
"""simple docstring"""





import json
import os
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_a								=						logging.get_logger(__name__)

_a								=						{"""vocab_file""": """vocab.json"""}

_a								=						{
    """vocab_file""": {
        """mgp-str""": """https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json""",
    }
}

_a								=						{"""mgp-str""": 27}






class        _UpperCAmelCase(       lowerCamelCase      ):
		lowercase__         = VOCAB_FILES_NAMES
		lowercase__         = PRETRAINED_VOCAB_FILES_MAP
		lowercase__         = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



		def __init__(   self							,						__a							,						__a="[GO]"							,						__a="[GO]"							,						__a="[s]"							,						__a="[GO]"							,						**__a)			->			Dict:






							'''simple docstring'''
							super().__init__(
							    unk_token=__a							,						bos_token=__a							,						eos_token=__a							,						pad_token=__a							,						**__a							,						)

							with open(__a							,						encoding='''utf-8''') as vocab_handle:
												_UpperCamelCase									=    json.load(__a)
							_UpperCamelCase									=    {v: k for k, v in self.vocab.items()}



		@property
		def 		UpperCAmelCase				(   self)			->			Dict:






							'''simple docstring'''
							return len(self.vocab)



		def 		UpperCAmelCase				(   self)			->			Optional[int]:






							'''simple docstring'''
							return dict(self.vocab							,						**self.added_tokens_encoder)



		def 		UpperCAmelCase				(   self							,						__a)			->			List[str]:






							'''simple docstring'''
							_UpperCamelCase									=    []
							for s in text:
												char_tokens.extend(__a)
							return char_tokens



		def 		UpperCAmelCase				(   self							,						__a)			->			Optional[Any]:






							'''simple docstring'''
							return self.vocab.get(__a							,						self.vocab.get(self.unk_token))



		def 		UpperCAmelCase				(   self							,						__a)			->			Union[str, Any]:






							'''simple docstring'''
							return self.decoder.get(__a)




		def 		UpperCAmelCase				(   self							,						__a							,						__a = None)			->			Tuple[str]:






							'''simple docstring'''
							if not os.path.isdir(__a):
												logger.error('''Vocabulary path ({}) should be a directory'''.format(__a))
												return
							_UpperCamelCase									=    os.path.join(
							    __a							,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])

							with open(__a							,						'''w'''							,						encoding='''utf-8''') as f:
												f.write(json.dumps(self.vocab							,						indent=2							,						sort_keys=__a							,						ensure_ascii=__a) + '''\n''')

							return (vocab_file,)








"""simple docstring"""





import heapq



def  lowerCamelCase__						(     __snake_case      )				->						set[int]:


					"""simple docstring"""





					_UpperCamelCase									=    []

					# for each node and his adjacency list add them and the rank of the node to queue
					# using heapq module the queue will be filled like a Priority Queue
					# heapq works with a min priority queue, so I used -1*len(v) to build it
					for key, value in graph.items():
										# O(log(n))
										heapq.heappush(__snake_case,	[-1 * len(__snake_case      ), (key, value)]      )

					# chosen_vertices = set of chosen vertices
					_UpperCamelCase									=    set()

					# while queue isn't empty and there are still edges
					#   (queue[0][0] is the rank of the node with max rank)
					while queue and queue[0][0] != 0:
										# extract vertex with max rank from queue and add it to chosen_vertices
										_UpperCamelCase									=    heapq.heappop(__snake_case      )[1][0]
										chosen_vertices.add(__snake_case      )

										# Remove all arcs adjacent to argmax
										for elem in queue:
															# if v haven't adjacent node, skip
															if elem[0] == 0:
																				continue
															# if argmax is reachable from elem
															# remove argmax from elem's adjacent list and update his rank
															if argmax in elem[1][1]:
																				_UpperCamelCase									=    elem[1][1].index(__snake_case      )
																				del elem[1][1][index]
																				elem[0] += 1
        # re-order the queue
										heapq.heapify(__snake_case      )
					return chosen_vertices


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				_a								=						{0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
				print(F"""Minimum vertex cover:\n{greedy_min_vertex_cover(graph)}""")






