






'''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:
      UpperCamelCase							=None


UpperCamelCase							=logging.get_logger(__name__)


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

UpperCamelCase							={
    '''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'''
        ),
    },
}

UpperCamelCase							={
    '''facebook/nllb-large-en-ro''': 1024,
    '''facebook/nllb-200-distilled-600M''': 1024,
}

# fmt: off
UpperCamelCase							=['''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     A    (      __a						):






 """simple docstring"""





 __a			:						Tuple      =						VOCAB_FILES_NAMES
 __a			:						str      =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __a			:						str      =						PRETRAINED_VOCAB_FILES_MAP
 __a			:						Union[str, Any]      =						['''input_ids''', '''attention_mask''']
 __a			:						Optional[int]      =						NllbTokenizer

 __a			:						List[int]      =						[]
 __a			:						List[int]      =						[]
 def __init__(							self			,     __lowerCAmelCase=None			,     __lowerCAmelCase=None			,     __lowerCAmelCase="<s>"			,     __lowerCAmelCase="</s>"			,     __lowerCAmelCase="</s>"			,     __lowerCAmelCase="<s>"			,     __lowerCAmelCase="<unk>"			,     __lowerCAmelCase="<pad>"			,     __lowerCAmelCase="<mask>"			,     __lowerCAmelCase=None			,     __lowerCAmelCase=None			,     __lowerCAmelCase=None			,     __lowerCAmelCase=False			,     **__lowerCAmelCase			,     ):
       # Mask token behave like a normal word, i.e. include the space before it
       UpperCamelCase_				:   int					    =					AddedToken(snake_case__			,     lstrip=snake_case__			,     rstrip=snake_case__ ) if isinstance(snake_case__			,     snake_case__ ) else mask_token
       UpperCamelCase_				:   Optional[int]					    =					legacy_behaviour
       super().__init__(
           vocab_file=snake_case__			,     tokenizer_file=snake_case__			,     bos_token=snake_case__			,     eos_token=snake_case__			,     sep_token=snake_case__			,     cls_token=snake_case__			,     unk_token=snake_case__			,     pad_token=snake_case__			,     mask_token=snake_case__			,     src_lang=snake_case__			,     tgt_lang=snake_case__			,     additional_special_tokens=snake_case__			,     legacy_behaviour=snake_case__			,     **snake_case__			,     )

       UpperCamelCase_				:   Any					    =					vocab_file
       UpperCamelCase_				:   Union[str, Any]					    =					False if not self.vocab_file else True

       UpperCamelCase_				:   List[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} )
       UpperCamelCase_				:   Optional[int]					    =					{
           lang_code: self.convert_tokens_to_ids(snake_case__ ) for lang_code in FAIRSEQ_LANGUAGE_CODES
       }

       UpperCamelCase_				:   List[str]					    =					src_lang if src_lang is not None else """eng_Latn"""
       UpperCamelCase_				:   str					    =					self.convert_tokens_to_ids(self._src_lang )
       UpperCamelCase_				:   List[Any]					    =					tgt_lang
       self.set_src_lang_special_tokens(self._src_lang )
 @property
 def   _UpperCAmelCase       (							self ):
       return self._src_lang
 @src_lang.setter
 def   _UpperCAmelCase       (							self			,     __lowerCAmelCase ):
       UpperCamelCase_				:   Dict					    =					new_src_lang
       self.set_src_lang_special_tokens(self._src_lang )
 def   _UpperCAmelCase       (							self			,     __lowerCAmelCase			,     __lowerCAmelCase = None ):
       if token_ids_a is None:
             return self.prefix_tokens + token_ids_a + self.suffix_tokens
       # We don't expect to process pairs, but leave the pair logic for API consistency
       return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
 def   _UpperCAmelCase       (							self			,     __lowerCAmelCase			,     __lowerCAmelCase = None ):
       UpperCamelCase_				:   str					    =					[self.sep_token_id]
       UpperCamelCase_				:   Dict					    =					[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   _UpperCAmelCase       (							self			,     __lowerCAmelCase			,     __lowerCAmelCase			,     __lowerCAmelCase			,     __lowerCAmelCase			,     **__lowerCAmelCase ):
       if src_lang is None or tgt_lang is None:
             raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model""" )
       UpperCamelCase_				:   Union[str, Any]					    =					src_lang
       UpperCamelCase_				:   Any					    =					self(snake_case__			,     add_special_tokens=snake_case__			,     return_tensors=snake_case__			,     **snake_case__ )
       UpperCamelCase_				:   Dict					    =					self.convert_tokens_to_ids(snake_case__ )
       UpperCamelCase_				:   List[Any]					    =					tgt_lang_id
       return inputs
 def   _UpperCAmelCase       (							self			,     __lowerCAmelCase			,     __lowerCAmelCase = "eng_Latn"			,     __lowerCAmelCase = None			,     __lowerCAmelCase = "fra_Latn"			,     **__lowerCAmelCase			,     ):
       UpperCamelCase_				:   Optional[Any]					    =					src_lang
       UpperCamelCase_				:   List[Any]					    =					tgt_lang
       return super().prepare_seqaseq_batch(snake_case__			,     snake_case__			,     **snake_case__ )
 def   _UpperCAmelCase       (							self ):
       return self.set_src_lang_special_tokens(self.src_lang )
 def   _UpperCAmelCase       (							self ):
       return self.set_tgt_lang_special_tokens(self.tgt_lang )
 def   _UpperCAmelCase       (							self			,     __lowerCAmelCase ):
       UpperCamelCase_				:   List[Any]					    =					self.convert_tokens_to_ids(snake_case__ )

