






'''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_nllb import NllbTokenizer
else:
  a_					= None


a_					= logging.get_logger(__name__)


a_					= {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

a_					= {
    'vocab_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/tokenizer.json'
        ),
    },
}

a_					= {
    'facebook/nllb-large-en-ro': 1_0_2_4,
    'facebook/nllb-200-distilled-600M': 1_0_2_4,
}

# fmt: off
a_					= ['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      __SCREAMING_SNAKE_CASE      (			lowerCamelCase				):
 snake_case_  							=							VOCAB_FILES_NAMES
 snake_case_  							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 snake_case_  							=							PRETRAINED_VOCAB_FILES_MAP
 snake_case_  							=							["""input_ids""", """attention_mask"""]
 snake_case_  							=							NllbTokenizer

 snake_case_  							=							[]
 snake_case_  							=							[]




 def __init__(      self	:							Any					,      __lowercase	:							int=None					,      __lowercase	:							str=None					,      __lowercase	:							str="<s>"					,      __lowercase	:							Any="</s>"					,      __lowercase	:							List[str]="</s>"					,      __lowercase	:							Any="<s>"					,      __lowercase	:							Optional[int]="<unk>"					,      __lowercase	:							List[Any]="<pad>"					,      __lowercase	:							Any="<mask>"					,      __lowercase	:							Any=None					,      __lowercase	:							str=None					,      __lowercase	:							Union[str, Any]=None					,      __lowercase	:							str=False					,      **__lowercase	:							List[str]					,      )	->						Optional[Any]:
       # Mask token behave like a normal word, i.e. include the space before it
       SCREAMING_SNAKE_CASE__     :				List[Any]									=AddedToken(__lowercase					,      lstrip=__lowercase					,      rstrip=__lowercase      ) if isinstance(__lowercase					,      __lowercase      ) else mask_token
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=legacy_behaviour
       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					,      legacy_behaviour=__lowercase					,      **__lowercase					,      )

       SCREAMING_SNAKE_CASE__     :				List[str]									=vocab_file
       SCREAMING_SNAKE_CASE__     :				str									=False if not self.vocab_file else True

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=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}      )
       SCREAMING_SNAKE_CASE__     :				List[Any]									={
           lang_code: self.convert_tokens_to_ids(__lowercase      ) for lang_code in FAIRSEQ_LANGUAGE_CODES
       }

       SCREAMING_SNAKE_CASE__     :				Optional[int]									=src_lang if src_lang is not None else '''eng_Latn'''
       SCREAMING_SNAKE_CASE__     :				Dict									=self.convert_tokens_to_ids(self._src_lang      )
       SCREAMING_SNAKE_CASE__     :				List[str]									=tgt_lang
       self.set_src_lang_special_tokens(self._src_lang      )




 @property
 def      __magic_name__	(      self	:							Optional[int]      )	->						str:
       return self._src_lang




 @src_lang.setter
 def      __magic_name__	(      self	:							List[Any]					,      __lowercase	:							str      )	->						None:
       SCREAMING_SNAKE_CASE__     :				List[Any]									=new_src_lang
       self.set_src_lang_special_tokens(self._src_lang      )




 def      __magic_name__	(      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      __magic_name__	(      self	:							Dict					,      __lowercase	:							List[int]					,      __lowercase	:							Optional[List[int]] = None      )	->						List[int]:
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=[self.sep_token_id]
       SCREAMING_SNAKE_CASE__     :				List[Any]									=[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      __magic_name__	(      self	:							Any					,      __lowercase	:							str					,      __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'''      )
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=src_lang
       SCREAMING_SNAKE_CASE__     :				Any									=self(__lowercase					,      add_special_tokens=__lowercase					,      return_tensors=__lowercase					,      **__lowercase      )
       SCREAMING_SNAKE_CASE__     :				int									=self.convert_tokens_to_ids(__lowercase      )
       SCREAMING_SNAKE_CASE__     :				List[Any]									=tgt_lang_id
       return inputs




