


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


__lowerCAmelCase		       =							logging.get_logger(__name__)

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

__lowerCAmelCase		       =							{
    '''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'''
        ),
    },
}

__lowerCAmelCase		       =							{
    '''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,
}

__lowerCAmelCase		       =							{
    '''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 :							Dict        = VOCAB_FILES_NAMES
 __lowercase :							Any        = PRETRAINED_VOCAB_FILES_MAP
 __lowercase :							Optional[Any]        = PRETRAINED_INIT_CONFIGURATION
 __lowercase :							str        = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowercase :							Union[str, Any]        = BertTokenizer
 def __init__(   self				, lowerCAmelCase__=None				, lowerCAmelCase__=None				, lowerCAmelCase__=True				, lowerCAmelCase__="[UNK]"				, lowerCAmelCase__="[SEP]"				, lowerCAmelCase__="[PAD]"				, lowerCAmelCase__="[CLS]"				, lowerCAmelCase__="[MASK]"				, lowerCAmelCase__=True				, lowerCAmelCase__=None				, **lowerCAmelCase__				, )					->				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__				, )

        lowercase__:   str  			=   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__:   Optional[Any]  			=   getattr(lowerCAmelCase__				, normalizer_state.pop('type' ) )
               lowercase__:   Tuple  			=   do_lower_case
               lowercase__:   List[Any]  			=   strip_accents
               lowercase__:   Any  			=   tokenize_chinese_chars
               lowercase__:   Dict  			=   normalizer_class(**lowerCAmelCase__ )

        lowercase__:   Dict  			=   do_lower_case
 def 		SCREAMING_SNAKE_CASE__   (   self				, lowerCAmelCase__				, lowerCAmelCase__=None )					->				int:




        '''simple docstring'''
        lowercase__:   Optional[int]  			=   [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 		SCREAMING_SNAKE_CASE__   (   self				, lowerCAmelCase__				, lowerCAmelCase__ = None )					->				Optional[int]:




        '''simple docstring'''
        lowercase__:   List[str]  			=   [self.sep_token_id]
        lowercase__:   str  			=   [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 		SCREAMING_SNAKE_CASE__   (   self				, lowerCAmelCase__				, lowerCAmelCase__ = None )					->				Optional[int]:




        '''simple docstring'''
        lowercase__:   List[str]  			=   self._tokenizer.model.save(lowerCAmelCase__				, name=lowerCAmelCase__ )
        return tuple(lowerCAmelCase__ )






from __future__ import annotations







def        _lowerCamelCase(	lowercase__   , lowercase__	)						->	Any:

		'''simple docstring'''







		if len(lowercase__	) <= 1 or n <= 1:
				return

		insert_next(lowercase__   , n - 1	)
		rec_insertion_sort(lowercase__   , n - 1	)







def        _lowerCamelCase(	lowercase__   , lowercase__	)						->	Any:

		'''simple docstring'''







		if index >= len(lowercase__	) or collection[index - 1] <= collection[index]:
				return

		# Swaps adjacent elements since they are not in ascending order
		__lowercase,							__lowercase=			(
		    collection[index],
		    collection[index - 1],
		)

		insert_next(lowercase__   , index + 1	)


if __name__ == "__main__":
	lowerCAmelCase           =		input('''Enter integers separated by spaces: ''')
	lowerCAmelCase           =		[int(num) for num in numbers.split()]
	rec_insertion_sort(number_list, len(number_list))
	print(number_list)






