





'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__magic_name__   :						Optional[int]    =			logging.get_logger(__name__)

__magic_name__   :						Optional[int]    =			{
    """kssteven/ibert-roberta-base""": """https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json""",
    """kssteven/ibert-roberta-large""": """https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json""",
    """kssteven/ibert-roberta-large-mnli""": (
        """https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json"""
    ),
}


class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase			):



       '''simple docstring'''






       UpperCAmelCase__       :						List[Any]      =   '''ibert'''

       def __init__(					self						,   lowerCamelCase=30_522						,   lowerCamelCase=768						,   lowerCamelCase=12						,   lowerCamelCase=12						,   lowerCamelCase=3_072						,   lowerCamelCase="gelu"						,   lowerCamelCase=0.1						,   lowerCamelCase=0.1						,   lowerCamelCase=512						,   lowerCamelCase=2						,   lowerCamelCase=0.02						,   lowerCamelCase=1e-12						,   lowerCamelCase=1						,   lowerCamelCase=0						,   lowerCamelCase=2						,   lowerCamelCase="absolute"						,   lowerCamelCase=False						,   lowerCamelCase="none"						,   **lowerCamelCase						,   ):
         super().__init__(pad_token_id=lowerCamelCase						,   bos_token_id=lowerCamelCase						,   eos_token_id=lowerCamelCase						,   **lowerCamelCase	)

         _snake_case     		=				vocab_size
         _snake_case     		=				hidden_size
         _snake_case     		=				num_hidden_layers
         _snake_case     		=				num_attention_heads
         _snake_case     		=				hidden_act
         _snake_case     		=				intermediate_size
         _snake_case     		=				hidden_dropout_prob
         _snake_case     		=				attention_probs_dropout_prob
         _snake_case     		=				max_position_embeddings
         _snake_case     		=				type_vocab_size
         _snake_case     		=				initializer_range
         _snake_case     		=				layer_norm_eps
         _snake_case     		=				position_embedding_type
         _snake_case     		=				quant_mode
         _snake_case     		=				force_dequant







class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase			):



       '''simple docstring'''






       @property
       def 	UpperCamelCase(					self	):
         if self.task == "multiple-choice":
           _snake_case     		=				{0: "batch", 1: "choice", 2: "sequence"}
         else:
           _snake_case     		=				{0: "batch", 1: "sequence"}
         return OrderedDict(
             [
                 ("input_ids", dynamic_axis),
                 ("attention_mask", dynamic_axis),
             ]	)









'''simple docstring'''



from __future__ import annotations

from PIL import Image

# Define glider example
__magic_name__   :						str    =			[
    [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
__magic_name__   :						List[Any]    =			[[0, 1, 0], [0, 1, 0], [0, 1, 0]]




def 				snake_case_      (		SCREAMING_SNAKE_CASE__       ):







  '''simple docstring'''



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




def 				snake_case_      (		SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__       ):







  '''simple docstring'''



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

    # Save cells to image
    for x in range(len(SCREAMING_SNAKE_CASE__       )       ):
      for y in range(len(cells[0]       )       ):
        _snake_case     		=				2_55 - cells[y][x] * 2_55
        _snake_case     		=				(colour, colour, colour)

        # Save image
    images.append(SCREAMING_SNAKE_CASE__       )
    _snake_case     		=				new_generation(SCREAMING_SNAKE_CASE__       )
  return images


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


