





"""simple docstring"""
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple

import numpy as np

from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
       from transformers.pipelines.conversational import Conversation


__UpperCamelCase     :						Optional[int]						       =  logging.get_logger(__name__)

__UpperCamelCase     :						str						       =  {'''vocab_file''': '''vocab.txt''', '''emoji_file''': '''emoji.json'''}

__UpperCamelCase     :						str						       =  {
    '''vocab_file''': {
        '''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/vocab.txt''',
    },
    '''emoji_file''': {
        '''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/emoji.json''',
    },
}

__UpperCamelCase     :						Optional[Any]						       =  {
    '''abeja/gpt-neox-japanese-2.7b''': 2048,
}

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    Any			):
 with open(_UpperCAmelCase  ,     'r'  ,     encoding='utf-8'			) as f:
  lowerCAmelCase    				= json.loads(f.read()			)

 lowerCAmelCase    				= collections.OrderedDict()
 lowerCAmelCase    				= collections.OrderedDict()
 lowerCAmelCase    				= collections.OrderedDict()
 with open(_UpperCAmelCase  ,     'r'  ,     encoding='utf-8'			) as f:
  lowerCAmelCase    				= f.readlines()
 lowerCAmelCase    				= [[t.rstrip('\n'			)] if (t == ',' or ',' not in t) else t.rstrip('\n'			).split(','			) for t in token]
 for idx, b in enumerate(_UpperCAmelCase			):
  lowerCAmelCase    				= b
  lowerCAmelCase    				= idx
  for wd in b:
   lowerCAmelCase    				= idx

 return vocab, raw_vocab, ids_to_tokens, emoji







class       a							(   a__  ):
 snake_case__             =       VOCAB_FILES_NAMES
 snake_case__             =       PRETRAINED_VOCAB_FILES_MAP
 snake_case__             =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 snake_case__             =       ['''input_ids''', '''attention_mask''']



 def __init__(     self				,       _snake_case				,       _snake_case				,       _snake_case="<|endoftext|>"				,       _snake_case="<|endoftext|>"				,       _snake_case="<|startoftext|>"				,       _snake_case="<|endoftext|>"				,       _snake_case=False				,       **_snake_case				,       ):







  """simple docstring"""






  super().__init__(
      unk_token=_snake_case				,       pad_token=_snake_case				,       bos_token=_snake_case				,       eos_token=_snake_case				,       do_clean_text=_snake_case				,       **_snake_case				,       )
  if not os.path.isfile(_snake_case     ):
   raise ValueError(
       F'Can\'t find a vocabulary file at path \'{vocab_file}\'. To load the vocabulary from a Google pretrained'
       ' model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`'     )
  if not os.path.isfile(_snake_case     ):
   raise ValueError(
       F'Can\'t find a emoji file at path \'{emoji_file}\'. To load the emoji information from a Google'
       ' pretrained model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`'     )
  lowerCAmelCase    				= do_clean_text
  lowerCAmelCase				,lowerCAmelCase				,lowerCAmelCase				,lowerCAmelCase    				= load_vocab_and_emoji(_snake_case				,       _snake_case     )
  lowerCAmelCase    				= SubWordJapaneseTokenizer(
      vocab=self.vocab				,       ids_to_tokens=self.ids_to_tokens				,       emoji=self.emoji     )



 @property
 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  return len(self.raw_vocab     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  return dict(self.raw_vocab				,       **self.added_tokens_encoder     )



 def    UpperCamelCase__  (     self				,       _snake_case     ):







  """simple docstring"""






  return self.subword_tokenizer.tokenize(_snake_case				,       clean=self.do_clean_text     )



 def    UpperCamelCase__  (     self				,       _snake_case     ):







  """simple docstring"""






  return self.vocab.get(_snake_case				,       self.vocab.get(self.unk_token     )     )



 def    UpperCamelCase__  (     self				,       _snake_case     ):







  """simple docstring"""






  return self.subword_tokenizer.convert_id_to_token(_snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case     ):







  """simple docstring"""






  lowerCAmelCase    				= ''.join(_snake_case     ).strip()
  return out_string



 def    UpperCamelCase__  (     self				,       _snake_case     ):







  """simple docstring"""






  lowerCAmelCase    				= []
  for is_user, text in conversation.iter_texts():
   input_ids.extend(self.encode(_snake_case				,       add_special_tokens=_snake_case     ) + [self.eos_token_id]     )

  if len(_snake_case     ) > self.model_max_length:
   lowerCAmelCase    				= input_ids[-self.model_max_length :]
  return input_ids



