

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


_SCREAMING_SNAKE_CASE					:  str             =      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					:  Optional[Any]             =      {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_SCREAMING_SNAKE_CASE					:  int             =      {
    '''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'''
        ),
    }
}

_SCREAMING_SNAKE_CASE					:  Dict             =      {
    '''junnyu/roformer_chinese_small''': 1536,
    '''junnyu/roformer_chinese_base''': 1536,
    '''junnyu/roformer_chinese_char_small''': 512,
    '''junnyu/roformer_chinese_char_base''': 512,
    '''junnyu/roformer_small_discriminator''': 128,
    '''junnyu/roformer_small_generator''': 128,
}


_SCREAMING_SNAKE_CASE					:  Union[str, Any]             =      {
    '''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 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  a									= VOCAB_FILES_NAMES
  a									= PRETRAINED_VOCAB_FILES_MAP
  a									= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  a									= PRETRAINED_INIT_CONFIGURATION
  a									= RoFormerTokenizer






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

       SCREAMING_SNAKE_CASE__   =   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
       ):
            SCREAMING_SNAKE_CASE__   =   getattr(__lowerCamelCase     ,       pre_tok_state.pop('''type''' ) )
            SCREAMING_SNAKE_CASE__   =   do_lower_case
            SCREAMING_SNAKE_CASE__   =   strip_accents
            SCREAMING_SNAKE_CASE__   =   pre_tok_class(**__lowerCamelCase )

       SCREAMING_SNAKE_CASE__   =   do_lower_case






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






  def __setstate__(							self						:		Optional[int]     ,       __lowerCamelCase						:		str )		->							Optional[Any]:
       SCREAMING_SNAKE_CASE__   =   d
       SCREAMING_SNAKE_CASE__   =   self.__dict__['''_tokenizer'''].get_vocab()
       SCREAMING_SNAKE_CASE__   =   PreTokenizer.custom(JiebaPreTokenizer(__lowerCamelCase ) )






  def 				lowercase_		(							self						:		int     ,       __lowerCamelCase						:		Any     ,       __lowerCamelCase						:		List[Any]=None )		->							List[str]:
       SCREAMING_SNAKE_CASE__   =   [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						:		Dict     ,       __lowerCamelCase						:		List[int]     ,       __lowerCamelCase						:		Optional[List[int]] = None )		->							List[int]:
       SCREAMING_SNAKE_CASE__   =   [self.sep_token_id]
       SCREAMING_SNAKE_CASE__   =   [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						:		List[str]     ,       __lowerCamelCase						:		str     ,       __lowerCamelCase						:		Optional[str] = None )		->							Tuple[str]:
       SCREAMING_SNAKE_CASE__   =   self._tokenizer.model.save(__lowerCamelCase     ,       name=__lowerCamelCase )
       return tuple(__lowerCamelCase )







  def 				lowercase_		(							self						:		int     ,       __lowerCamelCase						:		Optional[int]     ,       __lowerCamelCase						:		Union[str, Any]=None     ,       __lowerCamelCase						:		str=None     ,       __lowerCamelCase						:		Dict=False     ,       **__lowerCamelCase						:		Union[str, Any]     ,       )		->							Tuple:
       SCREAMING_SNAKE_CASE__   =   BertPreTokenizer()
       return super().save_pretrained(__lowerCamelCase     ,       __lowerCamelCase     ,       __lowerCamelCase     ,       __lowerCamelCase     ,       **__lowerCamelCase )





from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
       from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline


