

"""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_mbart import MBartTokenizer
else:
 _lowerCAmelCase						=		None


_lowerCAmelCase						=		logging.get_logger(__name__)


_lowerCAmelCase						=		{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

_lowerCAmelCase						=		{
    "vocab_file": {
        "facebook/mbart-large-en-ro": (
            "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"
        ),
        "facebook/mbart-large-cc25": (
            "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-en-ro": "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json",
        "facebook/mbart-large-cc25": "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json",
    },
}

_lowerCAmelCase						=		{
    "facebook/mbart-large-en-ro": 1_0_2_4,
    "facebook/mbart-large-cc25": 1_0_2_4,
}

# fmt: off
_lowerCAmelCase						=		["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"]







class 	__UpperCamelCase    (    UpperCAmelCase_						):
  _UpperCAmelCase          =		VOCAB_FILES_NAMES
  _UpperCAmelCase          =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _UpperCAmelCase          =		PRETRAINED_VOCAB_FILES_MAP
  _UpperCAmelCase          =		['input_ids', 'attention_mask']
  _UpperCAmelCase          =		MBartTokenizer

  _UpperCAmelCase          =		[]
  _UpperCAmelCase          =		[]

  def __init__(		self    ,_A=None    ,_A=None    ,_A="<s>"    ,_A="</s>"    ,_A="</s>"    ,_A="<s>"    ,_A="<unk>"    ,_A="<pad>"    ,_A="<mask>"    ,_A=None    ,_A=None    ,_A=None    ,**_A    ,):
      '''simple docstring'''

      _lowerCAmelCase       :   Union[str, Any]  =    AddedToken(_lowercase    ,lstrip=_lowercase    ,rstrip=_lowercase      ) if isinstance(_lowercase    ,_lowercase      ) else mask_token

      super().__init__(
          vocab_file=_lowercase    ,tokenizer_file=_lowercase    ,bos_token=_lowercase    ,eos_token=_lowercase    ,sep_token=_lowercase    ,cls_token=_lowercase    ,unk_token=_lowercase    ,pad_token=_lowercase    ,mask_token=_lowercase    ,src_lang=_lowercase    ,tgt_lang=_lowercase    ,additional_special_tokens=_lowercase    ,**_lowercase    ,)

      _lowerCAmelCase       :   List[Any]  =    vocab_file
      _lowerCAmelCase       :   List[Any]  =    False if not self.vocab_file else True

      _lowerCAmelCase       :   Optional[int]  =    FAIRSEQ_LANGUAGE_CODES.copy()

      if additional_special_tokens is not None:
          # Only add those special tokens if they are not already there.
          _additional_special_tokens.extend(
              [t for t in additional_special_tokens if t not in _additional_special_tokens]      )

      self.add_special_tokens({'additional_special_tokens': _additional_special_tokens}      )
      _lowerCAmelCase       :   Tuple  =    {
          lang_code: self.convert_tokens_to_ids(_lowercase      ) for lang_code in FAIRSEQ_LANGUAGE_CODES
      }

      _lowerCAmelCase       :   List[Any]  =    src_lang if src_lang is not None else 'en_XX'
      _lowerCAmelCase       :   int  =    self.convert_tokens_to_ids(self._src_lang      )
      _lowerCAmelCase       :   Any  =    tgt_lang
      self.set_src_lang_special_tokens(self._src_lang      )

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self._src_lang

  @src_lang.setter
  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   int  =    new_src_lang
      self.set_src_lang_special_tokens(self._src_lang      )

  def __lowerCamelCase		(		self    ,_A    ,_A = None      ):
      '''simple docstring'''

      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 __lowerCamelCase		(		self    ,_A    ,_A = None      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Union[str, Any]  =    [self.sep_token_id]
      _lowerCAmelCase       :   int  =    [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 __lowerCamelCase		(		self    ,_A    ,_A    ,_A    ,_A    ,**_A      ):
      '''simple docstring'''

      if src_lang is None or tgt_lang is None:
          raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'      )
      _lowerCAmelCase       :   int  =    src_lang
      _lowerCAmelCase       :   Any  =    self(_lowercase    ,add_special_tokens=_lowercase    ,return_tensors=_lowercase    ,**_lowercase      )
      _lowerCAmelCase       :   Optional[int]  =    self.convert_tokens_to_ids(_lowercase      )
      _lowerCAmelCase       :   Optional[int]  =    tgt_lang_id
      return inputs

  def __lowerCamelCase		(		self    ,_A    ,_A = "en_XX"    ,_A = None    ,_A = "ro_RO"    ,**_A    ,):
      '''simple docstring'''

      _lowerCAmelCase       :   Optional[int]  =    src_lang
      _lowerCAmelCase       :   Union[str, Any]  =    tgt_lang
      return super().prepare_seqaseq_batch(_lowercase    ,_lowercase    ,**_lowercase      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.set_src_lang_special_tokens(self.src_lang      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.set_tgt_lang_special_tokens(self.tgt_lang      )

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   str  =    self.convert_tokens_to_ids(_lowercase      )
      _lowerCAmelCase       :   Any  =    []
      _lowerCAmelCase       :   Optional[int]  =    [self.eos_token_id, self.cur_lang_code]

      _lowerCAmelCase       :   Optional[int]  =    self.convert_ids_to_tokens(self.prefix_tokens      )
      _lowerCAmelCase       :   Optional[int]  =    self.convert_ids_to_tokens(self.suffix_tokens      )

      _lowerCAmelCase       :   Any  =    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 __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Union[str, Any]  =    self.convert_tokens_to_ids(_lowercase      )
      _lowerCAmelCase       :   List[str]  =    []
      _lowerCAmelCase       :   Optional[int]  =    [self.eos_token_id, self.cur_lang_code]

      _lowerCAmelCase       :   Any  =    self.convert_ids_to_tokens(self.prefix_tokens      )
      _lowerCAmelCase       :   List[Any]  =    self.convert_ids_to_tokens(self.suffix_tokens      )

      _lowerCAmelCase       :   Union[str, Any]  =    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 __lowerCamelCase		(		self    ,_A    ,_A = 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(_lowercase      ):
          logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""      )
          return
      _lowerCAmelCase       :   Tuple  =    os.path.join(
          _lowercase    ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )

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

      return (out_vocab_file,)








"""simple docstring"""






import baseaa

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    return baseaa.aaaencode(string.encode('utf-8'   )   )

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    return baseaa.aaadecode(_lowerCamelCase   ).decode('utf-8'   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()





