
def        lowerCamelCase_  (   __UpperCamelCase ,						__UpperCamelCase     ):
				return (input_a, input_a).count(0     ) % 2



def        lowerCamelCase_  (   ):
				assert xor_gate(0 ,						0     ) == 0
				assert xor_gate(0 ,						1     ) == 1
				assert xor_gate(1 ,						0     ) == 1
				assert xor_gate(1 ,						1     ) == 0


if __name__ == "__main__":
						print(xor_gate(0, 0))
						print(xor_gate(0, 1))

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