
from abc import ABC, abstractmethod
from typing import Optional, Union

from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike




class 			UpperCAmelCase_     (					_a	):


  '''simple docstring'''







  def __init__(					self     :					Optional[Any]     ,				UpperCamelCase__     :					str = None     ,				UpperCamelCase__     :					Dict = None     ,				UpperCamelCase__     :					Tuple = None     ,				UpperCamelCase__     :					Dict = None     ,				UpperCamelCase__     :					str = False     ,				UpperCamelCase__     :					Union[str, Any] = False     ,				UpperCamelCase__     :					Dict = None     ,				**UpperCamelCase__     :					Optional[int]     ,				)     ->      str:







    """simple docstring"""






    __magic_name__								=			path_or_paths
    __magic_name__								=			split if split or isinstance(lowerCamelCase__     ,				lowerCamelCase__       ) else "train"
    __magic_name__								=			features
    __magic_name__								=			cache_dir
    __magic_name__								=			keep_in_memory
    __magic_name__								=			streaming
    __magic_name__								=			num_proc
    __magic_name__								=			kwargs





  @abstractmethod
  def 				_lowercase				(					self     :					Union[str, Any]       )     ->      List[str]:







    """simple docstring"""






    pass







class 			UpperCAmelCase_     (					_a	):


  '''simple docstring'''







  def __init__(					self     :					List[Any]     ,				UpperCamelCase__     :					Union[str, Any] = None     ,				UpperCamelCase__     :					Tuple = None     ,				UpperCamelCase__     :					int = False     ,				UpperCamelCase__     :					List[Any] = False     ,				UpperCamelCase__     :					Union[str, Any] = None     ,				**UpperCamelCase__     :					int     ,				)     ->      List[Any]:







    """simple docstring"""






    __magic_name__								=			features
    __magic_name__								=			cache_dir
    __magic_name__								=			keep_in_memory
    __magic_name__								=			streaming
    __magic_name__								=			num_proc
    __magic_name__								=			kwargs





  @abstractmethod
  def 				_lowercase				(					self     :					List[str]       )     ->      Optional[Any]:







    """simple docstring"""






    pass




def 			_A	(      SCREAMING_SNAKE_CASE      ):  # noqa: E741
	UpperCAmelCase__:	int									= len(SCREAMING_SNAKE_CASE      )
	UpperCAmelCase__:	Dict									= 0
	UpperCAmelCase__:	Optional[int]									= [0] * n
	UpperCAmelCase__:	List[str]									= [False] * n
	UpperCAmelCase__:	List[str]									= [False] * n

	def dfs(SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      ):
		if parent == root:
			out_edge_count += 1
		UpperCAmelCase__:	List[str]									= True
		UpperCAmelCase__:	List[Any]									= at

		for to in l[at]:
			if to == parent:
				pass
			elif not visited[to]:
				UpperCAmelCase__:	str									= dfs(SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE      )
				UpperCAmelCase__:	Optional[Any]									= min(low[at]	,low[to]      )

				# AP found via bridge
				if at < low[to]:
					UpperCAmelCase__:	List[Any]									= True
				# AP found via cycle
				if at == low[to]:
					UpperCAmelCase__:	str									= True
			else:
				UpperCAmelCase__:	Union[str, Any]									= min(low[at]	,SCREAMING_SNAKE_CASE      )
		return out_edge_count

	for i in range(SCREAMING_SNAKE_CASE      ):
		if not visited[i]:
			UpperCAmelCase__:	Optional[Any]									= 0
			UpperCAmelCase__:	Union[str, Any]									= dfs(SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,-1	,SCREAMING_SNAKE_CASE      )
			UpperCAmelCase__:	Tuple									= out_edge_count > 1

	for x in range(len(SCREAMING_SNAKE_CASE      )      ):
		if is_art[x] is True:
			print(SCREAMING_SNAKE_CASE      )


# Adjacency list of graph
_lowerCAmelCase  :      Any			 ={
    0: [1, 2],
    1: [0, 2],
    2: [0, 1, 3, 5],
    3: [2, 4],
    4: [3],
    5: [2, 6, 8],
    6: [5, 7],
    7: [6, 8],
    8: [5, 7],
}
compute_ap(data)