
'''simple docstring'''
from __future__ import annotations

from PIL import Image

# Define the first generation of cells
# fmt: off
a_           =    [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
          0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]

def     UpperCamelCase_  (						__SCREAMING_SNAKE_CASE							):
    """simple docstring"""






    return [int(__SCREAMING_SNAKE_CASE							) for c in f'{ruleset:08}'[:8]]

def     UpperCamelCase_  (						__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE							):
    """simple docstring"""






    snake_case_			:     int        =    len(cells[0]							)  # 31
    snake_case_			:     int        =    []
    for i in range(__SCREAMING_SNAKE_CASE							):
        # Get the neighbors of each cell
        # Handle neighbours outside bounds by using 0 as their value
        snake_case_			:     Tuple        =    0 if i == 0 else cells[time][i - 1]
        snake_case_			:     List[Any]        =    0 if i == population - 1 else cells[time][i + 1]
        # Define a new cell and add it to the new generation
        snake_case_			:     Optional[int]        =    7 - int(f'{left_neighbor}{cells[time][i]}{right_neighbor}',		2							)
        next_generation.append(rule[situation]							)
    return next_generation

def     UpperCamelCase_  (						__SCREAMING_SNAKE_CASE							):
    """simple docstring"""






    snake_case_			:     List[Any]        =    Image.new("RGB",		(len(cells[0]							), len(__SCREAMING_SNAKE_CASE							))							)
    snake_case_			:     Optional[Any]        =    img.load()
    # Generates image
    for w in range(img.width							):
        for h in range(img.height							):
            snake_case_			:     Optional[Any]        =    2_5_5 - int(2_5_5 * cells[h][w]							)
            snake_case_			:     Union[str, Any]        =    (color, color, color)
    return img


if __name__ == "__main__":
  a_           =    bin(int(input("Rule:\n").strip()))[2:]
  a_           =    format_ruleset(int(rule_num))
  for time in range(16):
    CELLS.append(new_generation(CELLS, rule, time))
  a_           =    generate_image(CELLS)
  # Uncomment to save the image
  # img.save(f"rule_{rule_num}.png")
  img.show()






'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


a_           =    {
    "configuration_sam": [
        "SAM_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SamConfig",
        "SamMaskDecoderConfig",
        "SamPromptEncoderConfig",
        "SamVisionConfig",
    ],
    "processing_sam": ["SamProcessor"],
}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_           =    [
      "SAM_PRETRAINED_MODEL_ARCHIVE_LIST",
      "SamModel",
      "SamPreTrainedModel",
  ]
try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_           =    [
      "TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TFSamModel",
      "TFSamPreTrainedModel",
  ]
try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_           =    ["SamImageProcessor"]


if TYPE_CHECKING:
  from .configuration_sam import (
      SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
      SamConfig,
      SamMaskDecoderConfig,
      SamPromptEncoderConfig,
      SamVisionConfig,
  )
  from .processing_sam import SamProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_sam import SamImageProcessor

else:
  import sys

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




