


from __future__ import annotations

from collections.abc import Iterator
from typing import Any


class 		_SCREAMING_SNAKE_CASE    :


     def __init__(     self       ,				A_						):
       _UpperCAmelCase		:       Any       =    data
       _UpperCAmelCase		:       Node | None       =    None




     def __str__(     self						):
       return F'''{self.data}'''


class 		_SCREAMING_SNAKE_CASE    :


     def __init__(     self						):
       _UpperCAmelCase		:       Node | None       =    None
       _UpperCAmelCase		:       Node | None       =    None


     def __iter__(     self						):
       _UpperCAmelCase		:       Optional[int]       =    self.front
       while node:
         yield node.data
         _UpperCAmelCase		:       List[str]       =    node.next


     def __len__(     self						):
       return len(tuple(iter(self						)						)						)


     def __str__(     self						):
       return " <- ".join(str(A_						) for item in self						)


     def 					__snake_case(     self						):
       return len(self						) == 0


     def 					__snake_case(     self       ,				A_						):
       _UpperCAmelCase		:       Optional[int]       =    Node(A_						)
       if self.is_empty():
         _UpperCAmelCase		:       Tuple       =    node
       else:
         assert isinstance(self.rear       ,				A_						)
         _UpperCAmelCase		:       Any       =    node
         _UpperCAmelCase		:       Tuple       =    node


     def 					__snake_case(     self						):
       if self.is_empty():
         raise IndexError("""dequeue from empty queue"""						)
       assert isinstance(self.front       ,				A_						)
       _UpperCAmelCase		:       Optional[Any]       =    self.front
       _UpperCAmelCase		:       Union[str, Any]       =    self.front.next
       if self.front is None:
         _UpperCAmelCase		:       int       =    None
       return node.data




     def 					__snake_case(     self						):
       _UpperCAmelCase		:       int       =    None


if __name__ == "__main__":
 from doctest import testmod

 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





