






import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer


A__      :     Any       =					logging.get_logger(__name__)

A__      :     Union[str, Any]       =					{'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

A__      :     List[Any]       =					{
    'vocab_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/vocab.txt',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/vocab.txt',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt'
        ),
        'bert-base-multilingual-cased': 'https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt',
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt'
        ),
        'bert-base-german-dbmdz-cased': 'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt',
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/tokenizer.json',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/tokenizer.json',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/tokenizer.json'
        ),
        'bert-base-multilingual-cased': (
            'https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/tokenizer.json',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/tokenizer.json',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-cased': (
            'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/tokenizer.json'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/tokenizer.json'
        ),
    },
}

A__      :     Union[str, Any]       =					{
    'bert-base-uncased': 5_12,
    'bert-large-uncased': 5_12,
    'bert-base-cased': 5_12,
    'bert-large-cased': 5_12,
    'bert-base-multilingual-uncased': 5_12,
    'bert-base-multilingual-cased': 5_12,
    'bert-base-chinese': 5_12,
    'bert-base-german-cased': 5_12,
    'bert-large-uncased-whole-word-masking': 5_12,
    'bert-large-cased-whole-word-masking': 5_12,
    'bert-large-uncased-whole-word-masking-finetuned-squad': 5_12,
    'bert-large-cased-whole-word-masking-finetuned-squad': 5_12,
    'bert-base-cased-finetuned-mrpc': 5_12,
    'bert-base-german-dbmdz-cased': 5_12,
    'bert-base-german-dbmdz-uncased': 5_12,
    'TurkuNLP/bert-base-finnish-cased-v1': 5_12,
    'TurkuNLP/bert-base-finnish-uncased-v1': 5_12,
    'wietsedv/bert-base-dutch-cased': 5_12,
}

A__      :     Optional[Any]       =					{
    'bert-base-uncased': {'do_lower_case': True},
    'bert-large-uncased': {'do_lower_case': True},
    'bert-base-cased': {'do_lower_case': False},
    'bert-large-cased': {'do_lower_case': False},
    'bert-base-multilingual-uncased': {'do_lower_case': True},
    'bert-base-multilingual-cased': {'do_lower_case': False},
    'bert-base-chinese': {'do_lower_case': False},
    'bert-base-german-cased': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking-finetuned-squad': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking-finetuned-squad': {'do_lower_case': False},
    'bert-base-cased-finetuned-mrpc': {'do_lower_case': False},
    'bert-base-german-dbmdz-cased': {'do_lower_case': False},
    'bert-base-german-dbmdz-uncased': {'do_lower_case': True},
    'TurkuNLP/bert-base-finnish-cased-v1': {'do_lower_case': False},
    'TurkuNLP/bert-base-finnish-uncased-v1': {'do_lower_case': True},
    'wietsedv/bert-base-dutch-cased': {'do_lower_case': False},
}
class  _UpperCAmelCase   (			A__      ):

				"""simple docstring"""




				lowercase__											=			VOCAB_FILES_NAMES
				lowercase__											=			PRETRAINED_VOCAB_FILES_MAP
				lowercase__											=			PRETRAINED_INIT_CONFIGURATION
				lowercase__											=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowercase__											=			BertTokenizer




				def __init__(	self		:       Union[str, Any],    lowerCamelCase		:       List[Any]=None,    lowerCamelCase		:       Tuple=None,    lowerCamelCase		:       Any=True,    lowerCamelCase		:       int="[UNK]",    lowerCamelCase		:       Tuple="[SEP]",    lowerCamelCase		:       List[str]="[PAD]",    lowerCamelCase		:       Union[str, Any]="[CLS]",    lowerCamelCase		:       Optional[int]="[MASK]",    lowerCamelCase		:       Union[str, Any]=True,    lowerCamelCase		:       Dict=None,    **lowerCamelCase		:       Any,    ):