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

       UpperCamelCase_				:   Union[str, Any]					    =					self.convert_ids_to_tokens(self.prefix_tokens )
       UpperCamelCase_				:   str					    =					self.convert_ids_to_tokens(self.suffix_tokens )

       UpperCamelCase_				:   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   _UpperCAmelCase       (							self			,     __lowerCAmelCase ):
       UpperCamelCase_				:   Any					    =					self.convert_tokens_to_ids(snake_case__ )
       if self.legacy_behaviour:
             UpperCamelCase_				:   int					    =					[]
             UpperCamelCase_				:   List[str]					    =					[self.eos_token_id, self.cur_lang_code]
       else:
             UpperCamelCase_				:   Optional[int]					    =					[self.cur_lang_code]
             UpperCamelCase_				:   Any					    =					[self.eos_token_id]

       UpperCamelCase_				:   int					    =					self.convert_ids_to_tokens(self.prefix_tokens )
       UpperCamelCase_				:   Dict					    =					self.convert_ids_to_tokens(self.suffix_tokens )

       UpperCamelCase_				:   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   _UpperCAmelCase       (							self			,     __lowerCAmelCase			,     __lowerCAmelCase = None ):
       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(snake_case__ ):
             logger.error(F"Vocabulary path ({save_directory}) should be a directory." )
             return
       UpperCamelCase_				:   List[Any]					    =					os.path.join(
           snake_case__			,     (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

       if os.path.abspath(self.vocab_file ) != os.path.abspath(snake_case__ ):
             copyfile(self.vocab_file			,     snake_case__ )

       return (out_vocab_file,)














'''simple docstring'''

import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
      UpperCamelCase							="pt"
elif is_tf_available():
      UpperCamelCase							="tf"
else:
      UpperCamelCase							="jax"




class     A    (      SCREAMING_SNAKE_CASE__,   unittest.TestCase						):






 """simple docstring"""





 __a			:						int      =						PerceiverTokenizer
 __a			:						List[str]      =						False
 def   _UpperCAmelCase       (							self ):
       super().setUp()
       UpperCamelCase_				:   Optional[int]					    =							PerceiverTokenizer()
       tokenizer.save_pretrained(self.tmpdirname )
 @cached_property
 def   _UpperCAmelCase       (							self ):
       return PerceiverTokenizer.from_pretrained("""deepmind/language-perceiver""" )
 def   _UpperCAmelCase       (							self			,     **__lowerCAmelCase ):
       return self.tokenizer_class.from_pretrained(self.tmpdirname			,     **__lowerCAmelCase )
 def   _UpperCAmelCase       (							self			,     __lowerCAmelCase			,     __lowerCAmelCase=False			,     __lowerCAmelCase=20			,     __lowerCAmelCase=5 ):
       # XXX The default common tokenizer tests assume that every ID is decodable on its own.
       # This assumption is invalid for Perceiver because single bytes might not be
       # valid utf-8 (byte 128 for instance).
       # Here we're overriding the smallest possible method to provide
       # a clean sequence without making the same assumption.