 def      __magic_name__	(      self	:							int					,      __lowercase	:							List[str]					,      __lowercase	:							str = "eng_Latn"					,      __lowercase	:							Optional[List[str]] = None					,      __lowercase	:							str = "fra_Latn"					,      **__lowercase	:							Optional[Any]					,      )	->						BatchEncoding:
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=src_lang
       SCREAMING_SNAKE_CASE__     :				str									=tgt_lang
       return super().prepare_seqaseq_batch(__lowercase					,      __lowercase					,      **__lowercase      )




 def      __magic_name__	(      self	:							int      )	->						Any:
       return self.set_src_lang_special_tokens(self.src_lang      )




 def      __magic_name__	(      self	:							List[str]      )	->						Union[str, Any]:
       return self.set_tgt_lang_special_tokens(self.tgt_lang      )




 def      __magic_name__	(      self	:							str					,      __lowercase	:							int      )	->						None:
       SCREAMING_SNAKE_CASE__     :				List[str]									=self.convert_tokens_to_ids(__lowercase      )

       if self.legacy_behaviour:
             SCREAMING_SNAKE_CASE__     :				List[Any]									=[]
             SCREAMING_SNAKE_CASE__     :				Optional[int]									=[self.eos_token_id, self.cur_lang_code]
       else:
             SCREAMING_SNAKE_CASE__     :				Optional[Any]									=[self.cur_lang_code]
             SCREAMING_SNAKE_CASE__     :				Tuple									=[self.eos_token_id]

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

       SCREAMING_SNAKE_CASE__     :				Dict									=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      __magic_name__	(      self	:							Optional[Any]					,      __lowercase	:							str      )	->						None:
       SCREAMING_SNAKE_CASE__     :				List[str]									=self.convert_tokens_to_ids(__lowercase      )
       if self.legacy_behaviour:
             SCREAMING_SNAKE_CASE__     :				Any									=[]
             SCREAMING_SNAKE_CASE__     :				Optional[int]									=[self.eos_token_id, self.cur_lang_code]
       else:
             SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=[self.cur_lang_code]
             SCREAMING_SNAKE_CASE__     :				Optional[Any]									=[self.eos_token_id]

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

       SCREAMING_SNAKE_CASE__     :				Optional[int]									=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      __magic_name__	(      self	:							Dict					,      __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
       SCREAMING_SNAKE_CASE__     :				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 unittest

from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken

from ...test_tokenization_common import TokenizerTesterMixin


a_					= get_tests_dir('fixtures/test_sentencepiece_bpe_char.model')






@require_sentencepiece
@require_tokenizers
class      __SCREAMING_SNAKE_CASE      (			lowerCamelCase	,				unittest.TestCase				):
 snake_case_  							=							SpeechTaTokenizer
 snake_case_  							=							False
 snake_case_  							=							True




 def      __magic_name__	(      self	:							int      )	->						Any:
       super().setUp()

       # We have a SentencePiece fixture for testing
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=SpeechTaTokenizer(__lowercase      )

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=AddedToken('''<mask>'''					,      lstrip=__lowercase					,      rstrip=__lowercase      )
       SCREAMING_SNAKE_CASE__     :				List[Any]									=mask_token
       tokenizer.add_special_tokens({'''mask_token''': mask_token}      )
       tokenizer.add_tokens(['''<ctc_blank>''']      )

       tokenizer.save_pretrained(self.tmpdirname      )




 def      __magic_name__	(      self	:							Dict					,      __lowercase	:							int      )	->						Optional[int]:
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									='''this is a test'''
       SCREAMING_SNAKE_CASE__     :				int									='''this is a test'''
       return input_text, output_text




 def      __magic_name__	(      self	:							List[Any]					,      __lowercase	:							int					,      __lowercase	:							Optional[Any]=False					,      __lowercase	:							Union[str, Any]=20					,      __lowercase	:							Any=5      )	->						Any:
       SCREAMING_SNAKE_CASE__		,	SCREAMING_SNAKE_CASE__     :				int									=self.get_input_output_texts(__lowercase      )
       SCREAMING_SNAKE_CASE__     :				str									=tokenizer.encode(__lowercase					,      add_special_tokens=__lowercase      )
       SCREAMING_SNAKE_CASE__     :				str									=tokenizer.decode(__lowercase					,      clean_up_tokenization_spaces=__lowercase      )
       return text, ids




 def      __magic_name__	(      self	:							Dict      )	->						str:
       SCREAMING_SNAKE_CASE__     :				Optional[int]									='''<pad>'''
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=1

