


'''simple docstring'''


from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream






class 	lowerCAmelCase__			(			UpperCAmelCase__	):




			def __init__(		self  :     str	,  lowerCamelCase__  :     Callable	,  lowerCamelCase__  :     Optional[Features] = None	,  lowerCamelCase__  :     str = None	,  lowerCamelCase__  :     bool = False	,  lowerCamelCase__  :     bool = False	,  lowerCamelCase__  :     Optional[dict] = None	,  lowerCamelCase__  :     Optional[int] = None	,  **lowerCamelCase__  :     Optional[Any]	,  )   ->Dict:



					'''simple docstring'''







					super().__init__(
					    features=lowerCamelCase__	,  cache_dir=lowerCamelCase__	,  keep_in_memory=lowerCamelCase__	,  streaming=lowerCamelCase__	,  num_proc=lowerCamelCase__	,  **lowerCamelCase__	,  )
					_UpperCAmelCase		:       Tuple								=      Generator(
					    cache_dir=lowerCamelCase__	,  features=lowerCamelCase__	,  generator=lowerCamelCase__	,  gen_kwargs=lowerCamelCase__	,  **lowerCamelCase__	,  )






			def 							lowerCAmelCase__    (		self  :     List[str] )   ->Any:



					'''simple docstring'''







					if self.streaming:
							_UpperCAmelCase		:       int								=      self.builder.as_streaming_dataset(split="train" )
					# Build regular (map-style) dataset
					else:
							_UpperCAmelCase		:       Dict								=      None
							_UpperCAmelCase		:       str								=      None
							_UpperCAmelCase		:       List[Any]								=      None
							_UpperCAmelCase		:       Union[str, Any]								=      None

							self.builder.download_and_prepare(
							    download_config=lowerCamelCase__	,  download_mode=lowerCamelCase__	,  verification_mode=lowerCamelCase__	,  base_path=lowerCamelCase__	,  num_proc=self.num_proc	,  )
							_UpperCAmelCase		:       List[Any]								=      self.builder.as_dataset(
							    split="train"	,  verification_mode=lowerCamelCase__	,  in_memory=self.keep_in_memory )
					return dataset







'''simple docstring'''


def  __lowerCAmelCase (__lowerCAmelCase   ):  # noqa: E741
		_UpperCAmelCase		:       List[str]								=      len(__lowerCAmelCase   )
		_UpperCAmelCase		:       str								=      0
		_UpperCAmelCase		:       List[str]								=      [0] * n
		_UpperCAmelCase		:       int								=      [False] * n
		_UpperCAmelCase		:       Dict								=      [False] * n

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

				for to in l[at]:
						if to == parent:
								pass
						elif not visited[to]:
								_UpperCAmelCase		:       List[str]								=      dfs(__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase   )
								_UpperCAmelCase		:       Tuple								=      min(low[at]      , low[to]   )

								# AP found via bridge
								if at < low[to]:
										_UpperCAmelCase		:       Dict								=      True
								# AP found via cycle
								if at == low[to]:
										_UpperCAmelCase		:       Dict								=      True
						else:
								_UpperCAmelCase		:       Optional[int]								=      min(low[at]      , __lowerCAmelCase   )
				return out_edge_count

		for i in range(__lowerCAmelCase   ):
				if not visited[i]:
						_UpperCAmelCase		:       str								=      0
						_UpperCAmelCase		:       Tuple								=      dfs(__lowerCAmelCase      , __lowerCAmelCase      , -1      , __lowerCAmelCase   )
						_UpperCAmelCase		:       Optional[int]								=      out_edge_count > 1

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


# Adjacency list of graph
lowerCamelCase__    	=     {
    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)