       UpperCamelCase_				:   str					    =							[]
       for i in range(len(__lowerCAmelCase ) ):
             try:
                   UpperCamelCase_				:   Tuple					    =							tokenizer.decode([i]			,     clean_up_tokenization_spaces=__lowerCAmelCase )
             except UnicodeDecodeError:
                   pass
             toks.append((i, tok) )

       UpperCamelCase_				:   Optional[Any]					    =							list(filter(lambda __lowerCAmelCase : re.match(R"""^[ a-zA-Z]+$"""			,     t[1] )			,     __lowerCAmelCase ) )
       UpperCamelCase_				:   int					    =							list(filter(lambda __lowerCAmelCase : [t[0]] == tokenizer.encode(t[1]			,     add_special_tokens=__lowerCAmelCase )			,     __lowerCAmelCase ) )
       if max_length is not None and len(__lowerCAmelCase ) > max_length:
             UpperCamelCase_				:   List[Any]					    =							toks[:max_length]
       if min_length is not None and len(__lowerCAmelCase ) < min_length and len(__lowerCAmelCase ) > 0:
             while len(__lowerCAmelCase ) < min_length:
                   UpperCamelCase_				:   Tuple					    =							toks + toks
        # toks_str = [t[1] for t in toks]
       UpperCamelCase_				:   List[Any]					    =							[t[0] for t in toks]

       # Ensure consistency
       UpperCamelCase_				:   str					    =							tokenizer.decode(__lowerCAmelCase			,     clean_up_tokenization_spaces=__lowerCAmelCase )
       if " " not in output_txt and len(__lowerCAmelCase ) > 1:
             UpperCamelCase_				:   Tuple					    =							(
                 tokenizer.decode([toks_ids[0]]			,     clean_up_tokenization_spaces=__lowerCAmelCase )
                 + """ """
                 + tokenizer.decode(toks_ids[1:]			,     clean_up_tokenization_spaces=__lowerCAmelCase )
             )
       if with_prefix_space:
             UpperCamelCase_				:   Tuple					    =							""" """ + output_txt
       UpperCamelCase_				:   List[str]					    =							tokenizer.encode(__lowerCAmelCase			,     add_special_tokens=__lowerCAmelCase )
       return output_txt, output_ids
 def   _UpperCAmelCase       (							self ):
       UpperCamelCase_				:   Dict					    =							self.perceiver_tokenizer
       UpperCamelCase_				:   Optional[int]					    =							"""Unicode €."""
       UpperCamelCase_				:   Dict					    =							tokenizer(__lowerCAmelCase )
       UpperCamelCase_				:   Tuple					    =							[4, 91, 1_16, 1_11, 1_05, 1_17, 1_06, 1_07, 38, 2_32, 1_36, 1_78, 52, 5]
       self.assertEqual(encoded["""input_ids"""]			,     __lowerCAmelCase )

       # decoding
       UpperCamelCase_				:   str					    =							tokenizer.decode(__lowerCAmelCase )
       self.assertEqual(__lowerCAmelCase			,     """[CLS]Unicode €.[SEP]""" )

       UpperCamelCase_				:   str					    =							tokenizer("""e è é ê ë""" )
       UpperCamelCase_				:   List[str]					    =							[4, 1_07, 38, 2_01, 1_74, 38, 2_01, 1_75, 38, 2_01, 1_76, 38, 2_01, 1_77, 5]
       self.assertEqual(encoded["""input_ids"""]			,     __lowerCAmelCase )
       # decoding
       UpperCamelCase_				:   List[str]					    =							tokenizer.decode(__lowerCAmelCase )
       self.assertEqual(__lowerCAmelCase			,     """[CLS]e è é ê ë[SEP]""" )

       # encode/decode, but with `encode` instead of `__call__`
       self.assertEqual(tokenizer.decode(tokenizer.encode("""e è é ê ë""" ) )			,     """[CLS]e è é ê ë[SEP]""" )
 def   _UpperCAmelCase       (							self ):
       UpperCamelCase_				:   Union[str, Any]					    =							self.perceiver_tokenizer
       UpperCamelCase_				:   Optional[Any]					    =							["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
       # fmt: off
       UpperCamelCase_				:   int					    =							[4, 71, 38, 1_14, 1_17, 1_16, 1_09, 38, 1_18, 1_03, 1_20, 1_03, 1_09, 1_20, 1_03, 1_18, 1_10, 38, 1_08, 1_17, 1_20, 38, 1_21, 1_23, 1_15, 1_15, 1_03, 1_20, 1_11, 1_28, 1_03, 1_22, 1_11, 1_17, 1_16, 52, 5, 0]
       # fmt: on
       UpperCamelCase_				:   Any					    =							tokenizer(__lowerCAmelCase			,     padding=__lowerCAmelCase			,     return_tensors=__lowerCAmelCase )
       self.assertIsInstance(__lowerCAmelCase			,     __lowerCAmelCase )

       if FRAMEWORK != "jax":
             UpperCamelCase_				:   Optional[Any]					    =							list(batch.input_ids.numpy()[0] )
       else:
             UpperCamelCase_				:   Optional[int]					    =							list(batch.input_ids.tolist()[0] )

