
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    lowercase	(  lowerCAmelCase__	):
			return [int(lowercase_	) for c in f"{ruleset:08}"[:8]]






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






def    lowercase	(  lowerCAmelCase__	):
			lowerCamelCase_ 		=     Image.new('''RGB'''  ,(len(cells[0]	), len(lowercase_	))	)
			lowerCamelCase_ 		=     img.load()
			# Generates image
			for w in range(img.width	):
						for h in range(img.height	):
									lowerCamelCase_ 		=     255 - int(255 * cells[h][w]	)
									lowerCamelCase_ 		=     (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 ...configuration_utils import PretrainedConfig
from ...utils import logging


A_						       =				logging.get_logger(__name__)

A_						       =				{
    """uw-madison/yoso-4096""": """https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json""",
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}




class    __lowerCamelCase     (   lowerCAmelCase ):
				a__:			Dict									=						'yoso'




				def __init__(							self       ,	UpperCAmelCase=5_0265       ,	UpperCAmelCase=768       ,	UpperCAmelCase=12       ,	UpperCAmelCase=12       ,	UpperCAmelCase=3072       ,	UpperCAmelCase="gelu"       ,	UpperCAmelCase=0.1       ,	UpperCAmelCase=0.1       ,	UpperCAmelCase=4096       ,	UpperCAmelCase=1       ,	UpperCAmelCase=0.0_2       ,	UpperCAmelCase=1e-1_2       ,	UpperCAmelCase="absolute"       ,	UpperCAmelCase=True       ,	UpperCAmelCase=9       ,	UpperCAmelCase=64       ,	UpperCAmelCase=None       ,	UpperCAmelCase=True       ,	UpperCAmelCase=True       ,	UpperCAmelCase=1       ,	UpperCAmelCase=0       ,	UpperCAmelCase=2       ,	**UpperCAmelCase       ,	):
							super().__init__(pad_token_id=UpperCAmelCase       ,	bos_token_id=UpperCAmelCase       ,	eos_token_id=UpperCAmelCase       ,	**UpperCAmelCase      )

							lowerCamelCase_ 		=     vocab_size
							lowerCamelCase_ 		=     max_position_embeddings
							lowerCamelCase_ 		=     hidden_size
							lowerCamelCase_ 		=     num_hidden_layers
							lowerCamelCase_ 		=     num_attention_heads
							lowerCamelCase_ 		=     intermediate_size
							lowerCamelCase_ 		=     hidden_act
							lowerCamelCase_ 		=     hidden_dropout_prob
							lowerCamelCase_ 		=     attention_probs_dropout_prob
							lowerCamelCase_ 		=     initializer_range
							lowerCamelCase_ 		=     type_vocab_size
							lowerCamelCase_ 		=     layer_norm_eps
							lowerCamelCase_ 		=     position_embedding_type
							lowerCamelCase_ 		=     use_expectation
							lowerCamelCase_ 		=     hash_code_len
							lowerCamelCase_ 		=     num_hash
							lowerCamelCase_ 		=     conv_window
							lowerCamelCase_ 		=     use_fast_hash
							lowerCamelCase_ 		=     lsh_backward