								'''simple docstring'''
								super().__init__(
								    lowerCamelCase,    tokenizer_file=lowerCamelCase,    do_lower_case=lowerCamelCase,    unk_token=lowerCamelCase,    sep_token=lowerCamelCase,    pad_token=lowerCamelCase,    cls_token=lowerCamelCase,    mask_token=lowerCamelCase,    tokenize_chinese_chars=lowerCamelCase,    strip_accents=lowerCamelCase,    **lowerCamelCase,    )

								lowercase__  					=     json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
								if (
								    normalizer_state.get('''lowercase''',    lowerCamelCase    ) != do_lower_case
								    or normalizer_state.get('''strip_accents''',    lowerCamelCase    ) != strip_accents
								    or normalizer_state.get('''handle_chinese_chars''',    lowerCamelCase    ) != tokenize_chinese_chars
								):
												lowercase__  					=     getattr(lowerCamelCase,    normalizer_state.pop('''type'''    )    )
												lowercase__  					=     do_lower_case
												lowercase__  					=     strip_accents
												lowercase__  					=     tokenize_chinese_chars
												lowercase__  					=     normalizer_class(**lowerCamelCase    )

								lowercase__  					=     do_lower_case




				def 							lowercase__  (	self		:       int,    lowerCamelCase		:       Dict,    lowerCamelCase		:       Union[str, Any]=None    ):

								'''simple docstring'''
								lowercase__  					=     [self.cls_token_id] + token_ids_a + [self.sep_token_id]

								if token_ids_a:
												output += token_ids_a + [self.sep_token_id]

								return output




				def 							lowercase__  (	self		:       Tuple,    lowerCamelCase		:       List[int],    lowerCamelCase		:       Optional[List[int]] = None    ):

								'''simple docstring'''
								lowercase__  					=     [self.sep_token_id]
								lowercase__  					=     [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    ) * [0] + len(token_ids_a + sep    ) * [1]




				def 							lowercase__  (	self		:       Optional[Any],    lowerCamelCase		:       str,    lowerCamelCase		:       Optional[str] = None    ):

								'''simple docstring'''
								lowercase__  					=     self._tokenizer.model.save(lowerCamelCase,    name=lowerCamelCase    )
								return tuple(lowerCamelCase    )












import heapq as hq
import math
from collections.abc import Iterator
class  _UpperCAmelCase   :

				"""simple docstring"""




				def __init__(	self		:       str,    lowerCamelCase		:       List[Any]    ):

								'''simple docstring'''
								lowercase__  					=     str(id_    )
								lowercase__  					=     None
								lowercase__  					=     None
								lowercase__  					=     []
								lowercase__  					=     {}  # {vertex:distance}




				def __lt__(	self		:       Dict,    lowerCamelCase		:       Tuple    ):

								'''simple docstring'''
								return self.key < other.key




				def __repr__(	self		:       Dict    ):

								'''simple docstring'''
								return self.id




				def 							lowercase__  (	self		:       str,    lowerCamelCase		:       List[str]    ):

								'''simple docstring'''
								self.neighbors.append(lowerCamelCase    )




				def 							lowercase__  (	self		:       Any,    lowerCamelCase		:       Dict,    lowerCamelCase		:       Optional[Any]    ):

								'''simple docstring'''
								lowercase__  					=     weight






def     a     (		lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				# add the neighbors:
				graph[a - 1].add_neighbor(graph[b - 1]							)
				graph[b - 1].add_neighbor(graph[a - 1]							)
				# add the edges:
				graph[a - 1].add_edge(graph[b - 1]						,  lowerCamelCase_							)
				graph[b - 1].add_edge(graph[a - 1]						,  lowerCamelCase_							)






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     []
				for u in graph:
								lowercase__  					=     math.inf
								lowercase__  					=     None
				lowercase__  					=     0
				lowercase__  					=     graph[:]
				while q:
								lowercase__  					=     min(lowerCamelCase_							)
								q.remove(lowerCamelCase_							)
								for v in u.neighbors:
												if (v in q) and (u.edges[v.id] < v.key):
																lowercase__  					=     u
																lowercase__  					=     u.edges[v.id]
				for i in range(1						,  len(lowerCamelCase_							)							):
								a.append((int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)							)
				return a






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				for u in graph:
								lowercase__  					=     math.inf
								lowercase__  					=     None
				lowercase__  					=     0

				lowercase__  					=     list(lowerCamelCase_							)
				hq.heapify(lowerCamelCase_							)

				while h:
								lowercase__  					=     hq.heappop(lowerCamelCase_							)
								for v in u.neighbors:
												if (v in h) and (u.edges[v.id] < v.key):
																lowercase__  					=     u
																lowercase__  					=     u.edges[v.id]
																hq.heapify(lowerCamelCase_							)

				for i in range(1						,  len(lowerCamelCase_							)							):
								yield (int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)






def     a     (		):






				'''simple docstring'''


if __name__ == "__main__":
							import doctest

							doctest.testmod()




