


'''simple docstring'''

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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


a_  :				List[Any]						= logging.get_logger(__name__)

a_  :				Any						= """▁"""

a_  :				Dict						= {"""vocab_file""": """sentencepiece.bpe.model"""}

a_  :				Dict						= {
    """vocab_file""": {
        """facebook/nllb-200-distilled-600M""": (
            """https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model"""
        ),
    }
}

a_  :				str						= {
    """facebook/nllb-200-distilled-600M""": 1024,
}

# fmt: off
a_  :				List[str]						= ["""ace_Arab""", """ace_Latn""", """acm_Arab""", """acq_Arab""", """aeb_Arab""", """afr_Latn""", """ajp_Arab""", """aka_Latn""", """amh_Ethi""", """apc_Arab""", """arb_Arab""", """ars_Arab""", """ary_Arab""", """arz_Arab""", """asm_Beng""", """ast_Latn""", """awa_Deva""", """ayr_Latn""", """azb_Arab""", """azj_Latn""", """bak_Cyrl""", """bam_Latn""", """ban_Latn""", """bel_Cyrl""", """bem_Latn""", """ben_Beng""", """bho_Deva""", """bjn_Arab""", """bjn_Latn""", """bod_Tibt""", """bos_Latn""", """bug_Latn""", """bul_Cyrl""", """cat_Latn""", """ceb_Latn""", """ces_Latn""", """cjk_Latn""", """ckb_Arab""", """crh_Latn""", """cym_Latn""", """dan_Latn""", """deu_Latn""", """dik_Latn""", """dyu_Latn""", """dzo_Tibt""", """ell_Grek""", """eng_Latn""", """epo_Latn""", """est_Latn""", """eus_Latn""", """ewe_Latn""", """fao_Latn""", """pes_Arab""", """fij_Latn""", """fin_Latn""", """fon_Latn""", """fra_Latn""", """fur_Latn""", """fuv_Latn""", """gla_Latn""", """gle_Latn""", """glg_Latn""", """grn_Latn""", """guj_Gujr""", """hat_Latn""", """hau_Latn""", """heb_Hebr""", """hin_Deva""", """hne_Deva""", """hrv_Latn""", """hun_Latn""", """hye_Armn""", """ibo_Latn""", """ilo_Latn""", """ind_Latn""", """isl_Latn""", """ita_Latn""", """jav_Latn""", """jpn_Jpan""", """kab_Latn""", """kac_Latn""", """kam_Latn""", """kan_Knda""", """kas_Arab""", """kas_Deva""", """kat_Geor""", """knc_Arab""", """knc_Latn""", """kaz_Cyrl""", """kbp_Latn""", """kea_Latn""", """khm_Khmr""", """kik_Latn""", """kin_Latn""", """kir_Cyrl""", """kmb_Latn""", """kon_Latn""", """kor_Hang""", """kmr_Latn""", """lao_Laoo""", """lvs_Latn""", """lij_Latn""", """lim_Latn""", """lin_Latn""", """lit_Latn""", """lmo_Latn""", """ltg_Latn""", """ltz_Latn""", """lua_Latn""", """lug_Latn""", """luo_Latn""", """lus_Latn""", """mag_Deva""", """mai_Deva""", """mal_Mlym""", """mar_Deva""", """min_Latn""", """mkd_Cyrl""", """plt_Latn""", """mlt_Latn""", """mni_Beng""", """khk_Cyrl""", """mos_Latn""", """mri_Latn""", """zsm_Latn""", """mya_Mymr""", """nld_Latn""", """nno_Latn""", """nob_Latn""", """npi_Deva""", """nso_Latn""", """nus_Latn""", """nya_Latn""", """oci_Latn""", """gaz_Latn""", """ory_Orya""", """pag_Latn""", """pan_Guru""", """pap_Latn""", """pol_Latn""", """por_Latn""", """prs_Arab""", """pbt_Arab""", """quy_Latn""", """ron_Latn""", """run_Latn""", """rus_Cyrl""", """sag_Latn""", """san_Deva""", """sat_Beng""", """scn_Latn""", """shn_Mymr""", """sin_Sinh""", """slk_Latn""", """slv_Latn""", """smo_Latn""", """sna_Latn""", """snd_Arab""", """som_Latn""", """sot_Latn""", """spa_Latn""", """als_Latn""", """srd_Latn""", """srp_Cyrl""", """ssw_Latn""", """sun_Latn""", """swe_Latn""", """swh_Latn""", """szl_Latn""", """tam_Taml""", """tat_Cyrl""", """tel_Telu""", """tgk_Cyrl""", """tgl_Latn""", """tha_Thai""", """tir_Ethi""", """taq_Latn""", """taq_Tfng""", """tpi_Latn""", """tsn_Latn""", """tso_Latn""", """tuk_Latn""", """tum_Latn""", """tur_Latn""", """twi_Latn""", """tzm_Tfng""", """uig_Arab""", """ukr_Cyrl""", """umb_Latn""", """urd_Arab""", """uzn_Latn""", """vec_Latn""", """vie_Latn""", """war_Latn""", """wol_Latn""", """xho_Latn""", """ydd_Hebr""", """yor_Latn""", """yue_Hant""", """zho_Hans""", """zho_Hant""", """zul_Latn"""]





