



"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
      from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
      A:     str										=	get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
      from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

A:     int										=	1_2_8_0_2_2
A:     Dict										=	1_2_8_0_2_8



@require_sentencepiece
class    SCREAMING_SNAKE_CASE__						(      _UpperCamelCase   ,    unittest.TestCase				):
   __lowerCAmelCase						:     Tuple		=		MaMaaaTokenizer
   __lowerCAmelCase						:     int		=		False
   __lowerCAmelCase						:     int		=		False
   __lowerCAmelCase						:     Tuple		=		True

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Tuple:





    '''simple docstring'''




    super().setUp()

    UpperCAmelCase			:      Union[str, Any]			=			["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
    UpperCAmelCase			:      Dict			=			dict(zip(_SCREAMING_SNAKE_CASE   ,  range(len(_SCREAMING_SNAKE_CASE		)		)		)		)
    UpperCAmelCase			:      Dict			=			Path(self.tmpdirname		)
    save_json(_SCREAMING_SNAKE_CASE   ,  save_dir / VOCAB_FILES_NAMES["""vocab_file"""]		)
    if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
     copyfile(_SCREAMING_SNAKE_CASE   ,  save_dir / VOCAB_FILES_NAMES["""spm_file"""]		)

    UpperCAmelCase			:      Optional[int]			=			MaMaaaTokenizer.from_pretrained(self.tmpdirname		)
    tokenizer.save_pretrained(self.tmpdirname		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  **_SCREAMING_SNAKE_CASE		)						->   Tuple:





    '''simple docstring'''




    return MaMaaaTokenizer.from_pretrained(self.tmpdirname   ,  **_SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   Optional[Any]:





    '''simple docstring'''




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

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   str:





    '''simple docstring'''




    UpperCAmelCase			:      Any			=			"</s>"
    UpperCAmelCase			:      Any			=			0

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

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Optional[int]:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			self.get_tokenizer()
    UpperCAmelCase			:      Tuple			=			list(tokenizer.get_vocab().keys()		)

    self.assertEqual(vocab_keys[0]   ,  """</s>"""		)
    self.assertEqual(vocab_keys[1]   ,  """<unk>"""		)
    self.assertEqual(vocab_keys[-1]   ,  """<s>"""		)
    self.assertEqual(len(_SCREAMING_SNAKE_CASE		)   ,  tokenizer.vocab_size + len(tokenizer.get_added_vocab()		)		)

   @unittest.skip("""Skip this test while all models are still to be uploaded."""		)
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Dict:





    '''simple docstring'''




    pass

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Optional[int]:





    '''simple docstring'''




    UpperCAmelCase			:      List[Any]			=			self.get_tokenizer()

    UpperCAmelCase			:      Optional[int]			=			tokenizer.tokenize("""This is a test"""		)
    self.assertListEqual(_SCREAMING_SNAKE_CASE   ,  ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

    self.assertListEqual(
        tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)   ,  [2, 3, 4, 5, 6]   ,  )

    UpperCAmelCase			:      Optional[Any]			=			tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]		)
    self.assertListEqual(_SCREAMING_SNAKE_CASE   ,  ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

    UpperCAmelCase			:      List[str]			=			tokenizer.convert_tokens_to_string(_SCREAMING_SNAKE_CASE		)
    self.assertEqual(_SCREAMING_SNAKE_CASE   ,  """This is a test"""		)




