



'''simple docstring'''

def 	__lowerCamelCase	( lowerCAmelCase_    )     -> Optional[Any]:
		_a	: Dict								=				[0] * len(lowerCAmelCase_    )
		_a	: List[str]								=				[]
		_a	: Optional[int]								=				[]
		_a	: Tuple								=				0

		for values in graph.values():
				for i in values:
						indegree[i] += 1

		for i in range(len(lowerCAmelCase_    )    ):
				if indegree[i] == 0:
						queue.append(lowerCAmelCase_    )

		while queue:
				_a	: int								=				queue.pop(0    )
				cnt += 1
				topo.append(lowerCAmelCase_    )
				for x in graph[vertex]:
						indegree[x] -= 1
						if indegree[x] == 0:
								queue.append(lowerCAmelCase_    )

		if cnt != len(lowerCAmelCase_    ):
				print('Cycle exists'    )
		else:
				print(lowerCAmelCase_    )


# Adjacency List of Graph
__lowerCAmelCase		     =  {0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}
topological_sort(graph)









'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


__lowerCAmelCase		     =  logging.get_logger(__name__)

class       __magic_name__		(       _UpperCamelCase  ):







							def __init__(				self   :			Optional[int]      ,*_UpperCAmelCase   :			List[Any]      ,**_UpperCAmelCase   :			Union[str, Any]						):
									warnings.warn(
									    'The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
									    ' use GLPNImageProcessor instead.'      ,_UpperCAmelCase      ,)
									super().__init__(*_UpperCAmelCase      ,**_UpperCAmelCase						)




