




from __future__ import annotations

from PIL import Image

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







def      _a				(						SCREAMING_SNAKE_CASE_							:    list[list[int]]					):
					__lowerCAmelCase           =	[]
					for i in range(len(SCREAMING_SNAKE_CASE_					)					):
										__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(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.
															__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(SCREAMING_SNAKE_CASE_					)
					return next_generation







def      _a				(						SCREAMING_SNAKE_CASE_							:    list[list[int]]				,				SCREAMING_SNAKE_CASE_							:    int					):
					__lowerCAmelCase           =	[]
					for _ in range(SCREAMING_SNAKE_CASE_					):
										# Create output image
										__lowerCAmelCase           =	Image.new("RGB"				,				(len(cells[0]					), len(SCREAMING_SNAKE_CASE_					))					)
										__lowerCAmelCase           =	img.load()

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

        # Save image
										images.append(SCREAMING_SNAKE_CASE_					)
										__lowerCAmelCase           =	new_generation(SCREAMING_SNAKE_CASE_					)
					return images


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










from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__         =      logging.get_logger(__name__)

UpperCamelCase__         =      {
    """alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}
class       a__   ( snake_case__				):
						_a							:   Dict =   """mgp-str"""






						def __init__(       self		,      _A=[3_2, 1_2_8]		,      _A=4		,      _A=3		,      _A=2_7		,      _A=3_8		,      _A=5_0_2_5_7		,      _A=3_0_5_2_2		,      _A=7_6_8		,      _A=1_2		,      _A=1_2		,      _A=4.0		,      _A=True		,      _A=False		,      _A=1E-5		,      _A=0.0		,      _A=0.0		,      _A=0.0		,      _A=False		,      _A=0.02		,      **_A		,      ):




											"""simple docstring"""



											super().__init__(**_A      )

											__lowerCAmelCase           =	image_size
											__lowerCAmelCase           =	patch_size
											__lowerCAmelCase           =	num_channels
											__lowerCAmelCase           =	max_token_length
											__lowerCAmelCase           =	num_character_labels
											__lowerCAmelCase           =	num_bpe_labels
											__lowerCAmelCase           =	num_wordpiece_labels
											__lowerCAmelCase           =	hidden_size
											__lowerCAmelCase           =	num_hidden_layers
											__lowerCAmelCase           =	num_attention_heads
											__lowerCAmelCase           =	mlp_ratio
											__lowerCAmelCase           =	distilled
											__lowerCAmelCase           =	layer_norm_eps
											__lowerCAmelCase           =	drop_rate
											__lowerCAmelCase           =	qkv_bias
											__lowerCAmelCase           =	attn_drop_rate
											__lowerCAmelCase           =	drop_path_rate
											__lowerCAmelCase           =	output_aa_attentions
											__lowerCAmelCase           =	initializer_range




