

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A_						:     Union[str, Any]			  =				{'configuration_bit': ['BIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BitConfig', 'BitOnnxConfig']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       A_						:     Any			  =				[
           'BIT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'BitForImageClassification',
           'BitModel',
           'BitPreTrainedModel',
           'BitBackbone',
       ]


try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       A_						:     Optional[Any]			  =				['BitImageProcessor']


if TYPE_CHECKING:
       from .configuration_bit import BIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BitConfig, BitOnnxConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_bit import (
                  BIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  BitBackbone,
                  BitForImageClassification,
                  BitModel,
                  BitPreTrainedModel,
              )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_bit import BitImageProcessor

else:
       import sys

       A_						:     List[str]			  =				_LazyModule(__name__, globals()['__file__'], _import_structure)







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    A_				( _a  ):


    '''simple docstring'''






    a__       							=    {
        "sld_warmup_steps": 15,
        "sld_guidance_scale": 20,
        "sld_threshold": 0.0,
        "sld_momentum_scale": 0.0,
        "sld_mom_beta": 0.0,
    }
    a__       							=    {
        "sld_warmup_steps": 10,
        "sld_guidance_scale": 10_00,
        "sld_threshold": 0.01,
        "sld_momentum_scale": 0.3,
        "sld_mom_beta": 0.4,
    }
    a__       							=    {
        "sld_warmup_steps": 7,
        "sld_guidance_scale": 20_00,
        "sld_threshold": 0.0_25,
        "sld_momentum_scale": 0.5,
        "sld_mom_beta": 0.7,
    }
    a__       							=    {
        "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    A_				( _a  ):


    '''simple docstring'''






    a__       							=    42
    a__       							=    42
    a__       							=    42
    a__       							=    42


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




