




'''simple docstring'''


def 		snake_case_   (UpperCamelCase	:  List[Any]				):





							'''simple docstring'''


							_a     					=    []
							_a     					=    set({'''(''', '''[''', '''{'''}				)
							_a     					=    set({''')''', ''']''', '''}'''}				)
							_a     					=    {'''{''': '''}''', '''[''': ''']''', '''(''': ''')'''}

							for i in range(len(__a				)				):
														if s[i] in open_brackets:
																					stack.append(s[i]				)

														elif s[i] in closed_brackets and (
														    len(__a				) == 0 or (len(__a				) > 0 and open_to_closed[stack.pop()] != s[i])
														):
																					return False

							return len(__a				) == 0
def 		snake_case_   ():





							'''simple docstring'''


							_a     					=    input('''Enter sequence of brackets: '''				)
							if is_balanced(__a				):
														print(__a			,						'''is balanced'''				)
							else:
														print(__a			,						'''is not balanced'''				)


if __name__ == "__main__":
				main()







'''simple docstring'''


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


_snake_case				:				Any       							=		logging.get_logger(__name__)

_snake_case				:				Any       							=		{'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

_snake_case				:				List[str]       							=		{
    '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'
        ),
    },
}

_snake_case				:				int       							=		{
    'bert-base-uncased': 512,
    'bert-large-uncased': 512,
    'bert-base-cased': 512,
    'bert-large-cased': 512,
    'bert-base-multilingual-uncased': 512,
    'bert-base-multilingual-cased': 512,
    'bert-base-chinese': 512,
    'bert-base-german-cased': 512,
    'bert-large-uncased-whole-word-masking': 512,
    'bert-large-cased-whole-word-masking': 512,
    'bert-large-uncased-whole-word-masking-finetuned-squad': 512,
    'bert-large-cased-whole-word-masking-finetuned-squad': 512,
    'bert-base-cased-finetuned-mrpc': 512,
    'bert-base-german-dbmdz-cased': 512,
    'bert-base-german-dbmdz-uncased': 512,
    'TurkuNLP/bert-base-finnish-cased-v1': 512,
    'TurkuNLP/bert-base-finnish-uncased-v1': 512,
    'wietsedv/bert-base-dutch-cased': 512,
}

_snake_case				:				int       							=		{
    '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       A   (		_a   ):
							lowercase_          =    VOCAB_FILES_NAMES
							lowercase_          =    PRETRAINED_VOCAB_FILES_MAP
							lowercase_          =    PRETRAINED_INIT_CONFIGURATION
							lowercase_          =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_          =    BertTokenizer







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

														_a     					=    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
														):
																					_a     					=    getattr(lowerCAmelCase_							,      normalizer_state.pop('''type''' ) )
																					_a     					=    do_lower_case
																					_a     					=    strip_accents
																					_a     					=    tokenize_chinese_chars
																					_a     					=    normalizer_class(**lowerCAmelCase_ )

														_a     					=    do_lower_case







							def        __lowerCAmelCase      (  self	:  str							,      lowerCAmelCase_	:  Dict							,      lowerCAmelCase_	:  int=None )      ->							List[str]:


														"""simple docstring"""


														_a     					=    [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        __lowerCAmelCase      (  self	:  Any							,      lowerCAmelCase_	:  List[int]							,      lowerCAmelCase_	:  Optional[List[int]] = None )      ->							List[int]:


														"""simple docstring"""


														_a     					=    [self.sep_token_id]
														_a     					=    [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        __lowerCAmelCase      (  self	:  List[Any]							,      lowerCAmelCase_	:  str							,      lowerCAmelCase_	:  Optional[str] = None )      ->							Tuple[str]:


														"""simple docstring"""


														_a     					=    self._tokenizer.model.save(lowerCAmelCase_							,      name=lowerCAmelCase_ )
														return tuple(lowerCAmelCase_ )

