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:
    __lowerCAmelCase							:			List[str]				=None
  
  
  __lowerCAmelCase							:			Optional[Any]				=logging.get_logger(__name__)
  
  __lowerCAmelCase							:			Union[str, Any]				={"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}
  
  __lowerCAmelCase							:			int				={
      "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"
          ),
      },
  }
  
  __lowerCAmelCase							:			Optional[Any]				={
      "facebook/mbart-large-50-one-to-many-mmt": 1024,
  }
  
  # fmt: off
  __lowerCAmelCase							:			Tuple				=["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      UpperCAmelCase			( 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   :int		, lowercase_   :List[Any]=None		, lowercase_   :int=None		, lowercase_   :int=None		, lowercase_   :Optional[Any]=None		, lowercase_   :Optional[Any]="</s>"		, lowercase_   :Optional[Any]="</s>"		, lowercase_   :Union[str, Any]="<s>"		, lowercase_   :List[str]="<unk>"		, lowercase_   :Dict="<pad>"		, lowercase_   :Optional[Any]="<mask>"		, **lowercase_   :Dict		, )->							Dict:
       # Mask token behave like a normal word, i.e. include the space before it
       A__       =    AddedToken(lowercase_		, lstrip=lowercase_		, rstrip=lowercase_							) if isinstance(lowercase_		, lowercase_							) else mask_token
  
       A__       =    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__(
           lowercase_		, src_lang=lowercase_		, tgt_lang=lowercase_		, tokenizer_file=lowercase_		, eos_token=lowercase_		, sep_token=lowercase_		, cls_token=lowercase_		, unk_token=lowercase_		, pad_token=lowercase_		, mask_token=lowercase_		, **lowercase_		, )
  
       A__       =    vocab_file
       A__       =    False if not self.vocab_file else True
  
       A__       =    {
           lang_code: self.convert_tokens_to_ids(lowercase_							) for lang_code in FAIRSEQ_LANGUAGE_CODES
       }
  
       A__       =    src_lang if src_lang is not None else "en_XX"
       A__       =    tgt_lang
       A__       =    self.lang_code_to_id[self._src_lang]
       self.set_src_lang_special_tokens(self._src_lang							)
   @property
   def   UpperCAmelCase_							(       self   :Optional[Any]							)->							str:
       return self._src_lang
   @src_lang.setter
   def   UpperCAmelCase_							(       self   :str		, lowercase_   :str							)->							None:
       A__       =    new_src_lang
       self.set_src_lang_special_tokens(self._src_lang							)
   def   UpperCAmelCase_							(       self   :Optional[int]		, lowercase_   :List[int]		, lowercase_   :Optional[List[int]] = 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   UpperCAmelCase_							(       self   :Dict		, lowercase_   :List[str]		, lowercase_   :str = "en_XX"		, lowercase_   :Optional[List[str]] = None		, lowercase_   :str = "ro_RO"		, **lowercase_   :Optional[Any]		, )->							BatchEncoding:
       A__       =    src_lang
       A__       =    tgt_lang
       return super().prepare_seqaseq_batch(lowercase_		, lowercase_		, **lowercase_							)
   def   UpperCAmelCase_							(       self   :int							)->							Tuple:
       return self.set_src_lang_special_tokens(self.src_lang							)
   def   UpperCAmelCase_							(       self   :Any							)->							List[Any]:
       return self.set_tgt_lang_special_tokens(self.tgt_lang							)
   def   UpperCAmelCase_							(       self   :Union[str, Any]		, lowercase_   :str							)->							None:
       A__       =    self.convert_tokens_to_ids(lowercase_							)
       A__       =    [self.cur_lang_code_id]
       A__       =    [self.eos_token_id]
  
       A__       =    self.convert_ids_to_tokens(self.prefix_tokens							)
       A__       =    self.convert_ids_to_tokens(self.suffix_tokens							)
  
       A__       =    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   UpperCAmelCase_							(       self   :Optional[Any]		, lowercase_   :str							)->							None:
       A__       =    self.convert_tokens_to_ids(lowercase_							)
       A__       =    [self.cur_lang_code_id]
       A__       =    [self.eos_token_id]
  
       A__       =    self.convert_ids_to_tokens(self.prefix_tokens							)
       A__       =    self.convert_ids_to_tokens(self.suffix_tokens							)
  