   @slow
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Any:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			{"input_ids": [[128022, 110108, 397, 11, 38272, 2247, 124811, 285, 18105, 1586, 207, 7, 39534, 4428, 397, 1019, 18105, 1586, 207, 7, 41337, 16786, 241, 7, 20214, 17, 125690, 10398, 7, 44378, 58069, 68342, 7798, 7343, 11, 299, 33310, 4, 158, 37350, 94077, 4569, 299, 33310, 90, 4, 52840, 290, 4, 31270, 112, 299, 682, 4, 52840, 39953, 14079, 193, 52519, 90894, 17894, 120697, 11, 40445, 551, 17, 1019, 52519, 90894, 17756, 963, 11, 40445, 480, 17, 9792, 1120, 5173, 1393, 6240, 16786, 241, 120996, 28, 1245, 1393, 118240, 11123, 1019, 93612, 2691, 10618, 98058, 120409, 1928, 279, 4, 40683, 367, 178, 207, 1019, 103, 103121, 506, 65296, 5, 2], [128022, 21217, 367, 117, 125450, 128, 719, 7, 7308, 40, 93612, 12669, 1116, 16704, 71, 17785, 3699, 15592, 35, 144, 9584, 241, 11943, 713, 950, 799, 2247, 88427, 150, 149, 118813, 120706, 1019, 106906, 81518, 28, 1224, 22799, 397, 5, 2, 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], [128022, 1658, 123311, 5155, 5578, 4722, 279, 14947, 2366, 1120, 1197, 14, 1348, 9232, 5, 2, 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]], "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, 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], [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, 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=_SCREAMING_SNAKE_CASE   ,  model_name="""facebook/m2m100_418M"""   ,  revision="""c168bae485c864188cf9aa0e4108b0b6934dc91e"""   ,  )



@require_torch
@require_sentencepiece
@require_tokenizers
class    SCREAMING_SNAKE_CASE__						(      unittest.TestCase				):
   __lowerCAmelCase						:     Tuple		=		'facebook/m2m100_418M'
   __lowerCAmelCase						:     int		=		[
       'In my opinion, there are two levels of response from the French government.',
       'NSA Affair Emphasizes Complete Lack of Debate on Intelligence',
   ]
   __lowerCAmelCase						:     str		=		[
       'Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.',
       'L\'affaire NSA souligne l\'absence totale de débat sur le renseignement',
   ]

   # fmt: off
   __lowerCAmelCase						:     Tuple		=		[EN_CODE, 593, 1_949, 115_781, 4, 71_586, 4_234, 60_633, 126_233, 432, 123_808, 15_592, 1_197, 117_132, 120_618, 5, 2]

   @classmethod
   def 			SCREAMING_SNAKE_CASE  (     cls		)						->   Union[str, Any]:





    '''simple docstring'''




    UpperCAmelCase			:      MaMaaaTokenizer			=			MaMaaaTokenizer.from_pretrained(
        cls.checkpoint_name   ,  src_lang="""en"""   ,  tgt_lang="""fr"""		)
    UpperCAmelCase			:      Optional[int]			=			1
    return cls

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Optional[Any]:





    '''simple docstring'''




    self.assertEqual(self.tokenizer.get_lang_id("""ar"""		)   ,  128006		)
    self.assertEqual(self.tokenizer.get_lang_id("""en"""		)   ,  128022		)
    self.assertEqual(self.tokenizer.get_lang_id("""ro"""		)   ,  128076		)
    self.assertEqual(self.tokenizer.get_lang_id("""mr"""		)   ,  128063		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Tuple:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			self.tokenizer.get_vocab()
    self.assertEqual(len(_SCREAMING_SNAKE_CASE		)   ,  self.tokenizer.vocab_size		)
    self.assertEqual(vocab["""<unk>"""]   ,  3		)
    self.assertIn(self.tokenizer.get_lang_token("""en"""		)   ,  _SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   str:





    '''simple docstring'''




    UpperCAmelCase			:      int			=			"en"
    UpperCAmelCase			:      Optional[Any]			=			self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
    self.assertListEqual(self.expected_src_tokens   ,  _SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Dict:





    '''simple docstring'''




    self.assertIn(_SCREAMING_SNAKE_CASE   ,  self.tokenizer.all_special_ids		)
    # fmt: off
    UpperCAmelCase			:      Optional[int]			=			[FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 14028, 136, 3286, 9706, 6, 90797, 6, 144012, 162, 88128, 30061, 5, 2]
    # fmt: on
    UpperCAmelCase			:      Any			=			self.tokenizer.decode(_SCREAMING_SNAKE_CASE   ,  skip_special_tokens=_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      Tuple			=			self.tokenizer.decode(generated_ids[1:]   ,  skip_special_tokens=_SCREAMING_SNAKE_CASE		)
    self.assertEqual(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)
    self.assertNotIn(self.tokenizer.eos_token   ,  _SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Optional[int]:





