code: 
  
  
  
  
  '''simple docstring'''
  
  
  
  
  
  import os
  from shutil import copyfile
  from typing import List, Optional, Tuple
  
  from tokenizers import processors
  
  from ...tokenization_utils import AddedToken, BatchEncoding
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import is_sentencepiece_available, logging
  
  
  if is_sentencepiece_available():
         from .tokenization_mbartaa import MBartaaTokenizer
  else:
         lowercase__			=	None
  
  
  lowercase__			=	logging.get_logger(__name__)
  
  lowercase__			=	{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}
  
  lowercase__			=	{
      '''vocab_file''': {
          '''facebook/mbart-large-50-one-to-many-mmt''': (
              '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'''
          ),
      },
      '''tokenizer_file''': {
          '''facebook/mbart-large-50-one-to-many-mmt''': (
              '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json'''
          ),
      },
  }
  
  lowercase__			=	{
      '''facebook/mbart-large-50-one-to-many-mmt''': 1_0_2_4,
  }
  
  # fmt: off
  lowercase__			=	['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''', '''af_ZA''', '''az_AZ''', '''bn_IN''', '''fa_IR''', '''he_IL''', '''hr_HR''', '''id_ID''', '''ka_GE''', '''km_KH''', '''mk_MK''', '''ml_IN''', '''mn_MN''', '''mr_IN''', '''pl_PL''', '''ps_AF''', '''pt_XX''', '''sv_SE''', '''sw_KE''', '''ta_IN''', '''te_IN''', '''th_TH''', '''tl_XX''', '''uk_UA''', '''ur_PK''', '''xh_ZA''', '''gl_ES''', '''sl_SI''']
  
  
  
  
  
  
  class 						lowercase     (   UpperCAmelCase_):
        __lowercase 		=  VOCAB_FILES_NAMES
        __lowercase 		=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
        __lowercase 		=  PRETRAINED_VOCAB_FILES_MAP
        __lowercase 		=  ['''input_ids''', '''attention_mask''']
        __lowercase 		=  MBartaaTokenizer
  
        __lowercase 		=  []
        __lowercase 		=  []
  
  
  
  
  
  
        def __init__(self ,  a__=None ,  a__=None ,  a__=None ,  a__=None ,  a__="</s>" ,  a__="</s>" ,  a__="<s>" ,  a__="<unk>" ,  a__="<pad>" ,  a__="<mask>" ,  **a__ ,  )       ->   Any:
           # Mask token behave like a normal word, i.e. include the space before it
           SCREAMING_SNAKE_CASE__			:				Union[str, Any]       						= AddedToken(a__ ,  lstrip=a__ ,  rstrip=a__					) if isinstance(a__ ,  a__					) else mask_token
  
           SCREAMING_SNAKE_CASE__			:				List[str]       						= kwargs.get('''additional_special_tokens''' ,  []					)
           kwargs["additional_special_tokens"] += [
               code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
           ]
  
           super().__init__(
               a__ ,  src_lang=a__ ,  tgt_lang=a__ ,  tokenizer_file=a__ ,  eos_token=a__ ,  sep_token=a__ ,  cls_token=a__ ,  unk_token=a__ ,  pad_token=a__ ,  mask_token=a__ ,  **a__ ,  )
  
           SCREAMING_SNAKE_CASE__			:				List[str]       						= vocab_file
           SCREAMING_SNAKE_CASE__			:				str       						= False if not self.vocab_file else True
  
           SCREAMING_SNAKE_CASE__			:				Tuple       						= {
               lang_code: self.convert_tokens_to_ids(a__					) for lang_code in FAIRSEQ_LANGUAGE_CODES
           }
  
           SCREAMING_SNAKE_CASE__			:				List[Any]       						= src_lang if src_lang is not None else '''en_XX'''
           SCREAMING_SNAKE_CASE__			:				Tuple       						= tgt_lang
           SCREAMING_SNAKE_CASE__			:				Optional[int]       						= self.lang_code_to_id[self._src_lang]
           self.set_src_lang_special_tokens(self._src_lang					)
  
  
  
  
  
  
        @property
        def    A__(self					)       ->   str:
           return self._src_lang
  
  
  
  
  
  
        @src_lang.setter
        def    A__(self ,  a__					)       ->   None:
           SCREAMING_SNAKE_CASE__			:				int       						= new_src_lang
           self.set_src_lang_special_tokens(self._src_lang					)
  
  
  
  
  
  
        def    A__(self ,  a__ ,  a__ = None					)       ->   List[int]:
           if token_ids_a is None:
              return self.prefix_tokens + token_ids_a + self.suffix_tokens
           # We don't expect to process pairs, but leave the pair logic for API consistency
           return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
  