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case = None     ):







  """simple docstring"""






  lowerCAmelCase    				= 0
  if os.path.isdir(_snake_case     ):
   lowerCAmelCase    				= os.path.join(
       _snake_case				,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )
   lowerCAmelCase    				= os.path.join(
       _snake_case				,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['emoji_file']     )
  else:
   lowerCAmelCase    				= (
       (filename_prefix + '-' if filename_prefix else '') + save_directory + VOCAB_FILES_NAMES['vocab_file']
   )
   lowerCAmelCase    				= (
       (filename_prefix + '-' if filename_prefix else '') + save_directory + VOCAB_FILES_NAMES['emoji_file']
   )
  with open(_snake_case				,       'w'				,       encoding='utf-8'     ) as writer:
   for token_index, token in self.ids_to_tokens.items():
    if index != token_index:
     logger.warning(
         F'Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'
         ' Please check that the vocabulary is not corrupted!'     )
     lowerCAmelCase    				= token_index
    writer.write(','.join(_snake_case     ) + '\n'     )
    index += 1
  with open(_snake_case				,       'w'				,       encoding='utf-8'     ) as writer:
   json.dump(self.emoji				,       _snake_case     )
  return vocab_file, emoji_file







class       a							(   a__  ):



 def __init__(     self				,       _snake_case				,       _snake_case				,       _snake_case     ):







  """simple docstring"""






  lowerCAmelCase    				= vocab  # same as swe
  lowerCAmelCase    				= ids_to_tokens  # same as bpe
  lowerCAmelCase    				= emoji
  lowerCAmelCase    				= np.max([len(_snake_case     ) for w in self.vocab.keys()]     )
  lowerCAmelCase    				= re.compile(r'(https?|ftp)(:\/\/[-_\.!~*\'()a-zA-Z0-9;\/?:\@&=\+$,%#]+)'     )
  lowerCAmelCase    				= re.compile(r'[A-Za-z0-9\._+]*@[\-_0-9A-Za-z]+(\.[A-Za-z]+)*'     )
  lowerCAmelCase    				= re.compile(r'[\(]{0,1}[0-9]{2,4}[\)\-\(]{0,1}[0-9]{2,4}[\)\-]{0,1}[0-9]{3,4}'     )
  lowerCAmelCase    				= re.compile(
      r'([12]\d{3}[/\-年])*(0?[1-9]|1[0-2])[/\-月]((0?[1-9]|[12][0-9]|3[01])日?)*(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*'     )
  lowerCAmelCase    				= re.compile(
      r'(明治|大正|昭和|平成|令和|㍾|㍽|㍼|㍻|\u32ff)\d{1,2}年(0?[1-9]|1[0-2])月(0?[1-9]|[12][0-9]|3[01])日(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*'     )
  lowerCAmelCase    				= re.compile(
      r'((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*億)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*万)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*千)*(0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*(千円|万円|千万円|円|千ドル|万ドル|千万ドル|ドル|千ユーロ|万ユーロ|千万ユーロ|ユーロ)+(\(税込\)|\(税抜\)|\+tax)*'     )
  lowerCAmelCase    				= '─━│┃┄┅┆┇┈┉┊┋┌┍┎┏┐┑┒┓└┕┖┗┘┙┚┛├┝┞┟┠┡┢┣┤┥┦┧┨┩┪┫┬┭┮┯┰┱┲┳┴┵┶┷┸┹┺┻┼┽┾┿╀╁╂╃╄╅╆╇╈╉╊╋╌╍╎╏═║╒╓╔╕╖╗╘╙╚╛╜╝╞╟╠╡╢╣╤╥╦╧╨╩╪╫╬╭╮╯╰╱╲╳╴╵╶╷╸╹╺╻╼╽╾╿'
  lowerCAmelCase    				= '▀▁▂▃▄▅▆▇█▉▊▋▌▍▎▏▐░▒▓▔▕▖▗▘▙▚▛▜▝▞▟'
  lowerCAmelCase    				= str.maketrans({k: '<BLOCK>' for k in keisen + blocks}     )



 def __len__(     self     ):







  """simple docstring"""






  return len(self.ids_to_tokens     )



 def    UpperCamelCase__  (     self				,       _snake_case     ):