class      snake_case    (    lowercase			):





  """simple docstring"""




  _lowerCamelCase		    =  VOCAB_FILES_NAMES
  _lowerCamelCase		    =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _lowerCamelCase		    =  PRETRAINED_VOCAB_FILES_MAP
  _lowerCamelCase		    =  ["input_ids", "attention_mask"]

  _lowerCamelCase		    =  []
  _lowerCamelCase		    =  []






  def __init__(    self			,  UpperCamelCase			,  UpperCamelCase="<s>"			,  UpperCamelCase="</s>"			,  UpperCamelCase="</s>"			,  UpperCamelCase="<s>"			,  UpperCamelCase="<unk>"			,  UpperCamelCase="<pad>"			,  UpperCamelCase="<mask>"			,  UpperCamelCase=None			,  UpperCamelCase=None			,  UpperCamelCase=None			,  UpperCamelCase = None			,  UpperCamelCase=None			,  UpperCamelCase=False			,  **UpperCamelCase			,  ):







   """simple docstring"""
   # Mask token behave like a normal word, i.e. include the space before it
   lowerCamelCase_      =  AddedToken(UpperCamelCase			,  lstrip=UpperCamelCase			,  rstrip=UpperCamelCase     ) if isinstance(UpperCamelCase			,  UpperCamelCase     ) else mask_token

   lowerCamelCase_      =  {} if sp_model_kwargs is None else sp_model_kwargs
   lowerCamelCase_      =  legacy_behaviour

   super().__init__(
       bos_token=UpperCamelCase			,  eos_token=UpperCamelCase			,  unk_token=UpperCamelCase			,  sep_token=UpperCamelCase			,  cls_token=UpperCamelCase			,  pad_token=UpperCamelCase			,  mask_token=UpperCamelCase			,  tokenizer_file=UpperCamelCase			,  src_lang=UpperCamelCase			,  tgt_lang=UpperCamelCase			,  additional_special_tokens=UpperCamelCase			,  sp_model_kwargs=self.sp_model_kwargs			,  legacy_behaviour=UpperCamelCase			,  **UpperCamelCase			,  )

   lowerCamelCase_      =  spm.SentencePieceProcessor(**self.sp_model_kwargs     )
   self.sp_model.Load(str(UpperCamelCase     )     )
   lowerCamelCase_      =  vocab_file
   # Original fairseq vocab and spm vocab must be "aligned":
   # Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
   # -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
   # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
   # spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

   # Mimic fairseq token-to-id alignment for the first 4 token
   lowerCamelCase_      =  {"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

   # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
   lowerCamelCase_      =  1

   lowerCamelCase_      =  len(self.sp_model     )
   lowerCamelCase_      =  {
       code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(UpperCamelCase     )
   }
   lowerCamelCase_      =  {v: k for k, v in self.lang_code_to_id.items()}
   lowerCamelCase_      =  len(self.sp_model     ) + len(self.lang_code_to_id     ) + self.fairseq_offset

   self.fairseq_tokens_to_ids.update(self.lang_code_to_id     )
   lowerCamelCase_      =  {v: k for k, v in self.fairseq_tokens_to_ids.items()}
   lowerCamelCase_      =  list(self.lang_code_to_id.keys()     )

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

   lowerCamelCase_      =  src_lang if src_lang is not None else "eng_Latn"
   lowerCamelCase_      =  self.lang_code_to_id[self._src_lang]
   lowerCamelCase_      =  tgt_lang
   self.set_src_lang_special_tokens(self._src_lang     )






  def __getstate__(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  self.__dict__.copy()
   lowerCamelCase_      =  None
   lowerCamelCase_      =  self.sp_model.serialized_model_proto()
   return state






  def __setstate__(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  d

   # for backward compatibility
   if not hasattr(self			,  "sp_model_kwargs"     ):
    lowerCamelCase_      =  {}

   lowerCamelCase_      =  spm.SentencePieceProcessor(**self.sp_model_kwargs     )
   self.sp_model.LoadFromSerializedProto(self.sp_model_proto     )






  @property
  def   snake_case		(    self     ):







   """simple docstring"""
   return len(self.sp_model     ) + len(self.lang_code_to_id     ) + self.fairseq_offset + 1  # Plus 1 for the mask token






  @property
  def   snake_case		(    self     ):







   """simple docstring"""
   return self._src_lang






  @src_lang.setter
  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  new_src_lang
   self.set_src_lang_special_tokens(self._src_lang     )






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase = None			,  UpperCamelCase = False     ):







   """simple docstring"""

   if already_has_special_tokens:
    return super().get_special_tokens_mask(
        token_ids_a=UpperCamelCase			,  token_ids_a=UpperCamelCase			,  already_has_special_tokens=UpperCamelCase     )

   lowerCamelCase_      =  [1] * len(self.prefix_tokens     )
   lowerCamelCase_      =  [1] * len(self.suffix_tokens     )
   if token_ids_a is None:
    return prefix_ones + ([0] * len(UpperCamelCase     )) + suffix_ones
   return prefix_ones + ([0] * len(UpperCamelCase     )) + ([0] * len(UpperCamelCase     )) + suffix_ones






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase = 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   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase = None     ):







   """simple docstring"""
   lowerCamelCase_      =  [self.sep_token_id]
   lowerCamelCase_      =  [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   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  UpperCamelCase			,  **UpperCamelCase     ):







   """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_      =  src_lang
   lowerCamelCase_      =  self(UpperCamelCase			,  add_special_tokens=UpperCamelCase			,  return_tensors=UpperCamelCase			,  **UpperCamelCase     )
   lowerCamelCase_      =  self.convert_tokens_to_ids(UpperCamelCase     )
   lowerCamelCase_      =  tgt_lang_id
   return inputs






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  {self.convert_ids_to_tokens(UpperCamelCase     ): i for i in range(self.vocab_size     )}
   vocab.update(self.added_tokens_encoder     )
   return vocab






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   return self.sp_model.encode(UpperCamelCase			,  out_type=UpperCamelCase     )






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   if token in self.fairseq_tokens_to_ids:
    return self.fairseq_tokens_to_ids[token]
   lowerCamelCase_      =  self.sp_model.PieceToId(UpperCamelCase     )

   # Need to return unknown token if the SP model returned 0
   return spm_id + self.fairseq_offset if spm_id else self.unk_token_id






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   if index in self.fairseq_ids_to_tokens:
    return self.fairseq_ids_to_tokens[index]
   return self.sp_model.IdToPiece(index - self.fairseq_offset     )