  
  
  
  
  
        def    A__(self ,  a__ ,  a__ = "en_XX" ,  a__ = None ,  a__ = "ro_RO" ,  **a__ ,  )       ->   BatchEncoding:
           SCREAMING_SNAKE_CASE__			:				Dict       						= src_lang
           SCREAMING_SNAKE_CASE__			:				Tuple       						= tgt_lang
           return super().prepare_seqaseq_batch(a__ ,  a__ ,  **a__					)
  
  
  
  
  
  
        def    A__(self					)       ->   Any:
           return self.set_src_lang_special_tokens(self.src_lang					)
  
  
  
  
  
  
        def    A__(self					)       ->   Any:
           return self.set_tgt_lang_special_tokens(self.tgt_lang					)
  
  
  
  
  
  
        def    A__(self ,  a__					)       ->   None:
           SCREAMING_SNAKE_CASE__			:				int       						= self.convert_tokens_to_ids(a__					)
           SCREAMING_SNAKE_CASE__			:				Dict       						= [self.cur_lang_code_id]
           SCREAMING_SNAKE_CASE__			:				Any       						= [self.eos_token_id]
  
           SCREAMING_SNAKE_CASE__			:				List[str]       						= self.convert_ids_to_tokens(self.prefix_tokens					)
           SCREAMING_SNAKE_CASE__			:				Optional[int]       						= self.convert_ids_to_tokens(self.suffix_tokens					)
  
           SCREAMING_SNAKE_CASE__			:				Optional[int]       						= processors.TemplateProcessing(
               single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str ,  pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str ,  special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str ,  self.prefix_tokens + self.suffix_tokens					)					) ,  )
  
  
  
  
  
  
        def    A__(self ,  a__					)       ->   None:
           SCREAMING_SNAKE_CASE__			:				Optional[Any]       						= self.convert_tokens_to_ids(a__					)
           SCREAMING_SNAKE_CASE__			:				List[str]       						= [self.cur_lang_code_id]
           SCREAMING_SNAKE_CASE__			:				List[str]       						= [self.eos_token_id]
  
           SCREAMING_SNAKE_CASE__			:				Dict       						= self.convert_ids_to_tokens(self.prefix_tokens					)
           SCREAMING_SNAKE_CASE__			:				Tuple       						= self.convert_ids_to_tokens(self.suffix_tokens					)
  
           SCREAMING_SNAKE_CASE__			:				Tuple       						= processors.TemplateProcessing(
               single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str ,  pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str ,  special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str ,  self.prefix_tokens + self.suffix_tokens					)					) ,  )
  
  
  
  
  
  
        def    A__(self ,  a__ ,  a__ ,  a__ ,  a__ ,  **a__					)       ->   List[str]:
           if src_lang is None or tgt_lang is None:
              raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model'''					)
           SCREAMING_SNAKE_CASE__			:				Tuple       						= src_lang
           SCREAMING_SNAKE_CASE__			:				List[Any]       						= self(a__ ,  add_special_tokens=a__ ,  return_tensors=a__ ,  **a__					)
           SCREAMING_SNAKE_CASE__			:				Optional[int]       						= self.convert_tokens_to_ids(a__					)
           SCREAMING_SNAKE_CASE__			:				Union[str, Any]       						= tgt_lang_id
           return inputs
  
  
  
  
  
  
        def    A__(self ,  a__ ,  a__ = 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(a__					):
              logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""					)
              return
           SCREAMING_SNAKE_CASE__			:				Any       						= 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,)
  
  
style_context: 
  
  
  
  
  '''simple docstring'''
  
  
  
  
  
  import json
  from typing import List, Optional, Tuple
  
  from tokenizers import normalizers
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_splinter import SplinterTokenizer
  
  
  lowercase__			=	logging.get_logger(__name__)
  
  lowercase__			=	{'''vocab_file''': '''vocab.txt'''}
  
  lowercase__			=	{
      '''vocab_file''': {
          '''tau/splinter-base''': '''https://huggingface.co/tau/splinter-base/resolve/main/vocab.txt''',
          '''tau/splinter-base-qass''': '''https://huggingface.co/tau/splinter-base-qass/resolve/main/vocab.txt''',
          '''tau/splinter-large''': '''https://huggingface.co/tau/splinter-large/resolve/main/vocab.txt''',
          '''tau/splinter-large-qass''': '''https://huggingface.co/tau/splinter-large-qass/resolve/main/vocab.txt''',
      }
  }
  
  lowercase__			=	{
      '''tau/splinter-base''': 5_1_2,
      '''tau/splinter-base-qass''': 5_1_2,
      '''tau/splinter-large''': 5_1_2,
      '''tau/splinter-large-qass''': 5_1_2,
  }
  
  lowercase__			=	{
      '''tau/splinter-base''': {'''do_lower_case''': False},
      '''tau/splinter-base-qass''': {'''do_lower_case''': False},
      '''tau/splinter-large''': {'''do_lower_case''': False},
      '''tau/splinter-large-qass''': {'''do_lower_case''': False},
  }
  
