optional[Any]										=	position
  a__:     Union[str, Any]										=	[
      (y + 1, x + 2),
      (y - 1, x + 2),
      (y + 1, x - 2),
      (y - 1, x - 2),
      (y + 2, x + 1),
      (y + 2, x - 1),
      (y - 2, x + 1),
      (y - 2, x - 1),
  ]
  a__:     int										=	[]

  for position in positions:
    a__:     Tuple										=	position
    if 0 <= y_test < n and 0 <= x_test < n:
      permissible_positions.append(_SCREAMING_SNAKE_CASE   )

  return permissible_positions







def 						__a   (	_SCREAMING_SNAKE_CASE   )	->bool:
  return not any(elem == 0 for row in board for elem in row   )







def 						__a   (	_SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE   )	->bool:

  if is_complete(_SCREAMING_SNAKE_CASE   ):
    return True

  for position in get_valid_pos(_SCREAMING_SNAKE_CASE		,     len(_SCREAMING_SNAKE_CASE   )   ):
    a__:     Any										=	position

    if board[y][x] == 0:
      a__:     List[str]										=	curr + 1
      if open_knight_tour_helper(_SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE		,     curr + 1   ):
        return True
      a__:     Optional[Any]										=	0

  return False







def 						__a   (	_SCREAMING_SNAKE_CASE   )	->list[list[int]]:
  a__:     Optional[int]										=	[[0 for i in range(_SCREAMING_SNAKE_CASE   )] for j in range(_SCREAMING_SNAKE_CASE   )]

  for i in range(_SCREAMING_SNAKE_CASE   ):
    for j in range(_SCREAMING_SNAKE_CASE   ):
      a__:     Optional[Any]										=	1
      if open_knight_tour_helper(_SCREAMING_SNAKE_CASE		,     (i, j)		,     1   ):
        return board
      a__:     Any										=	0

  a__:     List[str]										=	F'Open Kight Tour cannot be performed on a board of size {n}'
  raise ValueError(_SCREAMING_SNAKE_CASE   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()









import argparse
import json

from tqdm import tqdm







def  _SCREAMING_SNAKE_CASE				(   )      ->      List[Any]:
					__A	:						Tuple       =				argparse.ArgumentParser()

					# Required parameters
					parser.add_argument(
					    '--src_path'					,						type=a					,						default='biencoder-nq-dev.json'					,						help='Path to raw DPR training data'					,						)
					parser.add_argument(
					    '--evaluation_set'					,						type=a					,						help='where to store parsed evaluation_set file'					,						)
					parser.add_argument(
					    '--gold_data_path'					,						type=a					,						help='where to store parsed gold_data_path file'					,						)
					__A	:						Optional[int]       =				parser.parse_args()

					with open(args.src_path					,						'r'  ) as src_file, open(args.evaluation_set					,						'w'  ) as eval_file, open(
					    args.gold_data_path					,						'w'  ) as gold_file:
										__A	:						List[Any]       =				json.load(a  )
										for dpr_record in tqdm(a  ):
															__A	:						Dict       =				dpr_record['question']
															__A	:						Any       =				[context['title'] for context in dpr_record['positive_ctxs']]
															eval_file.write(question + '\n'  )
															gold_file.write('\t'.join(a  ) + '\n'  )


if __name__ == "__main__":
				main()