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  "".join(UpperCamelCase     ).replace(UpperCamelCase			,  " "     ).strip()
   return out_string






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase = None     ):







   """simple docstring"""
   if not os.path.isdir(UpperCamelCase     ):
    logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''     )
    return
   lowerCamelCase_      =  os.path.join(
       UpperCamelCase			,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]     )

   if os.path.abspath(self.vocab_file     ) != os.path.abspath(UpperCamelCase     ) and os.path.isfile(self.vocab_file     ):
    copyfile(self.vocab_file			,  UpperCamelCase     )
   elif not os.path.isfile(self.vocab_file     ):
    with open(UpperCamelCase			,  "wb"     ) as fi:
     lowerCamelCase_      =  self.sp_model.serialized_model_proto()
     fi.write(UpperCamelCase     )

   return (out_vocab_file,)






  def   snake_case		(    self			,  UpperCamelCase			,  UpperCamelCase = "eng_Latn"			,  UpperCamelCase = None			,  UpperCamelCase = "fra_Latn"			,  **UpperCamelCase			,  ):







   """simple docstring"""
   lowerCamelCase_      =  src_lang
   lowerCamelCase_      =  tgt_lang
   return super().prepare_seqaseq_batch(UpperCamelCase			,  UpperCamelCase			,  **UpperCamelCase     )






  def   snake_case		(    self     ):







   """simple docstring"""
   return self.set_src_lang_special_tokens(self.src_lang     )






  def   snake_case		(    self     ):







   """simple docstring"""
   return self.set_tgt_lang_special_tokens(self.tgt_lang     )






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  self.lang_code_to_id[src_lang]
   if self.legacy_behaviour:
    lowerCamelCase_      =  []
    lowerCamelCase_      =  [self.eos_token_id, self.cur_lang_code]
   else:
    lowerCamelCase_      =  [self.cur_lang_code]
    lowerCamelCase_      =  [self.eos_token_id]







  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  self.lang_code_to_id[lang]
   if self.legacy_behaviour:
    lowerCamelCase_      =  []
    lowerCamelCase_      =  [self.eos_token_id, self.cur_lang_code]
   else:
    lowerCamelCase_      =  [self.cur_lang_code]
    lowerCamelCase_      =  [self.eos_token_id]








'''simple docstring'''





import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class     UpperCAmelCase_       (       _a		,		unittest.TestCase	):
    """simple docstring"""







    lowercase					=		GPTSanJapaneseTokenizer
    lowercase					=		False
    lowercase					=		{"do_clean_text": False, "add_prefix_space": False}




    def lowerCamelCase       (    self					:     str						):
          super().setUp()

          # fmt: off
          snake_case__  :    Optional[Any]    						=      ["""こん""", """こんに""", """にちは""", """ばんは""", """世界,㔺界""", """、""", """。""", """<BR>""", """<SP>""", """<TAB>""", """<URL>""", """<EMAIL>""", """<TEL>""", """<DATE>""", """<PRICE>""", """<BLOCK>""", """<KIGOU>""", """<U2000U2BFF>""", """<|emoji1|>""", """<unk>""", """<|bagoftoken|>""", """<|endoftext|>"""]
          # fmt: on
          snake_case__  :    int    						=      {"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
          snake_case__  :    List[Any]    						=      {"""unk_token""": """<unk>"""}

          snake_case__  :    Optional[Any]    						=      os.path.join(self.tmpdirname ,     VOCAB_FILES_NAMES["""vocab_file"""]						)
          snake_case__  :    Dict    						=      os.path.join(self.tmpdirname ,     VOCAB_FILES_NAMES["""emoji_file"""]						)
          with open(self.vocab_file ,     """w""" ,     encoding="""utf-8"""						) as vocab_writer:
                vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]						)						)
          with open(self.emoji_file ,     """w"""						) as emoji_writer:
                emoji_writer.write(json.dumps(snake_case_						)						)




