




'''simple docstring'''



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

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


if is_sentencepiece_available():
     from .tokenization_xglm import XGLMTokenizer
else:
     UpperCAmelCase_       :  int      =		None


UpperCAmelCase_       :  Optional[Any]      =		logging.get_logger(__name__)

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

UpperCAmelCase_       :  Tuple      =		{
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json''',
    },
}

UpperCAmelCase_       :  Optional[Any]      =		{
    '''facebook/xglm-564M''': 2_0_4_8,
}





class     lowerCAmelCase   ( __lowerCAmelCase):
       __lowercase  :      Dict        =			VOCAB_FILES_NAMES
       __lowercase  :      Tuple        =			PRETRAINED_VOCAB_FILES_MAP
       __lowercase  :      List[Any]        =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __lowercase  :      str        =			['''input_ids''', '''attention_mask''']
       __lowercase  :      Optional[int]        =			XGLMTokenizer


       def __init__(   self    ,  __SCREAMING_SNAKE_CASE=None    ,  __SCREAMING_SNAKE_CASE=None    ,  __SCREAMING_SNAKE_CASE="<s>"    ,  __SCREAMING_SNAKE_CASE="</s>"    ,  __SCREAMING_SNAKE_CASE="</s>"    ,  __SCREAMING_SNAKE_CASE="<s>"    ,  __SCREAMING_SNAKE_CASE="<unk>"    ,  __SCREAMING_SNAKE_CASE="<pad>"    ,  **__SCREAMING_SNAKE_CASE    ,  )      ->  List[str]:



            '''simple docstring'''




            __snake_case    					=  7
            __snake_case    					=  [F'''<madeupword{i}>''' for i in range(self.num_madeup_words  )]

            __snake_case    					=  kwargs.get('''additional_special_tokens'''    ,  []  )
            kwargs["additional_special_tokens"] += [
                word for word in madeup_words if word not in kwargs["additional_special_tokens"]
            ]

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

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


       def       lowerCAmelCase      (   self    ,  __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE = None  )      ->  List[int]:



            '''simple docstring'''




            if token_ids_a is None:
                 return [self.sep_token_id] + token_ids_a
            __snake_case    					=  [self.sep_token_id]
            return sep + token_ids_a + sep + sep + token_ids_a


       def       lowerCAmelCase      (   self    ,  __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE = None  )      ->  List[int]:



            '''simple docstring'''




            __snake_case    					=  [self.sep_token_id]

            if token_ids_a is None:
                 return len(sep + token_ids_a  ) * [0]
            return len(sep + token_ids_a + sep + sep + token_ids_a  ) * [0]




       def       lowerCAmelCase      (   self    ,  __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE = None  )      ->  Tuple[str]:



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

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

            return (out_vocab_file,)












'''simple docstring'''



from transformers import ProcessorMixin





class     lowerCAmelCase   ( __lowerCAmelCase):
       __lowercase  :      Union[str, Any]        =			'''AutoFeatureExtractor'''
       __lowercase  :      List[Any]        =			'''AutoTokenizer'''