       A__       =    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   UpperCAmelCase_							(       self   :int		, lowercase_   :Dict		, lowercase_   :str		, lowercase_   :Optional[str]		, lowercase_   :Optional[str]		, **lowercase_   :Dict							)->							List[Any]:
       if src_lang is None or tgt_lang is None:
           raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"							)
       A__       =    src_lang
       A__       =    self(lowercase_		, add_special_tokens=lowercase_		, return_tensors=lowercase_		, **lowercase_							)
       A__       =    self.convert_tokens_to_ids(lowercase_							)
       A__       =    tgt_lang_id
       return inputs
  
  
  
   def   UpperCAmelCase_							(       self   :Optional[int]		, lowercase_   :str		, lowercase_   :Optional[str] = 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(lowercase_							):
           logger.error(F"Vocabulary path ({save_directory}) should be a directory"							)
           return
       A__       =    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,)
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  import os
  import tempfile
  import unittest
  from typing import List
  
  from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
  from transformers.testing_utils import require_tokenizers
  from transformers.tokenization_utils import PreTrainedTokenizer
  from transformers.tokenization_utils_base import PreTrainedTokenizerBase
  
  
  
  
  
  
  @require_tokenizers
  class      UpperCAmelCase			( unittest.TestCase       ):
   __lowercase     	=       EsmTokenizer
   def   UpperCAmelCase_							(       self   :Any							)->							int:
       super().setUp()
       A__       =    tempfile.mkdtemp()
       # fmt: off
       A__       =    ["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
       # fmt: on
       A__       =    os.path.join(self.tmpdirname		, VOCAB_FILES_NAMES["vocab_file"]							)
       with open(self.vocab_file		, "w"		, encoding="utf-8"							) as vocab_writer:
           vocab_writer.write("".join([x + "\n" for x in vocab_tokens]							)							)
   def   UpperCAmelCase_							(       self   :Any		, **lowercase_   :int							)->							List[PreTrainedTokenizerBase]:
       return [self.get_tokenizer(**lowercase_							)]
   def   UpperCAmelCase_							(       self   :Any		, **lowercase_   :Dict							)->							PreTrainedTokenizer:
       return self.tokenizer_class.from_pretrained(self.tmpdirname		, **lowercase_							)
   def   UpperCAmelCase_							(       self   :int							)->							Dict:
       A__       =    self.tokenizer_class(self.vocab_file							)
  
       A__       =    tokenizer.tokenize("LAGVS"							)
       self.assertListEqual(lowercase_		, ["L", "A", "G", "V", "S"]							)
       self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_							)		, [4, 5, 6, 7, 8]							)
   def   UpperCAmelCase_							(       self   :Tuple							)->							Tuple:
       A__       =    self.tokenizer_class(self.vocab_file							)
  
       A__       =    "LAGVS"
       self.assertListEqual(tokenizer.encode(lowercase_							)		, [0, 4, 5, 6, 7, 8, 2]							)
   def   UpperCAmelCase_							(       self   :Any							)->							Tuple:
       A__       =    self.tokenizer_class(self.vocab_file							)
  
       A__       =    ["LAGVS", "WCB"]
       A__       =    tokenizer(lowercase_		, padding=lowercase_							)["input_ids"]
  
       self.assertListEqual(lowercase_		, [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]							)
   def   UpperCAmelCase_							(       self   :str							)->							Any:
       A__       =    self.tokenizer_class(self.vocab_file							)
  
       A__       =    ["LAGVS", "WCB"]
       A__       =    tokenizer(lowercase_		, padding=lowercase_							)["input_ids"]
  
       self.assertListEqual(lowercase_		, [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]]							)
  
  
  
   def   UpperCAmelCase_							(       self   :Optional[Any]							)->							List[str]:
       A__       =    self.get_tokenizers(fast=lowercase_							)
       for tokenizer in tokenizers:
           with self.subTest(F"{tokenizer.__class__.__name__}"							):
               A__       =    "<unk>"
               A__       =    "<mask>"
  
               A__       =    tokenizer.tokenize(lowercase_							)
               A__       =    tokenizer.tokenize(lowercase_							)
  
               self.assertEqual(len(lowercase_							)		, 1							)
               self.assertEqual(len(lowercase_							)		, 1							)
               self.assertEqual(token_a[0]		, lowercase_							)
               self.assertEqual(token_a[0]		, lowercase_							)
  
  
  
  