


'''simple docstring'''






import random


def  _snake_case       (					A			,   A	)						->   tuple:
							lowerCAmelCase__	       =     [], [], []
							for element in data:
														if element < pivot:
																					less.append(_UpperCAmelCase	)
														elif element > pivot:
																					greater.append(_UpperCAmelCase	)
														else:
																					equal.append(_UpperCAmelCase	)
							return less, equal, greater






def  _snake_case       (					A			,   A	)						->   Any:


							if index >= len(_UpperCAmelCase	) or index < 0:
														return None

							lowerCAmelCase__	       =     items[random.randint(0			,   len(_UpperCAmelCase	) - 1	)]
							lowerCAmelCase__	       =     0
							lowerCAmelCase__	       =     _partition(_UpperCAmelCase			,   _UpperCAmelCase	)
							lowerCAmelCase__	       =     len(_UpperCAmelCase	)
							lowerCAmelCase__	       =     len(_UpperCAmelCase	)

							# index is the pivot
							if m <= index < m + count:
														return pivot
							# must be in smaller
							elif m > index:
														return quick_select(_UpperCAmelCase			,   _UpperCAmelCase	)
							# must be in larger
							else:
														return quick_select(_UpperCAmelCase			,   index - (m + count)	)



'''simple docstring'''






import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


__UpperCAmelCase       =							logging.get_logger(__name__)

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

__UpperCAmelCase       =							{
    '''vocab_file''': {
        '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt''',
        '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt''',
        '''junnyu/roformer_chinese_char_small''': (
            '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt'''
        ),
        '''junnyu/roformer_chinese_char_base''': (
            '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt'''
        ),
        '''junnyu/roformer_small_discriminator''': (
            '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt'''
        ),
        '''junnyu/roformer_small_generator''': (
            '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt'''
        ),
    }
}

__UpperCAmelCase       =							{
    '''junnyu/roformer_chinese_small''': 1_536,
    '''junnyu/roformer_chinese_base''': 1_536,
    '''junnyu/roformer_chinese_char_small''': 512,
    '''junnyu/roformer_chinese_char_base''': 512,
    '''junnyu/roformer_small_discriminator''': 128,
    '''junnyu/roformer_small_generator''': 128,
}


__UpperCAmelCase       =							{
    '''junnyu/roformer_chinese_small''': {'''do_lower_case''': True},
    '''junnyu/roformer_chinese_base''': {'''do_lower_case''': True},
    '''junnyu/roformer_chinese_char_small''': {'''do_lower_case''': True},
    '''junnyu/roformer_chinese_char_base''': {'''do_lower_case''': True},
    '''junnyu/roformer_small_discriminator''': {'''do_lower_case''': True},
    '''junnyu/roformer_small_generator''': {'''do_lower_case''': True},
}




class 		a__    (							a__  ):





							'''simple docstring'''






							lowercase__      :       int     						=				VOCAB_FILES_NAMES
							lowercase__      :       Optional[int]     						=				PRETRAINED_VOCAB_FILES_MAP
							lowercase__      :       Any     						=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase__      :       Union[str, Any]     						=				PRETRAINED_INIT_CONFIGURATION
							lowercase__      :       Tuple     						=				RoFormerTokenizer







							def __init__(		self ,   lowerCamelCase_=None ,   lowerCamelCase_=None ,   lowerCamelCase_=True ,   lowerCamelCase_="[UNK]" ,   lowerCamelCase_="[SEP]" ,   lowerCamelCase_="[PAD]" ,   lowerCamelCase_="[CLS]" ,   lowerCamelCase_="[MASK]" ,   lowerCamelCase_=True ,   lowerCamelCase_=None ,   **lowerCamelCase_ ,   )	->							Tuple:
														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_ ,   )

														lowerCAmelCase__	       =     json.loads(self.backend_tokenizer.normalizer.__getstate__()       )
														if (
														    pre_tok_state.get('''lowercase''' ,   lowerCamelCase_       ) != do_lower_case
														    or pre_tok_state.get('''strip_accents''' ,   lowerCamelCase_       ) != strip_accents
														):
																					lowerCAmelCase__	       =     getattr(lowerCamelCase_ ,   pre_tok_state.pop('''type'''       )       )
																					lowerCAmelCase__	       =     do_lower_case
																					lowerCAmelCase__	       =     strip_accents
																					lowerCAmelCase__	       =     pre_tok_class(**lowerCamelCase_       )

														lowerCAmelCase__	       =     do_lower_case







							def __getstate__(		self       )	->							Any:
														lowerCAmelCase__	       =     self.__dict__.copy()
														lowerCAmelCase__	       =     BertPreTokenizer()
														return state







							def __setstate__(		self ,   lowerCamelCase_       )	->							List[Any]:
														lowerCAmelCase__	       =     d
														lowerCAmelCase__	       =     self.__dict__['''_tokenizer'''].get_vocab()
														lowerCAmelCase__	       =     PreTokenizer.custom(JiebaPreTokenizer(lowerCamelCase_       )       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_=None       )	->							Union[str, Any]:
														lowerCAmelCase__	       =     [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       )	->							List[int]:
														lowerCAmelCase__	       =     [self.sep_token_id]
														lowerCAmelCase__	       =     [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       )	->							Tuple[str]:
														lowerCAmelCase__	       =     self._tokenizer.model.save(lowerCamelCase_ ,   name=lowerCamelCase_       )
														return tuple(lowerCamelCase_       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_=None ,   lowerCamelCase_=None ,   lowerCamelCase_=False ,   **lowerCamelCase_ ,   )	->							Union[str, Any]:
														lowerCAmelCase__	       =     BertPreTokenizer()
														return super().save_pretrained(lowerCamelCase_ ,   lowerCamelCase_ ,   lowerCamelCase_ ,   lowerCamelCase_ ,   **lowerCamelCase_       )