'''simple docstring'''




# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.






def 							lowerCamelCase			(   UpperCAmelCase__ :      str				)    ->   str:
							lowercase_      :    Optional[int]       		= [False] * len(UpperCAmelCase__				)
							lowercase_      :    List[str]       		= [-1] * len(UpperCAmelCase__				)

							def dfs(UpperCAmelCase__ :      Optional[int]   ,   UpperCAmelCase__ :      Any				):
														lowercase_      :    str       		= True
														lowercase_      :    Optional[Any]       		= c
														for u in graph[v]:
																					if not visited[u]:
																												dfs(UpperCAmelCase__   ,   1 - c				)

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

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

							return True


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

print(check_bipartite_dfs(graph))






'''simple docstring'''




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

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate





@dataclass(frozen=_UpperCAmelCase)
class 					__magic_name__		(					_UpperCAmelCase):
			UpperCamelCase__       = field(default='''image-classification''',  metadata={'''include_in_asdict_even_if_is_default''': True})
			UpperCamelCase__       = Features({'''image''': Image()})
			UpperCamelCase__       = Features({'''labels''': ClassLabel})
			UpperCamelCase__       = "image"
			UpperCamelCase__       = "labels"







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple       ,    lowercase_       :						str					):
										if self.label_column not in features:
																	raise ValueError(f'''Column {self.label_column} is not present in features.'''					)
										if not isinstance(features[self.label_column]       ,    lowercase_					):
																	raise ValueError(f'''Column {self.label_column} is not a ClassLabel.'''					)
										lowercase_      :    List[str]       		= copy.deepcopy(self					)
										lowercase_      :    List[str]       		= self.label_schema.copy()
										lowercase_      :    List[Any]       		= features[self.label_column]
										lowercase_      :    Optional[Any]       		= label_schema
										return task_template







			@property
			def 			SCREAMING_SNAKE_CASE_  (			self       :						int					):
										return {
										    self.image_column: "image",
										    self.label_column: "labels",
										}





