






"""simple docstring"""





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


UpperCamelCase_						:					Any      				=			logging.get_logger(__name__)

UpperCamelCase_						:					str      				=			{
    """google/reformer-crime-and-punishment""": (
        """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json"""
    ),
    """google/reformer-enwik8""": """https://huggingface.co/google/reformer-enwik8/resolve/main/config.json""",
}


class   _lowercase			(  lowerCAmelCase    ):
      _a :  List[Any]										= '''reformer'''
      _a :  Optional[int]										= ['''past_buckets_states''']
      _a :  int										= {}


      def __init__(     self					:						List[str]				, a					:						List[str]=6_4				, a					:						str=["local", "lsh", "local", "lsh", "local", "lsh"]				, a					:						Union[str, Any]=1.0				, a					:						List[str]=True				, a					:						List[str]=[6_4, 6_4]				, a					:						Tuple=[6_4, 1_9_2]				, a					:						str=0				, a					:						Any=2				, a					:						Dict=5_1_2				, a					:						List[Any]=None				, a					:						Union[str, Any]="relu"				, a					:						Optional[Any]=0.0_5				, a					:						Optional[int]=2_5_6				, a					:						int=0.0_2				, a					:						Tuple=False				, a					:						Any=1e-12				, a					:						Any=1				, a					:						List[str]=0				, a					:						str=0.0_5				, a					:						Dict=6_4				, a					:						str=6_4				, a					:						Union[str, Any]=0.0				, a					:						Any=1				, a					:						Any=0				, a					:						Tuple=4_0_9_6				, a					:						List[str]=1_2				, a					:						Union[str, Any]=None				, a					:						int=1				, a					:						Any=0				, a					:						Any=3_2_0				, a					:						Tuple=False				, a					:						List[Any]=True				, a					:						int=None				, **a					:						Dict				, ):





            """simple docstring"""







            __snake_case   :     List[Any]	      =hash_seed
            __snake_case   :     Dict	      =vocab_size
            __snake_case   :     Optional[int]	      =attention_head_size
            __snake_case   :     List[Any]	      =hidden_size
            __snake_case   :     Any	      =num_attention_heads
            __snake_case   :     Optional[Any]	      =num_hashes
            __snake_case   :     Union[str, Any]	      =len(a    )
            __snake_case   :     List[Any]	      =tuple(a    ) if isinstance(a				, a    ) else num_buckets
            __snake_case   :     Any	      =lsh_attn_chunk_length
            __snake_case   :     Any	      =local_attn_chunk_length
            __snake_case   :     List[str]	      =lsh_num_chunks_after
            __snake_case   :     Tuple	      =lsh_num_chunks_before
            __snake_case   :     Optional[int]	      =local_num_chunks_after
            __snake_case   :     Tuple	      =local_num_chunks_before
            __snake_case   :     Dict	      =hidden_act
            __snake_case   :     Optional[Any]	      =feed_forward_size
            __snake_case   :     Union[str, Any]	      =hidden_dropout_prob
            __snake_case   :     Optional[Any]	      =lsh_attention_probs_dropout_prob
            __snake_case   :     List[Any]	      =local_attention_probs_dropout_prob
            __snake_case   :     Optional[int]	      =max_position_embeddings
            __snake_case   :     Optional[Any]	      =initializer_range
            __snake_case   :     str	      =layer_norm_eps
            __snake_case   :     str	      =axial_pos_embds
            __snake_case   :     str	      =tuple(a    )
            __snake_case   :     Any	      =tuple(a    )
            __snake_case   :     int	      =axial_norm_std
            __snake_case   :     str	      =chunk_size_lm_head
            __snake_case   :     List[Any]	      =attn_layers
            __snake_case   :     Dict	      =use_cache
            __snake_case   :     Optional[Any]	      =classifier_dropout
            super().__init__(
                pad_token_id=a				, eos_token_id=a				, is_decoder=a				, tie_word_embeddings=a				, **a				, )










"""simple docstring"""





from __future__ import annotations

from PIL import Image

# Define the first generation of cells
# fmt: off
UpperCamelCase_						:					int      				=			[[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       (     a			:					int			)       ->       list[int]:
      return [int(a			) for c in f'''{ruleset:08}'''[:8]]



def      __lowercase       (     a			:					list[list[int]]							,		a			:					list[int]							,		a			:					int			)       ->       list[int]:
      __snake_case   :     Optional[Any]	      =len(cells[0]			)  # 31
      __snake_case   :     List[str]	      =[]
      for i in range(a			):
            # Get the neighbors of each cell
            # Handle neighbours outside bounds by using 0 as their value
            __snake_case   :     Optional[Any]	      =0 if i == 0 else cells[time][i - 1]
            __snake_case   :     Dict	      =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      __lowercase       (     a			:					list[list[int]]			)       ->       Image.Image:
      __snake_case   :     int	      =Image.new('''RGB'''							,		(len(cells[0]			), len(a			))			)
      __snake_case   :     List[Any]	      =img.load()
      # Generates image
      for w in range(img.width			):
            for h in range(img.height			):
                  __snake_case   :     int	      =255 - int(255 * cells[h][w]			)
                  __snake_case   :     List[str]	      =(color, color, color)
      return img


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


