



"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase					=       {'''configuration_wavlm''': ['''WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WavLMConfig''']}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase					=       [
					    '''WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''WavLMForAudioFrameClassification''',
					    '''WavLMForCTC''',
					    '''WavLMForSequenceClassification''',
					    '''WavLMForXVector''',
					    '''WavLMModel''',
					    '''WavLMPreTrainedModel''',
					]

if TYPE_CHECKING:
					from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_wavlm import (
										    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
										    WavLMForAudioFrameClassification,
										    WavLMForCTC,
										    WavLMForSequenceClassification,
										    WavLMForXVector,
										    WavLMModel,
										    WavLMPreTrainedModel,
										)

else:
					import sys

					lowercase					=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




"""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


__SCREAMING_SNAKE_CASE							=     logging.get_logger(__name__)

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

__SCREAMING_SNAKE_CASE							=     {
    '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							=     {
    '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,
}


__SCREAMING_SNAKE_CASE							=     {
    '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__       ):
     UpperCAmelCase__         =      VOCAB_FILES_NAMES
     UpperCAmelCase__         =      PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__         =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__         =      PRETRAINED_INIT_CONFIGURATION
     UpperCAmelCase__         =      RoFormerTokenizer



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

      UpperCamelCase_     :					Any   	=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
      ):
       UpperCamelCase_     :					Optional[Any]   	=getattr(_lowerCamelCase      ,  pre_tok_state.pop('type'   )   )
       UpperCamelCase_     :					Tuple   	=do_lower_case
       UpperCamelCase_     :					Union[str, Any]   	=strip_accents
       UpperCamelCase_     :					Union[str, Any]   	=pre_tok_class(**_lowerCamelCase   )

      UpperCamelCase_     :					List[str]   	=do_lower_case



     def __getstate__(							self :Any   ):







      '''simple docstring'''



      UpperCamelCase_     :					str   	=self.__dict__.copy()
      UpperCamelCase_     :					Union[str, Any]   	=BertPreTokenizer()
      return state



     def __setstate__(							self :str      ,  _lowerCamelCase :Optional[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					int   	=d
      UpperCamelCase_     :					Optional[int]   	=self.__dict__['_tokenizer'].get_vocab()
      UpperCamelCase_     :					Any   	=PreTokenizer.custom(JiebaPreTokenizer(_lowerCamelCase   )   )



     def  lowerCamelCase_						(							self :Dict      ,  _lowerCamelCase :Optional[Any]      ,  _lowerCamelCase :Any=None   ):







      '''simple docstring'''



      UpperCamelCase_     :					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  lowerCamelCase_						(							self :Union[str, Any]      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[Any]   	=[self.sep_token_id]
      UpperCamelCase_     :					List[Any]   	=[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 :Optional[int]      ,  _lowerCamelCase :str      ,  _lowerCamelCase :Optional[str] = None   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[Any]   	=self._tokenizer.model.save(_lowerCamelCase      ,  name=_lowerCamelCase   )
      return tuple(_lowerCamelCase   )




     def  lowerCamelCase_						(							self :str      ,  _lowerCamelCase :List[str]      ,  _lowerCamelCase :List[Any]=None      ,  _lowerCamelCase :Optional[Any]=None      ,  _lowerCamelCase :int=False      ,  **_lowerCamelCase :Optional[int]      ,  ):







      '''simple docstring'''



      UpperCamelCase_     :					str   	=BertPreTokenizer()
      return super().save_pretrained(_lowerCamelCase      ,  _lowerCamelCase      ,  _lowerCamelCase      ,  _lowerCamelCase      ,  **_lowerCamelCase   )