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




 def      __magic_name__	(      self	:							Tuple      )	->						List[str]:
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=list(self.get_tokenizer().get_vocab().keys()      )

       self.assertEqual(vocab_keys[0]					,      '''<s>'''      )
       self.assertEqual(vocab_keys[1]					,      '''<pad>'''      )
       self.assertEqual(vocab_keys[-4]					,      '''œ'''      )
       self.assertEqual(vocab_keys[-2]					,      '''<mask>'''      )
       self.assertEqual(vocab_keys[-1]					,      '''<ctc_blank>'''      )
       self.assertEqual(len(__lowercase      )					,      81      )




 def      __magic_name__	(      self	:							Dict      )	->						List[str]:
       self.assertEqual(self.get_tokenizer().vocab_size					,      79      )




 def      __magic_name__	(      self	:							Optional[Any]      )	->						str:
       SCREAMING_SNAKE_CASE__     :				str									=self.get_tokenizers(do_lower_case=__lowercase      )
       for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"      ):
                   SCREAMING_SNAKE_CASE__     :				Tuple									=tokenizer.vocab_size
                   SCREAMING_SNAKE_CASE__     :				Any									=len(__lowercase      )

                   self.assertNotEqual(__lowercase					,      0      )

                   # We usually have added tokens from the start in tests because our vocab fixtures are
                   # smaller than the original vocabs - let's not assert this
                   # self.assertEqual(vocab_size, all_size)

                   SCREAMING_SNAKE_CASE__     :				int									=['''aaaaa bbbbbb''', '''cccccccccdddddddd''']
                   SCREAMING_SNAKE_CASE__     :				List[str]									=tokenizer.add_tokens(__lowercase      )
                   SCREAMING_SNAKE_CASE__     :				List[str]									=tokenizer.vocab_size
                   SCREAMING_SNAKE_CASE__     :				Optional[int]									=len(__lowercase      )

                   self.assertNotEqual(__lowercase					,      0      )
                   self.assertEqual(__lowercase					,      __lowercase      )
                   self.assertEqual(__lowercase					,      len(__lowercase      )      )
                   self.assertEqual(__lowercase					,      all_size + len(__lowercase      )      )

                   SCREAMING_SNAKE_CASE__     :				Tuple									=tokenizer.encode('''aaaaa bbbbbb low cccccccccdddddddd l'''					,      add_special_tokens=__lowercase      )

                   self.assertGreaterEqual(len(__lowercase      )					,      4      )
                   self.assertGreater(tokens[0]					,      tokenizer.vocab_size - 1      )
                   self.assertGreater(tokens[-3]					,      tokenizer.vocab_size - 1      )

                   SCREAMING_SNAKE_CASE__     :				str									={'''eos_token''': '''>>>>|||<||<<|<<''', '''pad_token''': '''<<<<<|||>|>>>>|>'''}
                   SCREAMING_SNAKE_CASE__     :				int									=tokenizer.add_special_tokens(__lowercase      )
                   SCREAMING_SNAKE_CASE__     :				List[str]									=tokenizer.vocab_size
                   SCREAMING_SNAKE_CASE__     :				int									=len(__lowercase      )

                   self.assertNotEqual(__lowercase					,      0      )
                   self.assertEqual(__lowercase					,      __lowercase      )
                   self.assertEqual(__lowercase					,      len(__lowercase      )      )
                   self.assertEqual(__lowercase					,      all_size_a + len(__lowercase      )      )

