



'''simple docstring'''

import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__lowerCAmelCase						      =       logging.get_logger(__name__)


__lowerCAmelCase						      =       {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

# See all BART models at https://huggingface.co/models?filter=bart
__lowerCAmelCase						      =       {
    '''vocab_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/vocab.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/vocab.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/merges.txt''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/merges.txt''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt''',
    },
}

__lowerCAmelCase						      =       {
    '''facebook/bart-base''': 1_024,
    '''facebook/bart-large''': 1_024,
    '''facebook/bart-large-mnli''': 1_024,
    '''facebook/bart-large-cnn''': 1_024,
    '''facebook/bart-large-xsum''': 1_024,
    '''yjernite/bart_eli5''': 1_024,
}



@lru_cache()
def 					__lowerCamelCase					(				)      ->				Dict:
		_a					:				List[Any]				=							(
		    list(range(ord('!'  )						,      ord('~'  ) + 1  )  ) + list(range(ord('¡'  )						,      ord('¬'  ) + 1  )  ) + list(range(ord('®'  )						,      ord('ÿ'  ) + 1  )  )
		)
		_a					:				Any				=							bs[:]
		_a					:				int				=							0
		for b in range(2**8  ):
				if b not in bs:
						bs.append(lowerCAmelCase_  )
						cs.append(2**8 + n  )
						n += 1
		_a					:				Optional[Any]				=							[chr(lowerCAmelCase_  ) for n in cs]
		return dict(zip(lowerCAmelCase_						,      lowerCAmelCase_  )  )



def 					__lowerCamelCase					(				lowerCAmelCase_  )      ->				Optional[Any]:
		_a					:				int				=							set()
		_a					:				Any				=							word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)  )
				_a					:				Tuple				=							char
		return pairs

class      __magic_name__						(   _UpperCamelCase       ):
							lowerCAmelCase	:   Optional[int]           = VOCAB_FILES_NAMES
							lowerCAmelCase	:   Tuple           = PRETRAINED_VOCAB_FILES_MAP
							lowerCAmelCase	:   Union[str, Any]           = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCAmelCase	:   Any           = ['input_ids', 'attention_mask']







							def __init__(							self :	Union[str, Any]     ,_UpperCAmelCase :	Union[str, Any]     ,_UpperCAmelCase :	str     ,_UpperCAmelCase :	List[Any]="replace"     ,_UpperCAmelCase :	List[str]="<s>"     ,_UpperCAmelCase :	List[str]="</s>"     ,_UpperCAmelCase :	List[Any]="</s>"     ,_UpperCAmelCase :	Optional[Any]="<s>"     ,_UpperCAmelCase :	Dict="<unk>"     ,_UpperCAmelCase :	List[str]="<pad>"     ,_UpperCAmelCase :	Optional[int]="<mask>"     ,_UpperCAmelCase :	Any=False     ,**_UpperCAmelCase :	List[str]     ,):
									_a					:				List[str]				=							AddedToken(_UpperCAmelCase     ,lstrip=_UpperCAmelCase     ,rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase     ,_UpperCAmelCase		) else bos_token
									_a					:				Dict				=							AddedToken(_UpperCAmelCase     ,lstrip=_UpperCAmelCase     ,rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase     ,_UpperCAmelCase		) else eos_token
									_a					:				Optional[int]				=							AddedToken(_UpperCAmelCase     ,lstrip=_UpperCAmelCase     ,rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase     ,_UpperCAmelCase		) else sep_token
									_a					:				Optional[int]				=							AddedToken(_UpperCAmelCase     ,lstrip=_UpperCAmelCase     ,rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase     ,_UpperCAmelCase		) else cls_token
									_a					:				Any				=							AddedToken(_UpperCAmelCase     ,lstrip=_UpperCAmelCase     ,rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase     ,_UpperCAmelCase		) else unk_token
									_a					:				Dict				=							AddedToken(_UpperCAmelCase     ,lstrip=_UpperCAmelCase     ,rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase     ,_UpperCAmelCase		) else pad_token