  """simple docstring"""






  lowerCAmelCase    				= self.content_repattera.sub('<URL>'				,       _snake_case     )
  lowerCAmelCase    				= self.content_repattera.sub('<EMAIL>'				,       _snake_case     )
  lowerCAmelCase    				= self.content_repattera.sub('<TEL>'				,       _snake_case     )
  lowerCAmelCase    				= self.content_repattera.sub('<DATE>'				,       _snake_case     )
  lowerCAmelCase    				= self.content_repattera.sub('<DATE>'				,       _snake_case     )
  lowerCAmelCase    				= self.content_repattera.sub('<PRICE>'				,       _snake_case     )
  lowerCAmelCase    				= content.translate(self.content_transa     )
  while "<BLOCK><BLOCK>" in content:
   lowerCAmelCase    				= content.replace('<BLOCK><BLOCK>'				,       '<BLOCK>'     )
  return content



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case=False     ):







  """simple docstring"""






  lowerCAmelCase    				= text.replace(' '				,       '<SP>'     )
  lowerCAmelCase    				= text.replace('　'				,       '<SP>'     )
  lowerCAmelCase    				= text.replace('\r\n'				,       '<BR>'     )
  lowerCAmelCase    				= text.replace('\n'				,       '<BR>'     )
  lowerCAmelCase    				= text.replace('\r'				,       '<BR>'     )
  lowerCAmelCase    				= text.replace('\t'				,       '<TAB>'     )
  lowerCAmelCase    				= text.replace('—'				,       'ー'     )
  lowerCAmelCase    				= text.replace('−'				,       'ー'     )
  for k, v in self.emoji["emoji"].items():
   if k in text:
    lowerCAmelCase    				= text.replace(_snake_case				,       _snake_case     )
  if clean:
   lowerCAmelCase    				= self.clean_text(_snake_case     )

  def check_simbol(_snake_case     ):
   lowerCAmelCase    				= x.encode()
   if len(_snake_case     ) == 1 and len(_snake_case     ) == 2:
    lowerCAmelCase    				= (int(e[0]     ) << 8) + int(e[1]     )
    if (
        (c >= 0xc_2a1 and c <= 0xc_2bf)
        or (c >= 0xc_780 and c <= 0xc_783)
        or (c >= 0xc_ab9 and c <= 0xc_bbf)
        or (c >= 0xc_c80 and c <= 0xc_da2)
    ):
     return True
   return False

  def checkuae(_snake_case     ):
   lowerCAmelCase    				= x.encode()
   if len(_snake_case     ) == 1 and len(_snake_case     ) == 3:
    lowerCAmelCase    				= (int(e[0]     ) << 16) + (int(e[1]     ) << 8) + int(e[2]     )
    if c >= 0xe28_080 and c <= 0xe2b_07f:
     return True
   return False

  lowerCAmelCase    				= 0
  lowerCAmelCase    				= []
  while pos < len(_snake_case     ):
   lowerCAmelCase    				= min(len(_snake_case     )				,       pos + self.maxlen + 1     ) if text[pos] == '<' else pos + 3
   lowerCAmelCase    				= []  # (token_id, token, pos)
   for e in range(_snake_case				,       _snake_case				,       -1     ):
    lowerCAmelCase    				= text[pos:e]
    if wd in self.vocab:
     if wd[0] == "<" and len(_snake_case     ) > 2:
      lowerCAmelCase    				= [(self.vocab[wd], wd, e)]
      break
     else:
      candidates.append((self.vocab[wd], wd, e)     )
   if len(_snake_case     ) > 0:
    # the smallest token_id is adopted
    lowerCAmelCase				,lowerCAmelCase				,lowerCAmelCase    				= sorted(_snake_case				,       key=lambda _snake_case     : x[0]     )[0]
    result.append(_snake_case     )
    lowerCAmelCase    				= e
   else:
    lowerCAmelCase    				= pos + 1
    lowerCAmelCase    				= text[pos:end]
    if check_simbol(_snake_case     ):
     result.append('<KIGOU>'     )
    elif checkuae(_snake_case     ):
     result.append('<U2000U2BFF>'     )
    else:
     for i in wd.encode('utf-8'     ):
      result.append('<|byte%d|>' % i     )
    lowerCAmelCase    				= end
  return result



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case="\n"     ):