       self.assertListEqual(__lowerCAmelCase			,     __lowerCAmelCase )

       self.assertEqual((2, 38)			,     batch.input_ids.shape )
       self.assertEqual((2, 38)			,     batch.attention_mask.shape )
 def   _UpperCAmelCase       (							self ):
       UpperCamelCase_				:   Optional[int]					    =							self.perceiver_tokenizer
       UpperCamelCase_				:   Union[str, Any]					    =							["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
       UpperCamelCase_				:   int					    =							tokenizer(__lowerCAmelCase			,     padding=__lowerCAmelCase			,     return_tensors=__lowerCAmelCase )
       # check if input_ids are returned and no decoder_input_ids
       self.assertIn("""input_ids"""			,     __lowerCAmelCase )
       self.assertIn("""attention_mask"""			,     __lowerCAmelCase )
       self.assertNotIn("""decoder_input_ids"""			,     __lowerCAmelCase )
       self.assertNotIn("""decoder_attention_mask"""			,     __lowerCAmelCase )
 def   _UpperCAmelCase       (							self ):
       UpperCamelCase_				:   int					    =							self.perceiver_tokenizer
       UpperCamelCase_				:   List[str]					    =							[
           """Summary of the text.""",
           """Another summary.""",
       ]
       UpperCamelCase_				:   Dict					    =							tokenizer(
           text_target=__lowerCAmelCase			,     max_length=32			,     padding="""max_length"""			,     truncation=__lowerCAmelCase			,     return_tensors=__lowerCAmelCase )
       self.assertEqual(32			,     targets["""input_ids"""].shape[1] )
 def   _UpperCAmelCase       (							self ):
       # safety check on max_len default value so we are sure the test works
       UpperCamelCase_				:   Tuple					    =							self.get_tokenizers()
       for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}" ):
                   self.assertNotEqual(tokenizer.model_max_length			,     42 )

        # Now let's start the test
       UpperCamelCase_				:   Tuple					    =							self.get_tokenizers()
       for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}" ):
                   # Isolate this from the other tests because we save additional tokens/etc
                   UpperCamelCase_				:   Tuple					    =							tempfile.mkdtemp()

                   UpperCamelCase_				:   Optional[int]					    =							""" He is very happy, UNwant\u00E9d,running"""
                   UpperCamelCase_				:   Dict					    =							tokenizer.encode(__lowerCAmelCase			,     add_special_tokens=__lowerCAmelCase )
                   tokenizer.save_pretrained(__lowerCAmelCase )

                   UpperCamelCase_				:   Tuple					    =							tokenizer.__class__.from_pretrained(__lowerCAmelCase )
                   UpperCamelCase_				:   Union[str, Any]					    =							after_tokenizer.encode(__lowerCAmelCase			,     add_special_tokens=__lowerCAmelCase )
                   self.assertListEqual(__lowerCAmelCase			,     __lowerCAmelCase )

                   shutil.rmtree(__lowerCAmelCase )

       UpperCamelCase_				:   Union[str, Any]					    =							self.get_tokenizers(model_max_length=42 )
       for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}" ):
                   # Isolate this from the other tests because we save additional tokens/etc
                   UpperCamelCase_				:   Tuple					    =							tempfile.mkdtemp()

                   UpperCamelCase_				:   List[str]					    =							""" He is very happy, UNwant\u00E9d,running"""
                   tokenizer.add_tokens(["""bim""", """bambam"""] )
                   UpperCamelCase_				:   Any					    =							tokenizer.additional_special_tokens
                   additional_special_tokens.append("""new_additional_special_token""" )
                   tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens} )
                   UpperCamelCase_				:   Union[str, Any]					    =							tokenizer.encode(__lowerCAmelCase			,     add_special_tokens=__lowerCAmelCase )
                   tokenizer.save_pretrained(__lowerCAmelCase )

                   UpperCamelCase_				:   Tuple					    =							tokenizer.__class__.from_pretrained(__lowerCAmelCase )
                   UpperCamelCase_				:   List[Any]					    =							after_tokenizer.encode(__lowerCAmelCase			,     add_special_tokens=__lowerCAmelCase )
                   self.assertListEqual(__lowerCAmelCase			,     __lowerCAmelCase )
                   self.assertIn("""new_additional_special_token"""			,     after_tokenizer.additional_special_tokens )
                   self.assertEqual(after_tokenizer.model_max_length			,     42 )

