




"""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_barthez import BarthezTokenizer
else:
     A_						=				None

A_						=				logging.get_logger(__name__)

A_						=				{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

A_						=				{
    '''vocab_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json'''
        ),
    },
}

A_						=				{
    '''moussaKam/mbarthez''': 10_24,
    '''moussaKam/barthez''': 10_24,
    '''moussaKam/barthez-orangesum-title''': 10_24,
}

A_						=				'''▁'''






class 					lowercase(     __a ):







 '''simple docstring'''





 lowercase__ 					=					VOCAB_FILES_NAMES
 lowercase__ 					=					PRETRAINED_VOCAB_FILES_MAP
 lowercase__ 					=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase__ 					=					["input_ids", "attention_mask"]
 lowercase__ 					=					BarthezTokenizer


 def __init__(				self:		Tuple,      a_:		Union[str, Any]=None,      a_:		Dict=None,      a_:		Tuple="<s>",      a_:		int="</s>",      a_:		Dict="</s>",      a_:		Dict="<s>",      a_:		Any="<unk>",      a_:		Tuple="<pad>",      a_:		Tuple="<mask>",      **a_:		Tuple,      ):




   '''simple docstring'''



   _snake_case							:		List[Any]								=  AddedToken(a_,      lstrip=a_,      rstrip=a_		) if isinstance(a_,      a_		) else mask_token

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

   _snake_case							:		Optional[int]								=  vocab_file
   _snake_case							:		List[str]								=  False if not self.vocab_file else True


 def  UpperCamelCase_   (				self:		Optional[Any],      a_:		List[int],      a_:		Optional[List[int]] = None		):




   '''simple docstring'''



   if token_ids_a is None:
     return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
   _snake_case							:		Optional[int]								=  [self.cls_token_id]
   _snake_case							:		Dict								=  [self.sep_token_id]
   return cls + token_ids_a + sep + sep + token_ids_a + sep


 def  UpperCamelCase_   (				self:		Tuple,      a_:		List[int],      a_:		Optional[List[int]] = None		):




   '''simple docstring'''



   _snake_case							:		str								=  [self.sep_token_id]
   _snake_case							:		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 + sep + token_ids_a + sep		) * [0]


 def  UpperCamelCase_   (				self:		List[Any],      a_:		str,      a_:		Optional[str] = None		):




   '''simple docstring'''



   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(a_		):
     logger.error(f"Vocabulary path ({save_directory}) should be a directory"		)
     return
   _snake_case							:		int								=  os.path.join(
       a_,      (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]		)

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

   return (out_vocab_file,)









'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase					:     Optional[Any]												={
    '''configuration_nllb_moe''': [
        '''NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''NllbMoeConfig''',
    ]
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase					:     Tuple												=[
     '''NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''NllbMoeForConditionalGeneration''',
     '''NllbMoeModel''',
     '''NllbMoePreTrainedModel''',
     '''NllbMoeTop2Router''',
     '''NllbMoeSparseMLP''',
 ]


if TYPE_CHECKING:
 from .configuration_nllb_moe import (
     NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
     NllbMoeConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_nllb_moe import (
      NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
      NllbMoeForConditionalGeneration,
      NllbMoeModel,
      NllbMoePreTrainedModel,
      NllbMoeSparseMLP,
      NllbMoeTopaRouter,
  )


else:
 import sys

 lowerCAmelCase					:     Tuple												=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