									# Mask token behave like a normal word, i.e. include the space before it
									_a					:				Optional[int]				=							AddedToken(_UpperCAmelCase     ,lstrip=_UpperCAmelCase     ,rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase     ,_UpperCAmelCase		) else mask_token

									super().__init__(
									    errors=_UpperCAmelCase     ,bos_token=_UpperCAmelCase     ,eos_token=_UpperCAmelCase     ,unk_token=_UpperCAmelCase     ,sep_token=_UpperCAmelCase     ,cls_token=_UpperCAmelCase     ,pad_token=_UpperCAmelCase     ,mask_token=_UpperCAmelCase     ,add_prefix_space=_UpperCAmelCase     ,**_UpperCAmelCase     ,)

									with open(_UpperCAmelCase     ,encoding='utf-8'		) as vocab_handle:
											_a					:				Optional[int]				=							json.load(_UpperCAmelCase		)
									_a					:				List[Any]				=							{v: k for k, v in self.encoder.items()}
									_a					:				Any				=							errors  # how to handle errors in decoding
									_a					:				Optional[int]				=							bytes_to_unicode()
									_a					:				Optional[Any]				=							{v: k for k, v in self.byte_encoder.items()}
									with open(_UpperCAmelCase     ,encoding='utf-8'		) as merges_handle:
											_a					:				str				=							merges_handle.read().split('\n'		)[1:-1]
									_a					:				List[Any]				=							[tuple(merge.split()		) for merge in bpe_merges]
									_a					:				int				=							dict(zip(_UpperCAmelCase     ,range(len(_UpperCAmelCase		)		)		)		)
									_a					:				List[str]				=							{}
									_a					:				List[str]				=							add_prefix_space

									# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
									_a					:				Optional[int]				=							re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'		)







							@property
							def 							__lowercase      (							self :	List[Any]		):
									return len(self.encoder		)







							def 							__lowercase      (							self :	Tuple		):
									return dict(self.encoder     ,**self.added_tokens_encoder		)







							def 							__lowercase      (							self :	Optional[int]     ,_UpperCAmelCase :	Dict		):
									if token in self.cache:
											return self.cache[token]
									_a					:				Union[str, Any]				=							tuple(_UpperCAmelCase		)
									_a					:				Union[str, Any]				=							get_pairs(_UpperCAmelCase		)

									if not pairs:
											return token

									while True:
											_a					:				Tuple				=							min(_UpperCAmelCase     ,key=lambda _UpperCAmelCase		: self.bpe_ranks.get(_UpperCAmelCase     ,float('inf'		)		)		)
											if bigram not in self.bpe_ranks:
													break
											_a	, _a					:				Tuple				=							bigram
											_a					:				Optional[int]				=							[]
											_a					:				Tuple				=							0
											while i < len(_UpperCAmelCase		):
													try:
															_a					:				Dict				=							word.index(_UpperCAmelCase     ,_UpperCAmelCase		)
													except ValueError:
															new_word.extend(word[i:]		)
															break
													else:
															new_word.extend(word[i:j]		)
															_a					:				Tuple				=							j

													if word[i] == first and i < len(_UpperCAmelCase		) - 1 and word[i + 1] == second:
															new_word.append(first + second		)
															i += 2
													else:
															new_word.append(word[i]		)
															i += 1
											_a					:				List[str]				=							tuple(_UpperCAmelCase		)
											_a					:				Dict				=							new_word
											if len(_UpperCAmelCase		) == 1:
													break
											else:
													_a					:				Optional[Any]				=							get_pairs(_UpperCAmelCase		)
									_a					:				List[str]				=							' '.join(_UpperCAmelCase		)
									_a					:				Tuple				=							word
									return word







							def 							__lowercase      (							self :	Optional[int]     ,_UpperCAmelCase :	int		):
									_a					:				int				=							[]
									for token in re.findall(self.pat     ,_UpperCAmelCase		):
											_a					:				Union[str, Any]				=							''.join(
											    self.byte_encoder[b] for b in token.encode('utf-8'		)		)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
											bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_UpperCAmelCase		).split(' '		)		)
									return bpe_tokens







							def 							__lowercase      (							self :	Optional[Any]     ,_UpperCAmelCase :	Optional[int]		):
									return self.encoder.get(_UpperCAmelCase     ,self.encoder.get(self.unk_token		)		)







							def 							__lowercase      (							self :	str     ,_UpperCAmelCase :	int		):
									return self.decoder.get(_UpperCAmelCase		)