    def lowerCamelCase       (    self					:     Any ,     **snake_case_					:     Union[str, Any]						):
          kwargs.update(self.special_tokens_map						)
          return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname ,     **snake_case_						)




    def lowerCamelCase       (    self					:     Any ,     snake_case_					:     str						):
          snake_case__  :    Union[str, Any]    						=      """こんにちは、世界。 \nこんばんは、㔺界。😀"""
          snake_case__  :    List[str]    						=      """こんにちは、世界。 \nこんばんは、世界。😀"""
          return input_text, output_text




    def lowerCamelCase       (    self					:     Any ,     snake_case_					:     Dict						):
          snake_case__						,				snake_case__  :    int    						=      self.get_input_output_texts(snake_case_						)
          snake_case__  :    int    						=      tokenizer.encode(snake_case_ ,     add_special_tokens=snake_case_						)
          snake_case__  :    List[str]    						=      tokenizer.decode(snake_case_ ,     clean_up_tokenization_spaces=snake_case_						)
          return text, ids




    def lowerCamelCase       (    self					:     Optional[Any]						):
          pass  # TODO add if relevant




    def lowerCamelCase       (    self					:     Union[str, Any]						):
          pass  # TODO add if relevant




    def lowerCamelCase       (    self					:     List[str]						):
          pass  # TODO add if relevant




    def lowerCamelCase       (    self					:     Dict						):
          snake_case__  :    Optional[Any]    						=      self.get_tokenizer()

          # Testing tokenization
          snake_case__  :    int    						=      """こんにちは、世界。　こんばんは、㔺界。"""
          snake_case__  :    Optional[int]    						=      ["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
          snake_case__  :    Dict    						=      tokenizer.tokenize(snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)

          # Testing conversion to ids without special tokens
          snake_case__  :    Union[str, Any]    						=      [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
          snake_case__  :    List[Any]    						=      tokenizer.convert_tokens_to_ids(snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)

          # Testing conversion to ids with special tokens
          snake_case__  :    Union[str, Any]    						=      tokens + [tokenizer.unk_token]
          snake_case__  :    Dict    						=      [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
          snake_case__  :    Any    						=      tokenizer.convert_tokens_to_ids(snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)




    def lowerCamelCase       (    self					:     Optional[Any]						):
          snake_case__  :    Union[str, Any]    						=      self.get_tokenizer()

          # Testing tokenization
          snake_case__  :    Union[str, Any]    						=      """こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。"""
          snake_case__  :    Optional[int]    						=      """こんにちは、、、、世界。こんばんは、、、、世界。"""
          snake_case__  :    Any    						=      tokenizer.encode(snake_case_						)
          snake_case__  :    int    						=      tokenizer.decode(snake_case_						)
          self.assertEqual(snake_case_ ,     snake_case_						)




    @slow
    def lowerCamelCase       (    self					:     Union[str, Any]						):
          snake_case__  :    Optional[Any]    						=      self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""						)

          # Testing tokenization
          snake_case__  :    Tuple    						=      """こんにちは、世界。"""
          snake_case__  :    Optional[Any]    						=      """こんばんは、㔺界。😀"""
          snake_case__  :    List[str]    						=      """こんにちは、世界。こんばんは、世界。😀"""
          snake_case__  :    Dict    						=      tokenizer.encode(prefix_text + input_text						)
          snake_case__  :    Dict    						=      tokenizer.encode("""""" ,     prefix_text=prefix_text + input_text						)
          snake_case__  :    int    						=      tokenizer.encode(snake_case_ ,     prefix_text=snake_case_						)
          snake_case__  :    Optional[Any]    						=      tokenizer.decode(snake_case_						)
          snake_case__  :    Union[str, Any]    						=      tokenizer.decode(snake_case_						)
          snake_case__  :    str    						=      tokenizer.decode(snake_case_						)
          self.assertEqual(snake_case_ ,     snake_case_						)
          self.assertEqual(snake_case_ ,     snake_case_						)
          self.assertEqual(snake_case_ ,     snake_case_						)