                   SCREAMING_SNAKE_CASE__     :				List[Any]									=tokenizer.encode(
                       '''>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l'''					,      add_special_tokens=__lowercase      )

                   self.assertGreaterEqual(len(__lowercase      )					,      6      )
                   self.assertGreater(tokens[0]					,      tokenizer.vocab_size - 1      )
                   self.assertGreater(tokens[0]					,      tokens[1]      )
                   self.assertGreater(tokens[-3]					,      tokenizer.vocab_size - 1      )
                   self.assertGreater(tokens[-3]					,      tokens[-4]      )
                   self.assertEqual(tokens[0]					,      tokenizer.eos_token_id      )
                   self.assertEqual(tokens[-3]					,      tokenizer.pad_token_id      )




 def      __magic_name__	(      self	:							Optional[Any]      )	->						Any:
       pass




 def      __magic_name__	(      self	:							List[str]      )	->						List[Any]:
       pass




 def      __magic_name__	(      self	:							Dict      )	->						List[Any]:
       SCREAMING_SNAKE_CASE__     :				Dict									=self.get_tokenizer()

       SCREAMING_SNAKE_CASE__     :				Optional[int]									=tokenizer.tokenize('''This is a test'''      )
       # fmt: off
       self.assertListEqual(__lowercase					,      [SPIECE_UNDERLINE, '''T''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''a''', SPIECE_UNDERLINE, '''t''', '''e''', '''s''', '''t''']      )
       # fmt: on

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(__lowercase      )					,      [4, 32, 11, 10, 12, 4, 10, 12, 4, 7, 4, 6, 5, 12, 6]					,      )

       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=tokenizer.tokenize('''I was born in 92000, and this is falsé.'''      )
       self.assertListEqual(
           __lowercase					,      [SPIECE_UNDERLINE, '''I''', SPIECE_UNDERLINE, '''w''', '''a''', '''s''', SPIECE_UNDERLINE, '''b''', '''o''', '''r''', '''n''', SPIECE_UNDERLINE, '''i''', '''n''', SPIECE_UNDERLINE, '''92000''', ''',''', SPIECE_UNDERLINE, '''a''', '''n''', '''d''', SPIECE_UNDERLINE, '''t''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''f''', '''a''', '''l''', '''s''', '''é''', '''.''']      )

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=tokenizer.convert_tokens_to_ids(__lowercase      )
       # fmt: off
       self.assertListEqual(__lowercase					,      [4, 30, 4, 20, 7, 12, 4, 25, 8, 13, 9, 4, 10, 9, 4, 3, 23, 4, 7, 9, 14, 4, 6, 11, 10, 12, 4, 10, 12, 4, 19, 7, 15, 12, 73, 26]      )
       # fmt: on

       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=tokenizer.convert_ids_to_tokens(__lowercase      )
       self.assertListEqual(
           __lowercase					,      [SPIECE_UNDERLINE, '''I''', SPIECE_UNDERLINE, '''w''', '''a''', '''s''', SPIECE_UNDERLINE, '''b''', '''o''', '''r''', '''n''', SPIECE_UNDERLINE, '''i''', '''n''', SPIECE_UNDERLINE, '''<unk>''', ''',''', SPIECE_UNDERLINE, '''a''', '''n''', '''d''', SPIECE_UNDERLINE, '''t''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''f''', '''a''', '''l''', '''s''', '''é''', '''.''']      )




 @slow
 def      __magic_name__	(      self	:							List[str]      )	->						List[str]:
       # Use custom sequence because this tokenizer does not handle numbers.
       SCREAMING_SNAKE_CASE__     :				List[Any]									=[
           '''Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides '''
           '''general-purpose architectures (BERT, GPT, RoBERTa, XLM, DistilBert, XLNet...) for Natural '''
           '''Language Understanding (NLU) and Natural Language Generation (NLG) with over thirty-two pretrained '''
           '''models in one hundred plus languages and deep interoperability between Jax, PyTorch and TensorFlow.''',
           '''BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly '''
           '''conditioning on both left and right context in all layers.''',
           '''The quick brown fox jumps over the lazy dog.''',
       ]

