code: 
  
  
  __lowerCamelCase       :       Any				   =			float("inf")
  
  
  
  class 			a      :
  
  
  
  
  
  
  		def __init__(  self	,     __UpperCamelCase							)->			Dict:
  						'''simple docstring'''
  
  
  						A__     :							Dict   				=[0] * n
  						A__     :							Optional[int]   				=[0] * n
  						A__     :							Any   				=[0] * n
  						A__     :							List[str]   				=[[] for _ in range(__UpperCamelCase							)]
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     __UpperCamelCase	,     __UpperCamelCase	,     __UpperCamelCase	,     __UpperCamelCase=0							)->			Optional[Any]:
  						'''simple docstring'''
  
  
  						self.adj[a].append([b, len(self.adj[b]							), c, 0]							)
  						self.adj[b].append([a, len(self.adj[a]							) - 1, rcap, 0]							)
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     __UpperCamelCase	,     __UpperCamelCase	,     __UpperCamelCase							)->			Union[str, Any]:
  						'''simple docstring'''
  
  
  						if vertex == sink or not flow:
  										return flow
  
  						for i in range(self.ptr[vertex]	,     len(self.adj[vertex]							)							):
  										A__     :							int   				=self.adj[vertex][i]
  										if self.lvl[e[0]] == self.lvl[vertex] + 1:
  														A__     :							Tuple   				=self.depth_first_search(e[0]	,     __UpperCamelCase	,     min(__UpperCamelCase	,     e[2] - e[3]							)							)
  														if p:
  																		self.adj[vertex][i][3] += p
  																		self.adj[e[0]][e[1]][3] -= p
  																		return p
  										A__     :							Tuple   				=self.ptr[vertex] + 1
  						return 0
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     __UpperCamelCase	,     __UpperCamelCase							)->			Any:
  						'''simple docstring'''
  
  
  						A__				,  A__     :							List[Any]   				=0, source
  						for l in range(31							):  # noqa: E741  l = 30 maybe faster for random data
  										while True:
  														A__				,  A__     :							Optional[int]   				=[0] * len(self.q							), [0] * len(self.q							)
  														A__				,  A__				,  A__     :							List[Any]   				=0, 1, 1
  														while qi < qe and not self.lvl[sink]:
  																		A__     :							Dict   				=self.q[qi]
  																		qi += 1
  																		for e in self.adj[v]:
  																						if not self.lvl[e[0]] and (e[2] - e[3]) >> (30 - l):
  																										A__     :							List[Any]   				=e[0]
  																										qe += 1
  																										A__     :							Tuple   				=self.lvl[v] + 1
  
  														A__     :							Tuple   				=self.depth_first_search(__UpperCamelCase	,     __UpperCamelCase	,     __UpperCamelCase							)
  														while p:
  																		flow += p
  																		A__     :							Any   				=self.depth_first_search(__UpperCamelCase	,     __UpperCamelCase	,     __UpperCamelCase							)
  
  														if not self.lvl[sink]:
  																		break
  
  						return flow
  __lowerCamelCase       :       str				   =			Dinic(10)
  __lowerCamelCase       :       str				   =			0
  __lowerCamelCase       :       str				   =			9
  for vertex in range(1, 5):
  						graph.add_edge(source, vertex, 1)
  for vertex in range(5, 9):
  						graph.add_edge(vertex, sink, 1)
  for vertex in range(1, 5):
  						graph.add_edge(vertex, vertex + 4, 1)
  
  # Now we can know that is the maximum flow(source -> sink)
  print(graph.max_flow(source, sink))
  
  
  
  
style_context: 
  
  
  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      (      UpperCamelCase_   ):
  		__lowercase													=		{
  		    """sld_warmup_steps""": 15,
  		    """sld_guidance_scale""": 20,
  		    """sld_threshold""": 0.0,
  		    """sld_momentum_scale""": 0.0,
  		    """sld_mom_beta""": 0.0,
  		}
  		__lowercase													=		{
  		    """sld_warmup_steps""": 10,
  		    """sld_guidance_scale""": 1_000,
  		    """sld_threshold""": 0.01,
  		    """sld_momentum_scale""": 0.3,
  		    """sld_mom_beta""": 0.4,
  		}
  		__lowercase													=		{
  		    """sld_warmup_steps""": 7,
  		    """sld_guidance_scale""": 2_000,
  		    """sld_threshold""": 0.0_25,
  		    """sld_momentum_scale""": 0.5,
  		    """sld_mom_beta""": 0.7,
  		}
  		__lowercase													=		{
  		    """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      (      UpperCamelCase_   ):
  		__lowercase													=		42
  		__lowercase													=		42
  		__lowercase													=		42
  		__lowercase													=		42
  
  
  if is_transformers_available() and is_torch_available():
  						from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
  						from .safety_checker import SafeStableDiffusionSafetyChecker
  
  
  
  