
import sys



def 	_a  (					__SCREAMING_SNAKE_CASE					:  Optional[int]		,				__SCREAMING_SNAKE_CASE					:  Dict    ):






  """simple docstring"""




  if not numbers:
    return 0
  if target == 0 and target in numbers:
    return 0
  if not isinstance(__SCREAMING_SNAKE_CASE		,				(list, tuple)    ) or not all(
      isinstance(__SCREAMING_SNAKE_CASE		,				__SCREAMING_SNAKE_CASE    ) for number in numbers    ):
    raise ValueError('numbers must be an iterable of integers'    )

  _lowerCAmelCase						=		_lowerCAmelCase						=		_lowerCAmelCase						=		0
  _lowerCAmelCase						=		sys.maxsize

  while right < len(__SCREAMING_SNAKE_CASE    ):
    curr_sum += numbers[right]
    while curr_sum >= target and left <= right:
      _lowerCAmelCase						=		min(__SCREAMING_SNAKE_CASE		,				right - left + 1    )
      curr_sum -= numbers[left]
      left += 1
    right += 1

  return 0 if min_len == sys.maxsize else min_len




'''simple docstring'''

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"""



				__UpperCamelCase     :		Tuple						=						{
				    'sld_warmup_steps': 15,
				    'sld_guidance_scale': 20,
				    'sld_threshold': 0.0,
				    'sld_momentum_scale': 0.0,
				    'sld_mom_beta': 0.0,
				}
				__UpperCamelCase     :		Optional[Any]						=						{
				    'sld_warmup_steps': 10,
				    'sld_guidance_scale': 1_000,
				    'sld_threshold': 0.01,
				    'sld_momentum_scale': 0.3,
				    'sld_mom_beta': 0.4,
				}
				__UpperCamelCase     :		Tuple						=						{
				    'sld_warmup_steps': 7,
				    'sld_guidance_scale': 2_000,
				    'sld_threshold': 0.025,
				    'sld_momentum_scale': 0.5,
				    'sld_mom_beta': 0.7,
				}
				__UpperCamelCase     :		str						=						{
				    'sld_warmup_steps': 0,
				    'sld_guidance_scale': 5_000,
				    'sld_threshold': 1.0,
				    'sld_momentum_scale': 0.5,
				    'sld_mom_beta': 0.7,
				}


@dataclass
class    a__					(			__A   ):







				"""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

