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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE										=						logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE										=						{'vocab_file': 'sentencepiece.model'}

_SCREAMING_SNAKE_CASE										=						{
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
}

_SCREAMING_SNAKE_CASE										=						{
    'google/rembert': 256,
}



class 				a							(			__lowerCAmelCase       ):







 """simple docstring"""






 lowerCamelCase	:Optional[Any]    			=		VOCAB_FILES_NAMES
 lowerCamelCase	:Union[str, Any]    			=		PRETRAINED_VOCAB_FILES_MAP
 lowerCamelCase	:List[Any]    			=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



 def __init__(					self		,				lowerCAmelCase_		,				lowerCAmelCase_=False		,				lowerCAmelCase_=True		,				lowerCAmelCase_=True		,				lowerCAmelCase_="[CLS]"		,				lowerCAmelCase_="[SEP]"		,				lowerCAmelCase_="[UNK]"		,				lowerCAmelCase_="[SEP]"		,				lowerCAmelCase_="[PAD]"		,				lowerCAmelCase_="[CLS]"		,				lowerCAmelCase_="[MASK]"		,				**lowerCAmelCase_		,				)  ->					int:
        super().__init__(
            do_lower_case=lowerCAmelCase_		,				remove_space=lowerCAmelCase_		,				keep_accents=lowerCAmelCase_		,				bos_token=lowerCAmelCase_		,				eos_token=lowerCAmelCase_		,				unk_token=lowerCAmelCase_		,				sep_token=lowerCAmelCase_		,				pad_token=lowerCAmelCase_		,				cls_token=lowerCAmelCase_		,				mask_token=lowerCAmelCase_		,				**lowerCAmelCase_		,				)

        _A        =  do_lower_case
        _A        =  remove_space
        _A        =  keep_accents
        _A        =  vocab_file

        _A        =  spm.SentencePieceProcessor()
        self.sp_model.Load(lowerCAmelCase_							)



 @property
 def      UpperCAmelCase							(					self							)  ->					str:
        return len(self.sp_model							)



 def      UpperCAmelCase							(					self							)  ->					str:
        _A        =  {self.convert_ids_to_tokens(lowerCAmelCase_							): i for i in range(self.vocab_size							)}
        vocab.update(self.added_tokens_encoder							)
        return vocab



 def __getstate__(					self							)  ->					Union[str, Any]:
        _A        =  self.__dict__.copy()
        _A        =  None
        return state



 def __setstate__(					self		,				lowerCAmelCase_							)  ->					Any:
        _A        =  d
        _A        =  spm.SentencePieceProcessor()
        self.sp_model.Load(self.vocab_file							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_=False							)  ->					List[str]:
        _A        =  self.sp_model.EncodeAsPieces(lowerCAmelCase_							)
        return pieces



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					str:
        return self.sp_model.PieceToId(lowerCAmelCase_							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					Dict:
        return self.sp_model.IdToPiece(lowerCAmelCase_							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					str:
        _A        =  self.sp_model.decode_pieces(lowerCAmelCase_							)
        return out_string



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_ = None							)  ->					List[int]:
        _A        =  [self.sep_token_id]
        _A        =  [self.cls_token_id]
        if token_ids_a is None:
               return cls + token_ids_a + sep
        return cls + token_ids_a + sep + token_ids_a + sep



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_ = None		,				lowerCAmelCase_ = False							)  ->					List[int]:

        if already_has_special_tokens:
               if token_ids_a is not None:
                      raise ValueError(
                          """You should not supply a second sequence if the provided sequence of """
                          """ids is already formatted with special tokens for the model."""							)
               return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

        if token_ids_a is not None:
               return [1] + ([0] * len(lowerCAmelCase_							)) + [1] + ([0] * len(lowerCAmelCase_							)) + [1]
        return [1] + ([0] * len(lowerCAmelCase_							)) + [1]