  """simple docstring"""






  lowerCAmelCase    				= []
  lowerCAmelCase    				= []
  lowerCAmelCase    				= self.ids_to_tokens[index][0]
  if word[:6] == "<|byte" and word[-2:] == "|>":
   byte_tokens.append(int(word[6:-2]     )     )
  else:
   if len(_snake_case     ) > 0:
    words.append(bytearray(_snake_case     ).decode('utf-8'				,       errors='replace'     )     )
    lowerCAmelCase    				= []
   if word[:7] == "<|emoji" and word[-2:] == "|>":
    words.append(self.emoji['emoji_inv'][word]     )
   elif word == "<SP>":
    words.append(' '     )
   elif word == "<BR>":
    words.append(_snake_case     )
   elif word == "<TAB>":
    words.append('\t'     )
   elif word == "<BLOCK>":
    words.append('▀'     )
   elif word == "<KIGOU>":
    words.append('ǀ'     )
   elif word == "<U2000U2BFF>":
    words.append('‖'     )
   else:
    words.append(_snake_case     )
  if len(_snake_case     ) > 0:
   words.append(bytearray(_snake_case     ).decode('utf-8'				,       errors='replace'     )     )
  lowerCAmelCase    				= ''.join(_snake_case     )
  return text











'''simple docstring'''


import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
 from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase_      :  Optional[Any]				     =  get_tests_dir('fixtures/test_sentencepiece.model')

lowerCAmelCase_      :  int				     =  {'target_lang': 'fi', 'source_lang': 'en'}
lowerCAmelCase_      :  str				     =  '>>zh<<'
lowerCAmelCase_      :  List[str]				     =  'Helsinki-NLP/'

if is_torch_available():
 lowerCAmelCase_      :  Dict				     =  'pt'
elif is_tf_available():
 lowerCAmelCase_      :  Union[str, Any]				     =  'tf'
else:
 lowerCAmelCase_      :  int				     =  'jax'







@require_sentencepiece
class      SCREAMING_SNAKE_CASE    (						snake_case_							,      unittest.TestCase				):
      __magic_name__  :       Dict   							=					MarianTokenizer
      __magic_name__  :       Any   							=					False
      __magic_name__  :       str   							=					True






      def 							lowercase_						( self   :  Any       ):


           '''simple docstring'''

           super().setUp()
           a_     :							Optional[Any]     						=  ["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
           a_     :							Optional[int]     						=  dict(zip(lowercase__						,						range(len(lowercase__       )       )       )       )
           a_     :							List[str]     						=  Path(self.tmpdirname       )
           save_json(lowercase__						,						save_dir / VOCAB_FILES_NAMES["""vocab"""]       )
           save_json(lowercase__						,						save_dir / VOCAB_FILES_NAMES["""tokenizer_config_file"""]       )
           if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
                copyfile(lowercase__						,						save_dir / VOCAB_FILES_NAMES["""source_spm"""]       )
                copyfile(lowercase__						,						save_dir / VOCAB_FILES_NAMES["""target_spm"""]       )

           a_     :							Dict     						=  MarianTokenizer.from_pretrained(self.tmpdirname       )
           tokenizer.save_pretrained(self.tmpdirname       )






      def 							lowercase_						( self   :  Tuple						,						**lowercase__   :  int       ):


           '''simple docstring'''

           return MarianTokenizer.from_pretrained(self.tmpdirname						,						**lowercase__       )






      def 							lowercase_						( self   :  int						,						lowercase__   :  int       ):


           '''simple docstring'''

           return (
               "This is a test",
               "This is a test",
           )






      def 							lowercase_						( self   :  List[str]       ):


           '''simple docstring'''

           a_     :							Optional[int]     						=  """</s>"""
           a_     :							Optional[int]     						=  0

           self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase__       )						,						lowercase__       )
           self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase__       )						,						lowercase__       )






      def 							lowercase_						( self   :  Tuple       ):


           '''simple docstring'''

           a_     :							Optional[int]     						=  list(self.get_tokenizer().get_vocab().keys()       )

           self.assertEqual(vocab_keys[0]						,						"""</s>"""       )
           self.assertEqual(vocab_keys[1]						,						"""<unk>"""       )
           self.assertEqual(vocab_keys[-1]						,						"""<pad>"""       )
           self.assertEqual(len(lowercase__       )						,						9       )






      def 							lowercase_						( self   :  List[Any]       ):