    @slow
    def lowerCamelCase       (    self					:     Union[str, Any]						):
          snake_case__  :    Optional[Any]    						=      self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""						)

          # Testing tokenization
          snake_case__  :    Dict    						=      """こんにちは、世界。"""
          snake_case__  :    Optional[int]    						=      """こんばんは、㔺界。😀"""

          snake_case__  :    Any    						=      len(tokenizer.encode(snake_case_						)						) - 2
          snake_case__  :    Optional[int]    						=      len(tokenizer.encode(snake_case_						)						) - 2

          snake_case__  :    List[str]    						=      [1] + [0] * (len_prefix + len_text + 1)
          snake_case__  :    Optional[int]    						=      [1] * (len_prefix + len_text + 1) + [0]
          snake_case__  :    int    						=      [1] + [1] * (len_prefix) + [0] * (len_text + 1)

          snake_case__  :    Any    						=      tokenizer(prefix_text + input_text						).token_type_ids
          snake_case__  :    str    						=      tokenizer("""""" ,     prefix_text=prefix_text + input_text						).token_type_ids
          snake_case__  :    Optional[Any]    						=      tokenizer(snake_case_ ,     prefix_text=snake_case_						).token_type_ids
          self.assertListEqual(snake_case_ ,     snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)




    @slow
    def lowerCamelCase       (    self					:     Optional[int]						):
          snake_case__  :    Optional[Any]    						=      self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""						)

          snake_case__  :    Union[str, Any]    						=      tokenizer.encode("""あンいワ"""						)
          snake_case__  :    int    						=      tokenizer.encode("""""" ,     prefix_text="""あンいワ"""						)
          snake_case__  :    Dict    						=      tokenizer.encode("""いワ""" ,     prefix_text="""あン"""						)

          self.assertEqual(tokenizer.decode(snake_case_						) ,     tokenizer.decode(snake_case_						)						)
          self.assertEqual(tokenizer.decode(snake_case_						) ,     tokenizer.decode(snake_case_						)						)
          self.assertNotEqual(snake_case_ ,     snake_case_						)
          self.assertNotEqual(snake_case_ ,     snake_case_						)
          self.assertEqual(x_token_a[1] ,     x_token_a[-1]						)  # SEG token
          self.assertEqual(x_token_a[1] ,     x_token_a[3]						)  # SEG token




    @slow
    def lowerCamelCase       (    self					:     Any						):
          snake_case__  :    Optional[int]    						=      self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""						)

          snake_case__  :    int    						=      [["""武田信玄""", """は、"""], ["""織田信長""", """の配下の、"""]]
          snake_case__  :    Optional[Any]    						=      tokenizer(snake_case_ ,     padding=snake_case_						)
          snake_case__  :    Tuple    						=      tokenizer.batch_encode_plus(snake_case_ ,     padding=snake_case_						)

          # fmt: off
          snake_case__  :    Optional[Any]    						=      [[35_993, 8_640, 25_948, 35_998, 30_647, 35_675, 35_999, 35_999], [35_993, 10_382, 9_868, 35_998, 30_646, 9_459, 30_646, 35_675]]
          snake_case__  :    Optional[Any]    						=      [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
          snake_case__  :    Optional[Any]    						=      [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
          # fmt: on
          self.assertListEqual(x_token.input_ids ,     snake_case_						)
          self.assertListEqual(x_token.token_type_ids ,     snake_case_						)
          self.assertListEqual(x_token.attention_mask ,     snake_case_						)
          self.assertListEqual(x_token_a.input_ids ,     snake_case_						)
          self.assertListEqual(x_token_a.token_type_ids ,     snake_case_						)
          self.assertListEqual(x_token_a.attention_mask ,     snake_case_						)




    def lowerCamelCase       (    self					:     Any						):
          # Intentionally convert some words to accommodate character fluctuations unique to Japanese
          pass




    def lowerCamelCase       (    self					:     List[str]						):
          # tokenizer has no padding token
          pass