    '''simple docstring'''




    UpperCAmelCase			:      Any			=			tempfile.mkdtemp()
    UpperCAmelCase			:      List[str]			=			self.tokenizer.lang_token_to_id
    self.tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      Dict			=			MaMaaaTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE		)
    self.assertDictEqual(new_tok.lang_token_to_id   ,  _SCREAMING_SNAKE_CASE		)

   @require_torch
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   List[str]:





    '''simple docstring'''




    UpperCAmelCase			:      List[Any]			=			"en"
    UpperCAmelCase			:      Dict			=			"fr"

    UpperCAmelCase			:      Any			=			self.tokenizer(self.src_text   ,  text_target=self.tgt_text   ,  padding=_SCREAMING_SNAKE_CASE   ,  return_tensors="""pt"""		)

    UpperCAmelCase			:      str			=			shift_tokens_right(
        batch["""labels"""]   ,  self.tokenizer.pad_token_id   ,  self.tokenizer.eos_token_id		)

    for k in batch:
     UpperCAmelCase			:      Optional[Any]			=			batch[k].tolist()
    # batch = {k: v.tolist() for k,v in batch.items()}
    # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
    # batch.decoder_inputs_ids[0][0] ==
    assert batch.input_ids[1][0] == EN_CODE
    assert batch.input_ids[1][-1] == 2
    assert batch.labels[1][0] == FR_CODE
    assert batch.labels[1][-1] == 2
    assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]

   @require_torch
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   List[str]:





    '''simple docstring'''




    UpperCAmelCase			:      Dict			=			"mr"
    self.assertListEqual(self.tokenizer.prefix_tokens   ,  [self.tokenizer.get_lang_id("""mr"""		)]		)
    self.assertListEqual(self.tokenizer.suffix_tokens   ,  [self.tokenizer.eos_token_id]		)

    UpperCAmelCase			:      Optional[int]			=			"zh"
    self.assertListEqual(self.tokenizer.prefix_tokens   ,  [self.tokenizer.get_lang_id("""zh"""		)]		)
    self.assertListEqual(self.tokenizer.suffix_tokens   ,  [self.tokenizer.eos_token_id]		)

   @require_torch
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Tuple:





    '''simple docstring'''




    UpperCAmelCase			:      str			=			"mr"
    self.tokenizer._switch_to_target_mode()
    self.assertListEqual(self.tokenizer.prefix_tokens   ,  [self.tokenizer.get_lang_id("""mr"""		)]		)
    self.assertListEqual(self.tokenizer.suffix_tokens   ,  [self.tokenizer.eos_token_id]		)
    self.tokenizer._switch_to_input_mode()
    self.assertListEqual(self.tokenizer.prefix_tokens   ,  [self.tokenizer.get_lang_id(self.tokenizer.src_lang		)]		)

    UpperCAmelCase			:      str			=			"zh"
    self.tokenizer._switch_to_target_mode()
    self.assertListEqual(self.tokenizer.prefix_tokens   ,  [self.tokenizer.get_lang_id("""zh"""		)]		)
    self.assertListEqual(self.tokenizer.suffix_tokens   ,  [self.tokenizer.eos_token_id]		)
    self.tokenizer._switch_to_input_mode()
    self.assertListEqual(self.tokenizer.prefix_tokens   ,  [self.tokenizer.get_lang_id(self.tokenizer.src_lang		)]		)




   @require_torch
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   List[Any]:





    '''simple docstring'''




    UpperCAmelCase			:      str			=			self.tokenizer._build_translation_inputs("""A test"""   ,  return_tensors="""pt"""   ,  src_lang="""en"""   ,  tgt_lang="""ar"""		)

    self.assertEqual(
        nested_simplify(_SCREAMING_SNAKE_CASE		)   ,  {
            # en_XX, A, test, EOS
            """input_ids""": [[128022, 58, 4183, 2]],
            """attention_mask""": [[1, 1, 1, 1]],
            # ar_AR
            """forced_bos_token_id""": 128006,
        }   ,  )







