
from itertools import permutations



def        lowerCamelCase_  (   __UpperCamelCase = 5     ):




				if gon_side < 3 or gon_side > 5:
								raise ValueError('''gon_side must be in the range [3, 5]'''     )

				# Since it's 16, we know 10 is on the outer ring
				# Put the big numbers at the end so that they are never the first number
				A_       	=  list(range(gon_side + 1 ,						0 ,						-1     )     )
				A_       	=  list(range(gon_side + 2 ,						gon_side * 2 + 1     )     )

				for perm in permutations(small_numbers + big_numbers     ):
								A_       	=  generate_gon_ring(lowerCamelCase__ ,						list(lowerCamelCase__     )     )
								if is_magic_gon(lowerCamelCase__     ):
												return int(''''''.join(str(lowerCamelCase__     ) for n in numbers     )     )

				A_       	=  F"Magic {gon_side}-gon ring is impossible"
				raise ValueError(lowerCamelCase__     )



def        lowerCamelCase_  (   __UpperCamelCase ,						__UpperCamelCase     ):
				A_       	=  [0] * (gon_side * 3)
				A_       	=  perm[0:3]
				perm.append(perm[1]     )

				A_       	=  1 if gon_side < 5 else 2

				for i in range(1 ,						len(lowerCamelCase__     ) // 3 + magic_number     ):
								A_       	=  perm[2 * i + 1]
								A_       	=  result[3 * i - 1]
								A_       	=  perm[2 * i + 2]

				return result



def        lowerCamelCase_  (   __UpperCamelCase     ):




				if len(lowerCamelCase__     ) % 3 != 0:
								raise ValueError('''a gon ring should have a length that is a multiple of 3'''     )

				if min(numbers[::3]     ) != numbers[0]:
								return False

				A_       	=  sum(numbers[:3]     )

				return all(sum(numbers[i : i + 3]     ) == total for i in range(3 ,						len(lowerCamelCase__     ) ,						3     )     )


if __name__ == "__main__":
						print(solution())


from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available






@dataclass
class 					__lowercase		(					A       ):
					__magic_name__						:							int     	=	{
					    '''sld_warmup_steps''': 15,
					    '''sld_guidance_scale''': 20,
					    '''sld_threshold''': 0.0,
					    '''sld_momentum_scale''': 0.0,
					    '''sld_mom_beta''': 0.0,
					}
					__magic_name__						:							Optional[int]     	=	{
					    '''sld_warmup_steps''': 10,
					    '''sld_guidance_scale''': 10_00,
					    '''sld_threshold''': 0.01,
					    '''sld_momentum_scale''': 0.3,
					    '''sld_mom_beta''': 0.4,
					}
					__magic_name__						:							str     	=	{
					    '''sld_warmup_steps''': 7,
					    '''sld_guidance_scale''': 20_00,
					    '''sld_threshold''': 0.0_25,
					    '''sld_momentum_scale''': 0.5,
					    '''sld_mom_beta''': 0.7,
					}
					__magic_name__						:							List[Any]     	=	{
					    '''sld_warmup_steps''': 0,
					    '''sld_guidance_scale''': 50_00,
					    '''sld_threshold''': 1.0,
					    '''sld_momentum_scale''': 0.5,
					    '''sld_mom_beta''': 0.7,
					}






@dataclass
class 					__lowercase		(					A       ):
					__magic_name__						:							Union[List[PIL.Image.Image], np.ndarray]
					__magic_name__						:							Optional[List[bool]]
					__magic_name__						:							Optional[Union[List[PIL.Image.Image], np.ndarray]]
					__magic_name__						:							Optional[str]


if is_transformers_available() and is_torch_available():
						from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
						from .safety_checker import SafeStableDiffusionSafetyChecker