                   UpperCamelCase_				:   int					    =							tokenizer.__class__.from_pretrained(__lowerCAmelCase			,     model_max_length=43 )
                   self.assertEqual(tokenizer.model_max_length			,     43 )

                   shutil.rmtree(__lowerCAmelCase )
 def   _UpperCAmelCase       (							self ):
       UpperCamelCase_				:   str					    =							[]
       if self.test_slow_tokenizer:
             tokenizer_list.append((self.tokenizer_class, self.get_tokenizer()) )

       if self.test_rust_tokenizer:
             tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer()) )

       for tokenizer_class, tokenizer_utils in tokenizer_list:
             with tempfile.TemporaryDirectory() as tmp_dir:
                   tokenizer_utils.save_pretrained(__lowerCAmelCase )

                   with open(os.path.join(__lowerCAmelCase			,     """special_tokens_map.json""" )			,     encoding="""utf-8""" ) as json_file:
                         UpperCamelCase_				:   Union[str, Any]					    =							json.load(__lowerCAmelCase )

                   with open(os.path.join(__lowerCAmelCase			,     """tokenizer_config.json""" )			,     encoding="""utf-8""" ) as json_file:
                         UpperCamelCase_				:   List[str]					    =							json.load(__lowerCAmelCase )

                   UpperCamelCase_				:   Tuple					    =							[F"<extra_id_{i}>" for i in range(1_25 )]

                   UpperCamelCase_				:   Union[str, Any]					    =							added_tokens_extra_ids + [
                       """an_additional_special_token"""
                   ]
                   UpperCamelCase_				:   List[Any]					    =							added_tokens_extra_ids + [
                       """an_additional_special_token"""
                   ]

                   with open(os.path.join(__lowerCAmelCase			,     """special_tokens_map.json""" )			,     """w"""			,     encoding="""utf-8""" ) as outfile:
                         json.dump(__lowerCAmelCase			,     __lowerCAmelCase )
                   with open(os.path.join(__lowerCAmelCase			,     """tokenizer_config.json""" )			,     """w"""			,     encoding="""utf-8""" ) as outfile:
                         json.dump(__lowerCAmelCase			,     __lowerCAmelCase )

                   # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                   # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                   # "special_tokens_map.json" files
                   UpperCamelCase_				:   Optional[int]					    =							tokenizer_class.from_pretrained(
                       __lowerCAmelCase			,     )
                   self.assertIn(
                       """an_additional_special_token"""			,     tokenizer_without_change_in_init.additional_special_tokens )
                   self.assertEqual(
                       ["""an_additional_special_token"""]			,     tokenizer_without_change_in_init.convert_ids_to_tokens(
                           tokenizer_without_change_in_init.convert_tokens_to_ids(["""an_additional_special_token"""] ) )			,     )

                   # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                   UpperCamelCase_				:   Optional[Any]					    =							added_tokens_extra_ids + [AddedToken("""a_new_additional_special_token"""			,     lstrip=__lowerCAmelCase )]
                   UpperCamelCase_				:   Union[str, Any]					    =							tokenizer_class.from_pretrained(
                       __lowerCAmelCase			,     additional_special_tokens=__lowerCAmelCase			,     )

                   self.assertIn("""a_new_additional_special_token"""			,     tokenizer.additional_special_tokens )
                   self.assertEqual(
                       ["""a_new_additional_special_token"""]			,     tokenizer.convert_ids_to_tokens(
                           tokenizer.convert_tokens_to_ids(["""a_new_additional_special_token"""] ) )			,     )
 def   _UpperCAmelCase       (							self ):
       UpperCamelCase_				:   List[Any]					    =							self.perceiver_tokenizer
       self.assertEqual(tokenizer.decode([1_78] )			,     """�""" )
 def   _UpperCAmelCase       (							self ):
       pass
 def   _UpperCAmelCase       (							self ):
       pass
 def   _UpperCAmelCase       (							self ):
       pass
 def   _UpperCAmelCase       (							self ):
       pass





 def   _UpperCAmelCase       (							self ):
       # The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
       # strings and special added tokens as tokens
       UpperCamelCase_				:   Dict					    =							self.get_tokenizers(fast=__lowerCAmelCase			,     do_lower_case=__lowerCAmelCase )
       for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}" ):
                   UpperCamelCase_				:   str					    =							["""[CLS]""", """t""", """h""", """i""", """s""", """ """, """i""", """s""", """ """, """a""", """ """, """t""", """e""", """s""", """t""", """[SEP]"""]
                   UpperCamelCase_				:   Optional[Any]					    =							tokenizer.convert_tokens_to_string(__lowerCAmelCase )

                   self.assertIsInstance(__lowerCAmelCase			,     __lowerCAmelCase )