"""simple docstring"""
import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__   ,    unittest.TestCase				):
   __lowerCAmelCase						:     List[Any]		=		TransfoXLTokenizer
   __lowerCAmelCase						:     Optional[int]		=		False
   __lowerCAmelCase						:     Optional[Any]		=		False

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   List[str]:





    '''simple docstring'''




    super().setUp()

    UpperCAmelCase			:      Optional[Any]			=			[
        """<unk>""",
        """[CLS]""",
        """[SEP]""",
        """want""",
        """unwanted""",
        """wa""",
        """un""",
        """running""",
        """,""",
        """low""",
        """l""",
    ]
    UpperCAmelCase			:      int			=			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 			SCREAMING_SNAKE_CASE  (     self   ,  **_SCREAMING_SNAKE_CASE		)						->   List[Any]:





    '''simple docstring'''




    UpperCAmelCase			:      Optional[Any]			=			True
    return TransfoXLTokenizer.from_pretrained(self.tmpdirname   ,  **_SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   List[Any]:





    '''simple docstring'''




    UpperCAmelCase			:      int			=			"""<unk> UNwanted , running"""
    UpperCAmelCase			:      Dict			=			"""<unk> unwanted, running"""
    return input_text, output_text

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Any:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			TransfoXLTokenizer(vocab_file=self.vocab_file   ,  lower_case=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      Dict			=			tokenizer.tokenize("""<unk> UNwanted , running"""		)
    self.assertListEqual(_SCREAMING_SNAKE_CASE   ,  ["""<unk>""", """unwanted""", """,""", """running"""]		)

    self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)   ,  [0, 4, 8, 7]		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Tuple:





    '''simple docstring'''




    UpperCAmelCase			:      Tuple			=			TransfoXLTokenizer(lower_case=_SCREAMING_SNAKE_CASE		)

    self.assertListEqual(
        tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """		)   ,  ["""hello""", """!""", """how""", """are""", """you""", """?"""]		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Optional[Any]:





    '''simple docstring'''




    UpperCAmelCase			:      Optional[Any]			=			TransfoXLTokenizer(lower_case=_SCREAMING_SNAKE_CASE		)

    self.assertListEqual(
        tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """		)   ,  ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    UpperCAmelCase			:      List[Any]			=			TransfoXLTokenizer(lower_case=_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      Dict			=			"""Hello (bracket) and side-scrolled [and] Henry's $5,000 with 3.34 m. What's up!?"""
    UpperCAmelCase			:      Optional[Any]			=			[
        """Hello""",
        """(""",
        """bracket""",
        """)""",
        """and""",
        """side""",
        """@-@""",
        """scrolled""",
        """[""",
        """and""",
        """]""",
        """Henry""",
        """'s""",
        """$""",
        """5""",
        """@,@""",
        """000""",
        """with""",
        """3""",
        """@.@""",
        """34""",
        """m""",
        """.""",
        """What""",
        """'s""",
        """up""",
        """!""",
        """?""",
    ]

    self.assertListEqual(tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE		)

    self.assertEqual(tokenizer.convert_tokens_to_string(_SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE		)




   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Dict:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			self.get_tokenizer()
    UpperCAmelCase			:      Tuple			=			len(_SCREAMING_SNAKE_CASE		)

    tokenizer.add_tokens(["""new1""", """new2"""]		)
    tokenizer.move_added_token("""new1"""   ,  1		)

    # Check that moved token is not copied (duplicate)
    self.assertEqual(len(_SCREAMING_SNAKE_CASE		)   ,  original_len + 2		)
    # Check that token is moved to specified id
    self.assertEqual(tokenizer.encode("""new1"""		)   ,  [1]		)
    self.assertEqual(tokenizer.decode([1]		)   ,  """new1"""		)
