
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_		:     str        =     None

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

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

A_		:     Union[str, Any]        =     {
    '''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_		:     List[str]        =     {
    '''moussaKam/mbarthez''': 10_24,
    '''moussaKam/barthez''': 10_24,
    '''moussaKam/barthez-orangesum-title''': 10_24,
}

A_		:     str        =     '''▁'''



class 		_lowercase		(       __a	):
   _UpperCAmelCase     	=			VOCAB_FILES_NAMES
   _UpperCAmelCase     	=			PRETRAINED_VOCAB_FILES_MAP
   _UpperCAmelCase     	=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _UpperCAmelCase     	=			['''input_ids''', '''attention_mask''']
   _UpperCAmelCase     	=			BarthezTokenizer

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


    """simple docstring"""






    a						=		AddedToken(snake_case__							,   lstrip=snake_case__							,   rstrip=snake_case__							) if isinstance(snake_case__							,   snake_case__							) else mask_token

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

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

   def 		A							(      self			:       List[Any]							,   __lowerCAmelCase			:       List[int]							,   __lowerCAmelCase			:       Optional[List[int]] = None							)       ->				Any:


    """simple docstring"""






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

   def 		A							(      self			:       Tuple							,   __lowerCAmelCase			:       List[int]							,   __lowerCAmelCase			:       Optional[List[int]] = None							)       ->				Dict:


    """simple docstring"""






    a						=		[self.sep_token_id]
    a						=		[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			:       str							,   __lowerCAmelCase			:       str							,   __lowerCAmelCase			:       Optional[str] = None							)       ->				Union[str, Any]:


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

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

    return (out_vocab_file,)






from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
     if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     from ...utils.dummy_torch_and_transformers_objects import UnCLIPImageVariationPipeline, UnCLIPPipeline
else:
     from .pipeline_unclip import UnCLIPPipeline
     from .pipeline_unclip_image_variation import UnCLIPImageVariationPipeline
     from .text_proj import UnCLIPTextProjModel

