from __future__ import annotations

from PIL import Image

# Define glider example
snake_case__				= [
    [0, 1, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0, 0],
    [1, 1, 1, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
]

# Define blinker example
snake_case__				= [[0, 1, 0], [0, 1, 0], [0, 1, 0]]
def       __magic_name__(  __UpperCAmelCase		)						->    list[list[int]]:



      '''simple docstring'''

      _lowerCamelCase			    =				[]
      for i in range(len(__UpperCAmelCase		)		):
            _lowerCamelCase			    =				[]
            for j in range(len(cells[i]		)		):
                  # Get the number of live neighbours
                  _lowerCamelCase			    =				0
                  if i > 0 and j > 0:
                        neighbour_count += cells[i - 1][j - 1]
                  if i > 0:
                        neighbour_count += cells[i - 1][j]
                  if i > 0 and j < len(cells[i]		) - 1:
                        neighbour_count += cells[i - 1][j + 1]
                  if j > 0:
                        neighbour_count += cells[i][j - 1]
                  if j < len(cells[i]		) - 1:
                        neighbour_count += cells[i][j + 1]
                  if i < len(__UpperCAmelCase		) - 1 and j > 0:
                        neighbour_count += cells[i + 1][j - 1]
                  if i < len(__UpperCAmelCase		) - 1:
                        neighbour_count += cells[i + 1][j]
                  if i < len(__UpperCAmelCase		) - 1 and j < len(cells[i]		) - 1:
                        neighbour_count += cells[i + 1][j + 1]

                  # Rules of the game of life (excerpt from Wikipedia):
                  # 1. Any live cell with two or three live neighbours survives.
                  # 2. Any dead cell with three live neighbours becomes a live cell.
                  # 3. All other live cells die in the next generation.
                  #    Similarly, all other dead cells stay dead.
                  _lowerCamelCase			    =				cells[i][j] == 1
                  if (
                      (alive and 2 <= neighbour_count <= 3)
                      or not alive
                      and neighbour_count == 3
                  ):
                        next_generation_row.append(1		)
                  else:
                        next_generation_row.append(0		)

            next_generation.append(__UpperCAmelCase		)
      return next_generation
def       __magic_name__(  __UpperCAmelCase ,						__UpperCAmelCase		)						->    list[Image.Image]:



      '''simple docstring'''

      _lowerCamelCase			    =				[]
      for _ in range(__UpperCAmelCase		):
            # Create output image
            _lowerCamelCase			    =				Image.new('''RGB''' ,						(len(cells[0]		), len(__UpperCAmelCase		))		)
            _lowerCamelCase			    =				img.load()

            # Save cells to image
            for x in range(len(__UpperCAmelCase		)		):
                  for y in range(len(cells[0]		)		):
                        _lowerCamelCase			    =				255 - cells[y][x] * 255
                        _lowerCamelCase			    =				(colour, colour, colour)

        # Save image
            images.append(__UpperCAmelCase		)
            _lowerCamelCase			    =				new_generation(__UpperCAmelCase		)
      return images


if __name__ == "__main__":
     snake_case__				= generate_images(GLIDER, 16)
     images[0].save('out.gif', save_all=True, append_images=images[1:])
import argparse
import json

from tqdm import tqdm
def       __magic_name__(  )						->    List[str]:



      '''simple docstring'''

      _lowerCamelCase			    =				argparse.ArgumentParser()

      # Required parameters
      parser.add_argument(
          '''--src_path''' ,						type=__UpperCAmelCase ,						default='''biencoder-nq-dev.json''' ,						help='''Path to raw DPR training data''' ,						)
      parser.add_argument(
          '''--evaluation_set''' ,						type=__UpperCAmelCase ,						help='''where to store parsed evaluation_set file''' ,						)
      parser.add_argument(
          '''--gold_data_path''' ,						type=__UpperCAmelCase ,						help='''where to store parsed gold_data_path file''' ,						)
      _lowerCamelCase			    =				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:
            _lowerCamelCase			    =				json.load(__UpperCAmelCase		)
            for dpr_record in tqdm(__UpperCAmelCase		):
                  _lowerCamelCase			    =				dpr_record['''question''']
                  _lowerCamelCase			    =				[context['''title'''] for context in dpr_record['''positive_ctxs''']]
                  eval_file.write(question + '''\n'''		)
                  gold_file.write('''\t'''.join(__UpperCAmelCase		) + '''\n'''		)


if __name__ == "__main__":
     main()