


from __future__ import annotations




def       a__						(		snake_case__				:       int    ):
  assert (
      isinstance(snake_case__	,      snake_case__    ) and mask > 0
  ), f'''mask needs to be positive integer, your input {mask}'''
  _UpperCAmelCase		:       Dict       =    []
  _UpperCAmelCase		:       Union[str, Any]       =    mask

  while submask:
    all_submasks.append(snake_case__    )
    _UpperCAmelCase		:       int       =    (submask - 1) & mask

  return all_submasks


if __name__ == "__main__":
 import doctest

 doctest.testmod()









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 		_SCREAMING_SNAKE_CASE    (	A    ):
     __SCREAMING_SNAKE_CASE    				=						{
         '''sld_warmup_steps''': 1_5,
         '''sld_guidance_scale''': 2_0,
         '''sld_threshold''': 0.0,
         '''sld_momentum_scale''': 0.0,
         '''sld_mom_beta''': 0.0,
     }
     __SCREAMING_SNAKE_CASE    				=						{
         '''sld_warmup_steps''': 1_0,
         '''sld_guidance_scale''': 1_0_0_0,
         '''sld_threshold''': 0.01,
         '''sld_momentum_scale''': 0.3,
         '''sld_mom_beta''': 0.4,
     }
     __SCREAMING_SNAKE_CASE    				=						{
         '''sld_warmup_steps''': 7,
         '''sld_guidance_scale''': 2_0_0_0,
         '''sld_threshold''': 0.025,
         '''sld_momentum_scale''': 0.5,
         '''sld_mom_beta''': 0.7,
     }
     __SCREAMING_SNAKE_CASE    				=						{
         '''sld_warmup_steps''': 0,
         '''sld_guidance_scale''': 5_0_0_0,
         '''sld_threshold''': 1.0,
         '''sld_momentum_scale''': 0.5,
         '''sld_mom_beta''': 0.7,
     }


@dataclass
class 		_SCREAMING_SNAKE_CASE    (	A    ):
     __SCREAMING_SNAKE_CASE    				=						42
     __SCREAMING_SNAKE_CASE    				=						42
     __SCREAMING_SNAKE_CASE    				=						42
     __SCREAMING_SNAKE_CASE    				=						42


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





