
"""simple docstring"""




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
    from .tokenization_camembert import CamembertTokenizer
else:
    A__      :	List[str]          =    None


A__      :	Union[str, Any]          =    logging.get_logger(__name__)

A__      :	Optional[Any]          =    {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

A__      :	Optional[Any]          =    {
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    },
    """tokenizer_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/tokenizer.json""",
    },
}

A__      :	List[str]          =    {
    """camembert-base""": 512,
}

A__      :	str          =    """▁"""







class   _lowercase						(       lowerCAmelCase_				):


     '''simple docstring'''





     _A								=							VOCAB_FILES_NAMES
     _A								=							PRETRAINED_VOCAB_FILES_MAP
     _A								=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _A								=							['input_ids', 'attention_mask']
     _A								=							CamembertTokenizer



     def __init__(      self ,			__UpperCamelCase=None ,			__UpperCamelCase=None ,			__UpperCamelCase="<s>" ,			__UpperCamelCase="</s>" ,			__UpperCamelCase="</s>" ,			__UpperCamelCase="<s>" ,			__UpperCamelCase="<unk>" ,			__UpperCamelCase="<pad>" ,			__UpperCamelCase="<mask>" ,			__UpperCamelCase=["<s>NOTUSED", "</s>NOTUSED"] ,			**__UpperCamelCase ,			)->					Dict:
          # Mask token behave like a normal word, i.e. include the space before it
          UpperCAmelCase__							: str 							=						AddedToken(__UpperCamelCase ,			lstrip=__UpperCamelCase ,			rstrip=__UpperCamelCase  ) if isinstance(__UpperCamelCase ,			__UpperCamelCase  ) else mask_token

          super().__init__(
              __UpperCamelCase ,			tokenizer_file=__UpperCamelCase ,			bos_token=__UpperCamelCase ,			eos_token=__UpperCamelCase ,			sep_token=__UpperCamelCase ,			cls_token=__UpperCamelCase ,			unk_token=__UpperCamelCase ,			pad_token=__UpperCamelCase ,			mask_token=__UpperCamelCase ,			additional_special_tokens=__UpperCamelCase ,			**__UpperCamelCase ,			)

          UpperCAmelCase__							: str 							=						vocab_file
          UpperCAmelCase__							: Union[str, Any] 							=						False if not self.vocab_file else True



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase ,			__UpperCamelCase = None  )->					List[int]:

          if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          UpperCAmelCase__							: Union[str, Any] 							=						[self.cls_token_id]
          UpperCAmelCase__							: Optional[int] 							=						[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase ,			__UpperCamelCase = None  )->					List[int]:
          UpperCAmelCase__							: int 							=						[self.sep_token_id]
          UpperCAmelCase__							: List[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 + sep + token_ids_a + sep  ) * [0]



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase ,			__UpperCamelCase = None  )->					Tuple[str]:
          if not self.can_save_slow_tokenizer:
               raise ValueError(
                   "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                   "tokenizer."  )

          if not os.path.isdir(__UpperCamelCase  ):
               logger.error(F"Vocabulary path ({save_directory}) should be a directory"  )
               return
          UpperCAmelCase__							: int 							=						os.path.join(
              __UpperCamelCase ,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )

          if os.path.abspath(self.vocab_file  ) != os.path.abspath(__UpperCamelCase  ):
               copyfile(self.vocab_file ,			__UpperCamelCase  )

          return (out_vocab_file,)





"""simple docstring"""




from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin







class   _lowercase						(       lowerCAmelCase_	,   lowerCAmelCase_				):


     '''simple docstring'''





     @register_to_config
     def __init__(      self ,			__UpperCamelCase = 7_68 ,			)->					Union[str, Any]:
          super().__init__()

          UpperCAmelCase__							: str 							=						nn.Parameter(torch.zeros(1 ,			__UpperCamelCase  )  )
          UpperCAmelCase__							: Optional[int] 							=						nn.Parameter(torch.ones(1 ,			__UpperCamelCase  )  )



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase = None ,			__UpperCamelCase = None ,			)->					Any:
          UpperCAmelCase__							: Dict 							=						nn.Parameter(self.mean.to(__UpperCamelCase  ).to(__UpperCamelCase  )  )
          UpperCAmelCase__							: Any 							=						nn.Parameter(self.std.to(__UpperCamelCase  ).to(__UpperCamelCase  )  )
          return self



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase  )->					Union[str, Any]:
          UpperCAmelCase__							: Dict 							=						(embeds - self.mean) * 1.0 / self.std
          return embeds



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase  )->					List[Any]:
          UpperCAmelCase__							: Any 							=						(embeds * self.std) + self.mean
          return embeds