           '''simple docstring'''

           self.assertEqual(self.get_tokenizer().vocab_size						,						9       )






      def 							lowercase_						( self   :  str       ):


           '''simple docstring'''

           a_     :							str     						=  MarianTokenizer.from_pretrained(F"{ORG_NAME}opus-mt-en-de"       )
           a_     :							Any     						=  en_de_tokenizer(["""I am a small frog"""]						,						return_tensors=lowercase__       )
           self.assertIsInstance(lowercase__						,						lowercase__       )
           a_     :							str     						=  [38, 121, 14, 697, 3_8848, 0]
           self.assertListEqual(lowercase__						,						batch.input_ids[0]       )

           a_     :							Union[str, Any]     						=  tempfile.mkdtemp()
           en_de_tokenizer.save_pretrained(lowercase__       )
           a_     :							Union[str, Any]     						=  [x.name for x in Path(lowercase__       ).glob("""*"""       )]
           self.assertIn("""source.spm"""						,						lowercase__       )
           MarianTokenizer.from_pretrained(lowercase__       )






      def 							lowercase_						( self   :  str       ):


           '''simple docstring'''

           a_     :							int     						=  self.get_tokenizer()

           a_     :							Dict     						=  tok(
               ["""I am a small frog""" * 1000, """I am a small frog"""]						,						padding=lowercase__						,						truncation=lowercase__						,						return_tensors=lowercase__       )
           self.assertIsInstance(lowercase__						,						lowercase__       )
           self.assertEqual(batch.input_ids.shape						,						(2, 512)       )






      def 							lowercase_						( self   :  Optional[Any]       ):


           '''simple docstring'''

           a_     :							List[str]     						=  self.get_tokenizer()
           a_     :							Dict     						=  tok(["""I am a tiny frog""", """I am a small frog"""]						,						padding=lowercase__						,						return_tensors=lowercase__       )
           self.assertIsInstance(lowercase__						,						lowercase__       )
           self.assertEqual(batch_smaller.input_ids.shape						,						(2, 10)       )






      @slow
      def 							lowercase_						( self   :  List[Any]       ):


           '''simple docstring'''

           a_     :							Optional[int]     						=  {"""input_ids""": [[4_3495, 462, 20, 4_2164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 3_8999, 6, 8, 464, 132, 1703, 492, 13, 4669, 3_7867, 13, 7525, 27, 1593, 988, 13, 3_3972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 1_2338, 2, 1_3958, 387, 2, 3629, 6953, 188, 2900, 2, 1_3958, 8011, 1_1501, 23, 8460, 4073, 3_4009, 20, 435, 1_1439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 3_7867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 2_6453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 1_0767, 6, 316, 304, 4239, 3, 0], [148, 1_5722, 19, 1839, 12, 1350, 13, 2_2327, 5082, 5418, 4_7567, 3_5938, 59, 318, 1_9552, 108, 2183, 54, 1_4976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 1_9088, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100], [36, 6395, 1_2570, 3_9147, 1_1597, 6, 266, 4, 4_5405, 7296, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
           # fmt: on

           self.tokenizer_integration_test_util(
               expected_encoding=lowercase__						,						model_name="""Helsinki-NLP/opus-mt-en-de"""						,						revision="""1a8c2263da11e68e50938f97e10cd57820bd504c"""						,						decode_kwargs={"""use_source_tokenizer""": True}						,						)






      def 							lowercase_						( self   :  int       ):


           '''simple docstring'''

           a_     :							Tuple     						=  MarianTokenizer.from_pretrained("""hf-internal-testing/test-marian-two-vocabs"""       )

           a_     :							Tuple     						=  """Tämä on testi"""
           a_     :							Union[str, Any]     						=  """This is a test"""

           a_     :							Union[str, Any]     						=  [76, 7, 2047, 2]
           a_     :							Optional[int]     						=  [69, 12, 11, 940, 2]

           a_     :							Optional[Any]     						=  tokenizer(lowercase__       ).input_ids
           self.assertListEqual(lowercase__						,						lowercase__       )

           a_     :							Optional[int]     						=  tokenizer(text_target=lowercase__       ).input_ids
           self.assertListEqual(lowercase__						,						lowercase__       )

           a_     :							str     						=  tokenizer.decode(lowercase__						,						skip_special_tokens=lowercase__       )
           self.assertEqual(lowercase__						,						lowercase__       )
