



def snake_case__	(      __SCREAMING_SNAKE_CASE			)		->				Optional[Any]:
		return [
		    {
		        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],
		    },
		    {
		        0: [6],
		        1: [9],
		        2: [4, 5],
		        3: [4],
		        4: [2, 3],
		        5: [2],
		        6: [0, 7],
		        7: [6],
		        8: [],
		        9: [1],
		    },
		    {
		        0: [4],
		        1: [6],
		        2: [],
		        3: [5, 6, 7],
		        4: [0, 6],
		        5: [3, 8, 9],
		        6: [1, 3, 4, 7],
		        7: [3, 6, 8, 9],
		        8: [5, 7],
		        9: [5, 7],
		    },
		    {
		        0: [1, 3],
		        1: [0, 2, 4],
		        2: [1, 3, 4],
		        3: [0, 2, 4],
		        4: [1, 2, 3],
		    },
		][index]







def snake_case__	(      __SCREAMING_SNAKE_CASE			)		->				list[tuple[int, int]]:
		UpperCAmelCase_						       =					0
		UpperCAmelCase_						       =					len(__lowercase			)  # No of vertices in graph
		UpperCAmelCase_						       =					[0] * n
		UpperCAmelCase_						       =					[False] * n

		def dfs(__SCREAMING_SNAKE_CASE      ,  __SCREAMING_SNAKE_CASE      ,  __SCREAMING_SNAKE_CASE      ,  __SCREAMING_SNAKE_CASE			):
				UpperCAmelCase_						       =					True
				UpperCAmelCase_						       =					id_
				id_ += 1
				for to in graph[at]:
						if to == parent:
								pass
						elif not visited[to]:
								dfs(__lowercase      ,  __lowercase      ,  __lowercase      ,  id_			)
								UpperCAmelCase_						       =					min(low[at]      ,  low[to]			)
								if id_ <= low[to]:
										bridges.append((at, to) if at < to else (to, at)			)
						else:
								# This edge is a back edge and cannot be a bridge
								UpperCAmelCase_						       =					min(low[at]      ,  low[to]			)

		UpperCAmelCase_						       =					[]
		for i in range(__lowercase			):
				if not visited[i]:
						dfs(__lowercase      ,  -1      ,  __lowercase      ,  id_			)
		return bridges


if __name__ == "__main__":
			import doctest

			doctest.testmod()









from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType






class 						UpperCAmelCase__ (							__snake_case							):
		__snake_case      :       Optional[Any]     =   ["image_processor", "tokenizer"]
		__snake_case      :       Tuple     =   "BridgeTowerImageProcessor"
		__snake_case      :       List[str]     =   ("RobertaTokenizer", "RobertaTokenizerFast")







		def __init__(					self       ,A__       ,A__		):
						super().__init__(A__       ,A__		)







		def __call__(					self       ,A__       ,A__ = None       ,A__ = True       ,A__ = False       ,A__ = None       ,A__ = None       ,A__ = 0       ,A__ = None       ,A__ = None       ,A__ = None       ,A__ = False       ,A__ = False       ,A__ = False       ,A__ = False       ,A__ = True       ,A__ = None       ,**A__       ,):
						_A	:				List[Any]   =      self.tokenizer(
						    text=A__       ,add_special_tokens=A__       ,padding=A__       ,truncation=A__       ,max_length=A__       ,stride=A__       ,pad_to_multiple_of=A__       ,return_token_type_ids=A__       ,return_attention_mask=A__       ,return_overflowing_tokens=A__       ,return_special_tokens_mask=A__       ,return_offsets_mapping=A__       ,return_length=A__       ,verbose=A__       ,return_tensors=A__       ,**A__       ,)
						# add pixel_values + pixel_mask
						_A	:				Optional[Any]   =      self.image_processor(
						    A__       ,return_tensors=A__       ,do_normalize=A__       ,do_center_crop=A__       ,**A__		)
						encoding.update(A__		)

						return encoding







		def  A__      (					self       ,*A__       ,**A__		):
						return self.tokenizer.batch_decode(*A__       ,**A__		)







		def  A__      (					self       ,*A__       ,**A__		):
						return self.tokenizer.decode(*A__       ,**A__		)







		@property
		def  A__      (					self		):
						_A	:				Union[str, Any]   =      self.tokenizer.model_input_names
						_A	:				str   =      self.image_processor.model_input_names
						return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names		)		)



