





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       (   __magic_name__	):
   lowercase__			       =  []
   for i in range(len(lowerCAmelCase__	)	):
      lowercase__			       =  []
      for j in range(len(cells[i]	)	):
         # Get the number of live neighbours
         lowercase__			       =  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.
         lowercase__			       =  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       (   __magic_name__  , __magic_name__	):
   lowercase__			       =  []
   for _ in range(lowerCAmelCase__	):
      # Create output image
      lowercase__			       =  Image.new("RGB"  , (len(cells[0]	), len(lowerCAmelCase__	))	)
      lowercase__			       =  img.load()

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

        # Save image
      images.append(lowerCAmelCase__	)
      lowercase__			       =  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:])













from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_snake_case           =			{
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _snake_case           =			[
      """AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """AutoformerForPrediction""",
      """AutoformerModel""",
      """AutoformerPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_autoformer import (
      AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      AutoformerConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_autoformer import (
        AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        AutoformerForPrediction,
        AutoformerModel,
        AutoformerPreTrainedModel,
    )

else:
  import sys

  _snake_case           =			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






