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_):
  							snake_case_        =		{
  							    """sld_warmup_steps""": 15,
  							    """sld_guidance_scale""": 20,
  							    """sld_threshold""": 0.0,
  							    """sld_momentum_scale""": 0.0,
  							    """sld_mom_beta""": 0.0,
  							}
  							snake_case_        =		{
  							    """sld_warmup_steps""": 10,
  							    """sld_guidance_scale""": 10_00,
  							    """sld_threshold""": 0.01,
  							    """sld_momentum_scale""": 0.3,
  							    """sld_mom_beta""": 0.4,
  							}
  							snake_case_        =		{
  							    """sld_warmup_steps""": 7,
  							    """sld_guidance_scale""": 20_00,
  							    """sld_threshold""": 0.025,
  							    """sld_momentum_scale""": 0.5,
  							    """sld_mom_beta""": 0.7,
  							}
  							snake_case_        =		{
  							    """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_				( UpperCamelCase_):
  							snake_case_        =		42
  							snake_case_        =		42
  							snake_case_        =		42
  							snake_case_        =		42
  
  
  if is_transformers_available() and is_torch_available():
  	from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
  	from .safety_checker import SafeStableDiffusionSafetyChecker
style_context: 
  
  
  import abc
  import copy
  import dataclasses
  from dataclasses import dataclass
  from typing import ClassVar, Dict, Type, TypeVar
  
  from ..features import Features
  
  
  A_    :					Tuple             =TypeVar("""T""", bound="""TaskTemplate""")
  
  
  
  
  
  @dataclass(frozen=UpperCamelCase__)
  class        lowercase_				( abc.ABC):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  
  
  							snake_case_        =		42
  							snake_case_        =		42
  							snake_case_        =		42
  
  
  							def 						lowercase__     (   self			,    _UpperCAmelCase		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													return copy.deepcopy(self		)
  
  
  							@property
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													return Features(**self.input_schema			,    **self.label_schema		)
  
  
  							@property
  							@abc.abstractmethod
  							def 						lowercase__     (   self		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													raise NotImplementedError
  
  
  
  
  
  
  							@classmethod
  							def 						lowercase__     (   cls			,    _UpperCAmelCase		):
  
  
  
  
  
  
  
  													"""simple docstring"""
  
  
  													a_					=		{f.name for f in dataclasses.fields(cls		)}
  													return cls(**{k: v for k, v in template_dict.items() if k in field_names}		)