






"""simple docstring"""




def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase      )			->     Optional[Any]:
     UpperCamelCase__      :       int	    =  [False] * len(__lowerCAmelCase      )
     UpperCamelCase__      :       Optional[Any]	    =  [-1] * len(__lowerCAmelCase      )

     def dfs(__lowerCAmelCase ,   __lowerCAmelCase      ):
          UpperCamelCase__      :       str	    =  True
          UpperCamelCase__      :       Tuple	    =  c
          for u in graph[v]:
               if not visited[u]:
                    dfs(__lowerCAmelCase ,   1 - c      )

     for i in range(len(__lowerCAmelCase      )      ):
          if not visited[i]:
               dfs(__lowerCAmelCase ,   0      )

     for i in range(len(__lowerCAmelCase      )      ):
          for j in graph[i]:
               if color[i] == color[j]:
                    return False

     return True


# Adjacency list of graph
lowerCamelCase     :							Any    ={0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}




print(check_bipartite_dfs(graph))







from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate





@dataclass(frozen=A__	)
class       __a  (   A__	):
 _lowerCAmelCase	:	str				=			field(default='''language-modeling'''	,       metadata={'''include_in_asdict_even_if_is_default''': True}	)

 _lowerCAmelCase	:	ClassVar[Features]				=			Features({'''text''': Value('''string'''	)}	)
 _lowerCAmelCase	:	ClassVar[Features]				=			Features({}	)
 _lowerCAmelCase	:	str				=			"text"







 @property
 def  __lowercase (		self :       str						):


      '''simple docstring'''






      return {self.text_column: "text"}