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_ = None							)  ->					List[int]:
        _A        =  [self.sep_token_id]
        _A        =  [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							) * [0] + len(token_ids_a + sep							) * [1]



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_ = None							)  ->					Tuple[str]:
        if not os.path.isdir(lowerCAmelCase_							):
               logger.error("""Vocabulary path ({}) should be a directory""".format(lowerCAmelCase_							)							)
               return
        _A        =  os.path.join(
            lowerCAmelCase_		,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)

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

        return (out_vocab_file,)





import json
import os
import unittest
from typing import Tuple

from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from transformers.testing_utils import require_phonemizer

from ...test_tokenization_common import TokenizerTesterMixin



@require_phonemizer
class 				a							(			__lowerCAmelCase       ,			unittest.TestCase       ):







 """simple docstring"""






 lowerCamelCase	:Dict    			=		WavaVecaPhonemeCTCTokenizer
 lowerCamelCase	:Optional[int]    			=		False



 def      UpperCAmelCase							(					self							)  ->					Optional[int]:
        super().setUp()

        _A        =  (
            """<s> <pad> </s> <unk> n s t ə l a i k d m ɛ ɾ e ɪ p o ɐ z ð f j v b ɹ ʁ ʊ iː r w ʌ u ɡ æ aɪ ʃ h ɔ ɑː """
            """ŋ ɚ eɪ β uː y ɑ̃ oʊ ᵻ eː θ aʊ ts oː ɔ̃ ɣ ɜ ɑ dʒ əl x ɜː ç ʒ tʃ ɔː ɑːɹ ɛ̃ ʎ ɔːɹ ʋ aː ɕ œ ø oːɹ ɲ yː """
            """ʔ iə i5 s. tɕ ?? nʲ ɛː œ̃ ɭ ɔø ʑ tʲ ɨ ɛɹ ts. rʲ ɪɹ ɭʲ i.5 ɔɪ q sʲ u5 ʊɹ iɜ a5 iɛ5 øː ʕ ja əɜ th ɑ5 """
            """oɪ dʲ ə5 tɕh ts.h mʲ ɯ dʑ vʲ e̞ tʃʲ ei5 o5 onɡ5 ɑu5 iɑ5 ai5 aɪɚ kh ə1 ʐ i2 ʉ ħ t[ aɪə ʲ ju ə2 u2 oɜ """
            """pː iɛɜ ou5 y5 uɜ tː uo5 d[ uoɜ tsh ɑɜ ɵ i̪5 uei5 ɟ aɜ ɑɨ i.ɜ eʊ o2 ɐ̃ ä pʲ kʲ n̩ ɒ ph ɑu2 uɨ əɪ ɫ ɬ """
            """yɜ bʲ ɑ2 s̪ aiɜ χ ɐ̃ʊ̃ 1 ə4 yæɜ a2 ɨː t̪ iouɜ ũ onɡɜ aɨ iɛ2 ɔɨ ɑuɜ o̞ ei2 iou2 c kː y2 ɖ oe dˤ yɛɜ """
            """əʊ S ɡʲ onɡ2 u\" eiɜ ʈ ɯᵝ iou5 dZ r̝̊ i.2 tS s^ ʝ yə5 iɑɜ uə5 pf ɨu iɑ2 ou2 ər2 fʲ ai2 r̝ uəɜ ɳ əɨ """
            """ua5 uɪ ɽ bː yu5 uo2 yɛ5 l̩ ɻ ərɜ ʂ i̪2 ouɜ uaɜ a. a.ː yæ5 dː r̩ ee ɪu ər5 i̪ ɜ æi u: i.ː t^ o1 ɪ^ """
            """ai ueiɜ æː ɛɪ eə i. ɴ ie ua2 ɑ1 o4 tʃː o: ɑ: u1 N i̪1 au yæ2 u. qː yəɜ y: kʰ tʃʰ iʊ sx õ uo tʰ """
            """uai5 bʰ u.ː uə2 ʊə d^ s̪ː yiɜ dʰ r. oe: i1 ɟː yu2 nʲʲ i̪4 uei2 tsʲ ɸ ĩ ɑ4 t̪ː eɑ u4 e: tsː ʈʰ ɡʰ """
            """ɯɯ dʒʲ ʂʲ X ɵː uaiɜ tɕʲ ã t^ː ẽː yɛ2 cː i.1 ɛʊ dˤdˤ dʒː i4 ɡː yi ɕʲ ɟʰ pʰ dʑʲ yuɜ ua1 ua4 æiː ɐɐ """
            """ui iou1 ʊː a1 iou4 cʰ iɛ1 yə2 ɖʰ ẽ ʒʲ ää ər4 iːː ɪː iɑ1 ər1 œː øi ɪuː cʰcʰ əː1 iː1 ũ kʰː o̞o̞ xʲ """
            """ou1 iɛ4 e̞e̞ y1 dzː dʲʲ dʰː ɯᵝɯᵝ lː uo1 i.4 i: yɛ5ʲ a4"""
        ).split(""" """							)
        _A        =  dict(zip(lowerCAmelCase_		,				range(len(lowerCAmelCase_							)							)							)							)