  
  
  
  
  
  class 						lowercase     (   UpperCAmelCase_):
        __lowercase 		=  VOCAB_FILES_NAMES
        __lowercase 		=  PRETRAINED_VOCAB_FILES_MAP
        __lowercase 		=  PRETRAINED_INIT_CONFIGURATION
        __lowercase 		=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
        __lowercase 		=  SplinterTokenizer
  
  
  
  
  
  
        def __init__(self ,  a__=None ,  a__=None ,  a__=True ,  a__="[UNK]" ,  a__="[SEP]" ,  a__="[PAD]" ,  a__="[CLS]" ,  a__="[MASK]" ,  a__="[QUESTION]" ,  a__=True ,  a__=None ,  **a__ ,  )       ->   Any:
           super().__init__(
               a__ ,  tokenizer_file=a__ ,  do_lower_case=a__ ,  unk_token=a__ ,  sep_token=a__ ,  pad_token=a__ ,  cls_token=a__ ,  mask_token=a__ ,  tokenize_chinese_chars=a__ ,  strip_accents=a__ ,  additional_special_tokens=(question_token,) ,  **a__ ,  )
  
           SCREAMING_SNAKE_CASE__			:				Tuple       						= json.loads(self.backend_tokenizer.normalizer.__getstate__()					)
           if (
               pre_tok_state.get('''lowercase''' ,  a__					) != do_lower_case
               or pre_tok_state.get('''strip_accents''' ,  a__					) != strip_accents
           ):
              SCREAMING_SNAKE_CASE__			:				List[Any]       						= getattr(a__ ,  pre_tok_state.pop('''type'''					)					)
              SCREAMING_SNAKE_CASE__			:				Optional[int]       						= do_lower_case
              SCREAMING_SNAKE_CASE__			:				Optional[int]       						= strip_accents
              SCREAMING_SNAKE_CASE__			:				Optional[Any]       						= pre_tok_class(**a__					)
  
           SCREAMING_SNAKE_CASE__			:				Optional[int]       						= do_lower_case
  
  
  
  
  
  
        @property
        def    A__(self					)       ->   List[str]:
           return self.convert_tokens_to_ids(self.question_token					)
  
  
  
  
  
  
        def    A__(self ,  a__ ,  a__ = None					)       ->   List[int]:
           if token_ids_a is None:
              return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  
           SCREAMING_SNAKE_CASE__			:				Dict       						= [self.cls_token_id]
           SCREAMING_SNAKE_CASE__			:				Tuple       						= [self.sep_token_id]
           SCREAMING_SNAKE_CASE__			:				List[Any]       						= [self.question_token_id] + [self.convert_tokens_to_ids('''.'''					)]
           if self.padding_side == "right":
              # Input is question-then-context
              return cls + token_ids_a + question_suffix + sep + token_ids_a + sep
           else:
              # Input is context-then-question
              return cls + token_ids_a + sep + token_ids_a + question_suffix + sep
  
  
  
  
  
  
        def    A__(self ,  a__ ,  a__ = None					)       ->   List[int]:
           SCREAMING_SNAKE_CASE__			:				Optional[Any]       						= [self.sep_token_id]
           SCREAMING_SNAKE_CASE__			:				Any       						= [self.cls_token_id]
           SCREAMING_SNAKE_CASE__			:				Optional[Any]       						= [self.question_token_id] + [self.convert_tokens_to_ids('''.'''					)]
           if token_ids_a is None:
              return len(cls + token_ids_a + sep					) * [0]
  
           if self.padding_side == "right":
              # Input is question-then-context
              return len(cls + token_ids_a + question_suffix + sep					) * [0] + len(token_ids_a + sep					) * [1]
           else:
              # Input is context-then-question
              return len(cls + token_ids_a + sep					) * [0] + len(token_ids_a + question_suffix + sep					) * [1]
  
  
  
  
  
  
        def    A__(self ,  a__ ,  a__ = None					)       ->   Tuple[str]:
           SCREAMING_SNAKE_CASE__			:				int       						= self._tokenizer.model.save(a__ ,  name=a__					)
           return tuple(a__					)
  
  