       # fmt: off
       SCREAMING_SNAKE_CASE__     :				str									={
           '''input_ids''': [
               [4, 32, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 64, 19, 8, 13, 18, 5, 13, 15, 22, 4, 28, 9, 8, 20, 9, 4, 7, 12, 4, 24, 22, 6, 8, 13, 17, 11, 39, 6, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 7, 9, 14, 4, 24, 22, 6, 8, 13, 17, 11, 39, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 39, 25, 5, 13, 6, 63, 4, 24, 13, 8, 27, 10, 14, 5, 12, 4, 21, 5, 9, 5, 13, 7, 15, 39, 24, 16, 13, 24, 8, 12, 5, 4, 7, 13, 17, 11, 10, 6, 5, 17, 6, 16, 13, 5, 12, 4, 64, 40, 47, 54, 32, 23, 4, 53, 49, 32, 23, 4, 54, 8, 40, 47, 54, 32, 7, 23, 4, 69, 52, 43, 23, 4, 51, 10, 12, 6, 10, 15, 40, 5, 13, 6, 23, 4, 69, 52, 48, 5, 6, 26, 26, 26, 63, 4, 19, 8, 13, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 61, 9, 14, 5, 13, 12, 6, 7, 9, 14, 10, 9, 21, 4, 64, 48, 52, 61, 63, 4, 7, 9, 14, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 53, 5, 9, 5, 13, 7, 6, 10, 8, 9, 4, 64, 48, 52, 53, 63, 4, 20, 10, 6, 11, 4, 8, 27, 5, 13, 4, 6, 11, 10, 13, 6, 22, 39, 6, 20, 8, 4, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 4, 18, 8, 14, 5, 15, 12, 4, 10, 9, 4, 8, 9, 5, 4, 11, 16, 9, 14, 13, 5, 14, 4, 24, 15, 16, 12, 4, 15, 7, 9, 21, 16, 7, 21, 5, 12, 4, 7, 9, 14, 4, 14, 5, 5, 24, 4, 10, 9, 6, 5, 13, 8, 24, 5, 13, 7, 25, 10, 15, 10, 6, 22, 4, 25, 5, 6, 20, 5, 5, 9, 4, 58, 7, 37, 23, 4, 49, 22, 32, 8, 13, 17, 11, 4, 7, 9, 14, 4, 32, 5, 9, 12, 8, 13, 55, 15, 8, 20, 26, 2],
               [4, 40, 47, 54, 32, 4, 10, 12, 4, 14, 5, 12, 10, 21, 9, 5, 14, 4, 6, 8, 4, 24, 13, 5, 39, 6, 13, 7, 10, 9, 4, 14, 5, 5, 24, 4, 25, 10, 14, 10, 13, 5, 17, 6, 10, 8, 9, 7, 15, 4, 13, 5, 24, 13, 5, 12, 5, 9, 6, 7, 6, 10, 8, 9, 12, 4, 19, 13, 8, 18, 4, 16, 9, 15, 7, 25, 5, 15, 5, 14, 4, 6, 5, 37, 6, 4, 25, 22, 4, 46, 8, 10, 9, 6, 15, 22, 4, 17, 8, 9, 14, 10, 6, 10, 8, 9, 10, 9, 21, 4, 8, 9, 4, 25, 8, 6, 11, 4, 15, 5, 19, 6, 4, 7, 9, 14, 4, 13, 10, 21, 11, 6, 4, 17, 8, 9, 6, 5, 37, 6, 4, 10, 9, 4, 7, 15, 15, 4, 15, 7, 22, 5, 13, 12, 26, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
               [4, 32, 11, 5, 4, 45, 16, 10, 17, 28, 4, 25, 13, 8, 20, 9, 4, 19, 8, 37, 4, 46, 16, 18, 24, 12, 4, 8, 27, 5, 13, 4, 6, 11, 5, 4, 15, 7, 57, 22, 4, 14, 8, 21, 26, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
               [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 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, 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, 1, 1, 1, 1, 1, 1, 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, 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, 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, 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],
           ]
       }
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=__lowercase					,      model_name='''microsoft/speecht5_asr'''					,      revision='''c5ef64c71905caeccde0e4462ef3f9077224c524'''					,      sequences=__lowercase					,      )