




'''simple docstring'''







import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mpnet import MPNetTokenizer


A			   =logging.get_logger(__name__)

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

A			   ={
    'vocab_file': {
        'microsoft/mpnet-base': 'https://huggingface.co/microsoft/mpnet-base/resolve/main/vocab.txt',
    },
    'tokenizer_file': {
        'microsoft/mpnet-base': 'https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer.json',
    },
}

A			   ={
    'microsoft/mpnet-base': 5_12,
}

A			   ={
    'microsoft/mpnet-base': {'do_lower_case': True},
}


class       _a  (     __a			):
       __a    :					int           = VOCAB_FILES_NAMES
       __a    :					str           = PRETRAINED_VOCAB_FILES_MAP
       __a    :					Dict           = PRETRAINED_INIT_CONFIGURATION
       __a    :					Union[str, Any]           = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __a    :					Optional[Any]           = MPNetTokenizer
       __a    :					List[str]           = ["""input_ids""", """attention_mask"""]
       def __init__(     self						:     List[str]       ,    lowercase						:     List[Any]=None       ,    lowercase						:     List[Any]=None       ,    lowercase						:     Any=True       ,    lowercase						:     str="<s>"       ,    lowercase						:     Any="</s>"       ,    lowercase						:     Tuple="</s>"       ,    lowercase						:     int="<s>"       ,    lowercase						:     Optional[Any]="[UNK]"       ,    lowercase						:     Union[str, Any]="<pad>"       ,    lowercase						:     Optional[int]="<mask>"       ,    lowercase						:     Optional[int]=True       ,    lowercase						:     Optional[Any]=None       ,    **lowercase						:     Union[str, Any]       ,    ):



           '''simple docstring'''

           super().__init__(
               lowercase       ,    tokenizer_file=lowercase       ,    do_lower_case=lowercase       ,    bos_token=lowercase       ,    eos_token=lowercase       ,    sep_token=lowercase       ,    cls_token=lowercase       ,    unk_token=lowercase       ,    pad_token=lowercase       ,    mask_token=lowercase       ,    tokenize_chinese_chars=lowercase       ,    strip_accents=lowercase       ,    **lowercase       ,    )

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

           UpperCAmelCase      	=		do_lower_case
       @property
       def    A				(     self						:     Union[str, Any]    ):



           '''simple docstring'''

           if self._mask_token is None:
               if self.verbose:
                   logger.error('''Using mask_token, but it is not set yet.'''    )
               return None
           return str(self._mask_token    )
       @mask_token.setter
       def    A				(     self						:     int       ,    lowercase						:     Dict    ):



           '''simple docstring'''

           UpperCAmelCase      	=		AddedToken(lowercase       ,    lstrip=lowercase       ,    rstrip=lowercase    ) if isinstance(lowercase       ,    lowercase    ) else value
           UpperCAmelCase      	=		value
       def    A				(     self						:     Tuple       ,    lowercase						:     Dict       ,    lowercase						:     Optional[Any]=None    ):



           '''simple docstring'''

           UpperCAmelCase      	=		[self.bos_token_id] + token_ids_a + [self.eos_token_id]
           if token_ids_a is None:
               return output

           return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]
       def    A				(     self						:     Dict       ,    lowercase						:     List[int]       ,    lowercase						:     Optional[List[int]] = None    ):



           '''simple docstring'''

           UpperCAmelCase      	=		[self.sep_token_id]
           UpperCAmelCase      	=		[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 + sep + token_ids_a + sep    ) * [0]







       def    A				(     self						:     Union[str, Any]       ,    lowercase						:     str       ,    lowercase						:     Optional[str] = None    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self._tokenizer.model.save(lowercase       ,    name=lowercase    )
           return tuple(lowercase    )










'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A			   ={'configuration_dinat': ['DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DinatConfig']}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A			   =[
       'DINAT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'DinatForImageClassification',
       'DinatModel',
       'DinatPreTrainedModel',
       'DinatBackbone',
   ]

if TYPE_CHECKING:
   from .configuration_dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_dinat import (
          DINAT_PRETRAINED_MODEL_ARCHIVE_LIST,
          DinatBackbone,
          DinatForImageClassification,
          DinatModel,
          DinatPreTrainedModel,
      )

else:
   import sys

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




