


'''simple docstring'''




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 	a_					( lowerCamelCase	:     list[list[int]]				):
   lowerCAmelCase     =			[]
   for i in range(len(lowerCamelCase				)				):
      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(lowerCamelCase				) - 1 and j > 0:
            neighbour_count += cells[i + 1][j - 1]
         if i < len(lowerCamelCase				) - 1:
            neighbour_count += cells[i + 1][j]
         if i < len(lowerCamelCase				) - 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(lowerCamelCase				)
   return next_generation





def 	a_					( lowerCamelCase	:     list[list[int]]	, lowerCamelCase	:     int				):
   lowerCAmelCase     =			[]
   for _ in range(lowerCamelCase				):
      # Create output image
      lowerCAmelCase     =			Image.new('RGB'	, (len(cells[0]				), len(lowerCamelCase				))				)
      lowerCAmelCase     =			img.load()

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

        # Save image
      images.append(lowerCamelCase				)
      lowerCAmelCase     =			new_generation(lowerCamelCase				)
   return images


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












'''simple docstring'''

import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase_					= logging.getLogger(__name__)

if __name__ == "__main__":
      lowercase_					= argparse.ArgumentParser(
          description="""Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)"""
      )
      parser.add_argument(
          """--data_file""", type=str, default="""data/dump.bert-base-uncased.pickle""", help="""The binarized dataset."""
      )
      parser.add_argument(
          """--token_counts_dump""", type=str, default="""data/token_counts.bert-base-uncased.pickle""", help="""The dump file."""
      )
      parser.add_argument("""--vocab_size""", default=30_522, type=int)
      lowercase_					= parser.parse_args()

      logger.info(f"""Loading data from {args.data_file}""")
      with open(args.data_file, """rb""") as fp:
            lowercase_					= pickle.load(fp)

      logger.info("""Counting occurrences for MLM.""")
      lowercase_					= Counter()
      for tk_ids in data:
            counter.update(tk_ids)
      lowercase_					= [0] * args.vocab_size
      for k, v in counter.items():
            lowercase_					= v

      logger.info(f"""Dump to {args.token_counts_dump}""")
      with open(args.token_counts_dump, """wb""") as handle:
            pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)



