


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:
  UpperCAmelCase__   	=							None

UpperCAmelCase__   	=							logging.get_logger(__name__)

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

UpperCAmelCase__   	=							{
    '''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'''
        ),
    },
}

UpperCAmelCase__   	=							{
    '''moussaKam/mbarthez''': 1024,
    '''moussaKam/barthez''': 1024,
    '''moussaKam/barthez-orangesum-title''': 1024,
}

UpperCAmelCase__   	=							'''▁'''







class       lowerCamelCase__   (       lowerCAmelCase):
     SCREAMING_SNAKE_CASE__      			=			VOCAB_FILES_NAMES
     SCREAMING_SNAKE_CASE__      			=			PRETRAINED_VOCAB_FILES_MAP
     SCREAMING_SNAKE_CASE__      			=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     SCREAMING_SNAKE_CASE__      			=			['''input_ids''', '''attention_mask''']
     SCREAMING_SNAKE_CASE__      			=			BarthezTokenizer





     def __init__(self		,     UpperCAmelCase=None		,     UpperCAmelCase=None		,     UpperCAmelCase="<s>"		,     UpperCAmelCase="</s>"		,     UpperCAmelCase="</s>"		,     UpperCAmelCase="<s>"		,     UpperCAmelCase="<unk>"		,     UpperCAmelCase="<pad>"		,     UpperCAmelCase="<mask>"		,     **UpperCAmelCase		,     )     ->   List[str]:
      # Mask token behave like a normal word, i.e. include the space before it
      _lowercase							      =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		,     unk_token=UpperCAmelCase		,     sep_token=UpperCAmelCase		,     cls_token=UpperCAmelCase		,     pad_token=UpperCAmelCase		,     mask_token=UpperCAmelCase		,     **UpperCAmelCase		,     )

      _lowercase							      =vocab_file
      _lowercase							      =False if not self.vocab_file else True





     def      __A					(self		,     UpperCAmelCase		,     UpperCAmelCase = None       )     ->   List[int]:

      if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      _lowercase							      =[self.cls_token_id]
      _lowercase							      =[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep





     def      __A					(self		,     UpperCAmelCase		,     UpperCAmelCase = None       )     ->   List[int]:
      _lowercase							      =[self.sep_token_id]
      _lowercase							      =[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		,     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
      _lowercase							      =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 TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowercase          =  {
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''InstructBlipQFormerModel''',
						    '''InstructBlipPreTrainedModel''',
						    '''InstructBlipForConditionalGeneration''',
						    '''InstructBlipVisionModel''',
						]

if TYPE_CHECKING:
						from .configuration_instructblip import (
						    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    InstructBlipConfig,
						    InstructBlipQFormerConfig,
						    InstructBlipVisionConfig,
						)
						from .processing_instructblip import InstructBlipProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_instructblip import (
												    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    InstructBlipForConditionalGeneration,
												    InstructBlipPreTrainedModel,
												    InstructBlipQFormerModel,
												    InstructBlipVisionModel,
												)

else:
						import sys

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




