code: 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_						(						UpperCamelCase_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      List[Any]     =       {
  	    """sld_warmup_steps""": 15,
  	    """sld_guidance_scale""": 20,
  	    """sld_threshold""": 0.0,
  	    """sld_momentum_scale""": 0.0,
  	    """sld_mom_beta""": 0.0,
  	}
  	UpperCAmelCase_						:      List[Any]     =       {
  	    """sld_warmup_steps""": 10,
  	    """sld_guidance_scale""": 1000,
  	    """sld_threshold""": 0.01,
  	    """sld_momentum_scale""": 0.3,
  	    """sld_mom_beta""": 0.4,
  	}
  	UpperCAmelCase_						:      Optional[Any]     =       {
  	    """sld_warmup_steps""": 7,
  	    """sld_guidance_scale""": 2000,
  	    """sld_threshold""": 0.025,
  	    """sld_momentum_scale""": 0.5,
  	    """sld_mom_beta""": 0.7,
  	}
  	UpperCAmelCase_						:      str     =       {
  	    """sld_warmup_steps""": 0,
  	    """sld_guidance_scale""": 5000,
  	    """sld_threshold""": 1.0,
  	    """sld_momentum_scale""": 0.5,
  	    """sld_mom_beta""": 0.7,
  	}
  
  
  
  
  @dataclass
  class      lowercase_						(						UpperCamelCase_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      Union[List[PIL.Image.Image], np.ndarray]
  	UpperCAmelCase_						:      Optional[List[bool]]
  	UpperCAmelCase_						:      Optional[Union[List[PIL.Image.Image], np.ndarray]]
  	UpperCAmelCase_						:      Optional[str]
  
  
  if is_transformers_available() and is_torch_available():
  	from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
  	from .safety_checker import SafeStableDiffusionSafetyChecker
  
  
  
  
style_context: from dataclasses import dataclass
  from typing import List, Optional, Union
  
  import numpy as np
  import PIL
  
  from ...utils import BaseOutput, is_invisible_watermark_available, is_torch_available, is_transformers_available
  
  
  
  
  @dataclass
  class      lowercase_						(						UpperCamelCase_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      Union[List[PIL.Image.Image], np.ndarray]
  
  
  if is_transformers_available() and is_torch_available() and is_invisible_watermark_available():
  	from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
  	from .pipeline_stable_diffusion_xl_imgaimg import StableDiffusionXLImgaImgPipeline
  
  
  
  