






'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

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


__magic_name__		:     List[str]					=    logging.get_logger(__name__)

__magic_name__		:     Any					=    {
    '''nvidia/segformer-b0-finetuned-ade-512-512''': (
        '''https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'''
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}







class 	UpperCamelCase__					(     __SCREAMING_SNAKE_CASE			):

		"""simple docstring"""
		UpperCAmelCase__     			=						'segformer'




		def __init__( self						:						str							,    __A						:						Any=3							,    __A						:						Optional[Any]=4							,    __A						:						str=[2, 2, 2, 2]							,    __A						:						Optional[Any]=[8, 4, 2, 1]							,    __A						:						Optional[Any]=[3_2, 6_4, 1_6_0, 2_5_6]							,    __A						:						int=[7, 3, 3, 3]							,    __A						:						Optional[int]=[4, 2, 2, 2]							,    __A						:						Any=[1, 2, 5, 8]							,    __A						:						Dict=[4, 4, 4, 4]							,    __A						:						Any="gelu"							,    __A						:						Any=0.0							,    __A						:						List[Any]=0.0							,    __A						:						List[Any]=0.1							,    __A						:						Optional[int]=0.0_2							,    __A						:						Union[str, Any]=0.1							,    __A						:						str=1e-6							,    __A						:						Optional[int]=2_5_6							,    __A						:						Optional[int]=2_5_5							,    **__A						:						Tuple							,    ):







							"""simple docstring"""
							super().__init__(**UpperCamelCase__    )

							if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
												warnings.warn(
												    "Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be"
												    " removed, as the behaviour will default to that of reshape_last_stage = True."							,    UpperCamelCase__							,    )

							_lowercase			= num_channels
							_lowercase			= num_encoder_blocks
							_lowercase			= depths
							_lowercase			= sr_ratios
							_lowercase			= hidden_sizes
							_lowercase			= patch_sizes
							_lowercase			= strides
							_lowercase			= mlp_ratios
							_lowercase			= num_attention_heads
							_lowercase			= hidden_act
							_lowercase			= hidden_dropout_prob
							_lowercase			= attention_probs_dropout_prob
							_lowercase			= classifier_dropout_prob
							_lowercase			= initializer_range
							_lowercase			= drop_path_rate
							_lowercase			= layer_norm_eps
							_lowercase			= decoder_hidden_size
							_lowercase			= kwargs.get("reshape_last_stage"							,    UpperCamelCase__    )
							_lowercase			= semantic_loss_ignore_index







class 	UpperCamelCase__					(     __SCREAMING_SNAKE_CASE			):

		"""simple docstring"""
		UpperCAmelCase__     			=						version.parse('1.11'			)




		@property
		def       snake_case     ( self						:						Dict    ):







							"""simple docstring"""
							return OrderedDict(
							    [
							        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
							    ]    )




		@property
		def       snake_case     ( self						:						List[Any]    ):







							"""simple docstring"""
							return 1e-4




		@property
		def       snake_case     ( self						:						str    ):







							"""simple docstring"""
							return 1_2



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

from PIL import Image

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




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__			)  ->							list[list[int]]:


		'''simple docstring'''


		snake_case  :       Optional[Any]     			=						[]
		for i in range(len(SCREAMING_SNAKE_CASE__			)			):
				snake_case  :       str     			=						[]
				for j in range(len(cells[i]			)			):
						# Get the number of live neighbours
						snake_case  :       Any     			=						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  :       List[Any]     			=						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    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__			)  ->							list[Image.Image]:


		'''simple docstring'''


		snake_case  :       Tuple     			=						[]
		for _ in range(SCREAMING_SNAKE_CASE__			):
				# Create output image
				snake_case  :       List[Any]     			=						Image.new('''RGB''' ,       (len(cells[0]			), len(SCREAMING_SNAKE_CASE__			))			)
				snake_case  :       Optional[Any]     			=						img.load()

				# Save cells to image
				for x in range(len(SCREAMING_SNAKE_CASE__			)			):
						for y in range(len(cells[0]			)			):
								snake_case  :       str     			=						255 - cells[y][x] * 255
								snake_case  :       List[str]     			=						(colour, colour, colour)

        # Save image
				images.append(SCREAMING_SNAKE_CASE__			)
				snake_case  :       Dict     			=						new_generation(SCREAMING_SNAKE_CASE__			)
		return images


if __name__ == "__main__":
						lowercase__						       =      generate_images(GLIDER, 1_6)
						images[0].save("out.gif", save_all=True, append_images=images[1:])