							def 							__lowercase      (							self :	Optional[int]     ,_UpperCAmelCase :	Optional[int]		):
									_a					:				List[str]				=							''.join(_UpperCAmelCase		)
									_a					:				Any				=							bytearray([self.byte_decoder[c] for c in text]		).decode('utf-8'     ,errors=self.errors		)
									return text







							def 							__lowercase      (							self :	Tuple     ,_UpperCAmelCase :	str     ,_UpperCAmelCase :	Optional[str] = None		):
									if not os.path.isdir(_UpperCAmelCase		):
											logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""		)
											return
									_a					:				Any				=							os.path.join(
									    _UpperCAmelCase     ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']		)
									_a					:				Optional[int]				=							os.path.join(
									    _UpperCAmelCase     ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']		)

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

									_a					:				Union[str, Any]				=							0
									with open(_UpperCAmelCase     ,'w'     ,encoding='utf-8'		) as writer:
											writer.write('#version: 0.2\n'		)
											for bpe_tokens, token_index in sorted(self.bpe_ranks.items()     ,key=lambda _UpperCAmelCase		: kv[1]		):
													if index != token_index:
															logger.warning(
															    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
															    ' Please check that the tokenizer is not corrupted!'		)
															_a					:				Optional[Any]				=							token_index
													writer.write(' '.join(_UpperCAmelCase		) + '\n'		)
													index += 1

									return vocab_file, merge_file







							def 							__lowercase      (							self :	Optional[int]     ,_UpperCAmelCase :	List[int]     ,_UpperCAmelCase :	Optional[List[int]] = None		):
									if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
									_a					:				str				=							[self.cls_token_id]
									_a					:				int				=							[self.sep_token_id]
									return cls + token_ids_a + sep + sep + token_ids_a + sep







							def 							__lowercase      (							self :	Any     ,_UpperCAmelCase :	List[int]     ,_UpperCAmelCase :	Optional[List[int]] = None     ,_UpperCAmelCase :	bool = False		):
									if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=_UpperCAmelCase     ,token_ids_a=_UpperCAmelCase     ,already_has_special_tokens=_UpperCAmelCase		)

									if token_ids_a is None:
											return [1] + ([0] * len(_UpperCAmelCase		)) + [1]
									return [1] + ([0] * len(_UpperCAmelCase		)) + [1, 1] + ([0] * len(_UpperCAmelCase		)) + [1]







							def 							__lowercase      (							self :	str     ,_UpperCAmelCase :	List[int]     ,_UpperCAmelCase :	Optional[List[int]] = None		):
									_a					:				Tuple				=							[self.sep_token_id]
									_a					:				Any				=							[self.cls_token_id]

									if token_ids_a is None:
											return len(cls + token_ids_a + sep		) * [0]
									return len(cls + token_ids_a + sep + sep + token_ids_a + sep		) * [0]







							def 							__lowercase      (							self :	str     ,_UpperCAmelCase :	Dict     ,_UpperCAmelCase :	int=False     ,**_UpperCAmelCase :	int		):
									_a					:				Union[str, Any]				=							kwargs.pop('add_prefix_space'     ,self.add_prefix_space		)
									if (is_split_into_words or add_prefix_space) and (len(_UpperCAmelCase		) > 0 and not text[0].isspace()):
											_a					:				str				=							' ' + text
									return (text, kwargs)









'''simple docstring'''

import heapq



def 					__lowerCamelCase					(				lowerCAmelCase_  )      ->				set[int]:
		_a					:				list[list]				=							[]

		# 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(lowerCAmelCase_						,      [-1 * len(lowerCAmelCase_  ), (key, value)]  )

		# chosen_vertices = set of chosen vertices
		_a					:				str				=							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
				_a					:				Optional[int]				=							heapq.heappop(lowerCAmelCase_  )[1][0]
				chosen_vertices.add(lowerCAmelCase_  )

				# 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]:
								_a					:				Dict				=							elem[1][1].index(lowerCAmelCase_  )
								del elem[1][1][index]
								elem[0] += 1
        # re-order the queue
				heapq.heapify(lowerCAmelCase_  )
		return chosen_vertices


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							__lowerCAmelCase						      =       {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)}""")