        _A        =  {"""pad_token""": """<pad>""", """unk_token""": """<unk>""", """bos_token""": """<s>""", """eos_token""": """</s>"""}

        _A        =  os.path.join(self.tmpdirname		,				VOCAB_FILES_NAMES["""vocab_file"""]							)
        with open(self.vocab_file		,				"""w"""		,				encoding="""utf-8"""							) as fp:
               fp.write(json.dumps(lowerCAmelCase_							) + """\n"""							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_		,				lowerCAmelCase_=False		,				lowerCAmelCase_=20		,				lowerCAmelCase_=5							)  ->					Tuple[str, list]:
        _A        =  [(i, tokenizer.decode([i]		,				clean_up_tokenization_spaces=lowerCAmelCase_							)) for i in range(len(lowerCAmelCase_							)							)]
        _A        =  list(filter(lambda lowerCAmelCase_							: [t[0]] == tokenizer.encode(t[1]		,				do_phonemize=lowerCAmelCase_							)		,				lowerCAmelCase_							)							)
        if max_length is not None and len(lowerCAmelCase_							) > max_length:
               _A        =  toks[:max_length]
        if min_length is not None and len(lowerCAmelCase_							) < min_length and len(lowerCAmelCase_							) > 0:
               while len(lowerCAmelCase_							) < min_length:
                      _A        =  toks + toks
        # toks_str = [t[1] for t in toks]
        _A        =  [t[0] for t in toks]

        # Ensure consistency
        _A        =  tokenizer.decode(lowerCAmelCase_		,				clean_up_tokenization_spaces=lowerCAmelCase_							)
        if " " not in output_txt and len(lowerCAmelCase_							) > 1:
               _A        =  (
                   tokenizer.decode([toks_ids[0]]		,				clean_up_tokenization_spaces=lowerCAmelCase_							)
                   + """ """
                   + tokenizer.decode(toks_ids[1:]		,				clean_up_tokenization_spaces=lowerCAmelCase_							)
               )
        if with_prefix_space:
               _A        =  """ """ + output_txt
        _A        =  tokenizer.encode(lowerCAmelCase_		,				add_special_tokens=lowerCAmelCase_							)
        return output_txt, output_ids



 def      UpperCAmelCase							(					self		,				**lowerCAmelCase_							)  ->					Any:
        kwargs.update(self.special_tokens_map							)
        return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname		,				**lowerCAmelCase_							)



 def      UpperCAmelCase							(					self							)  ->					List[str]:
        _A        =  self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""							)

        # check adding a single token
        tokenizer.add_tokens("""xxx"""							)
        _A        =  tokenizer("""m xxx ɪ"""		,				do_phonemize=lowerCAmelCase_							).input_ids
        self.assertEqual(lowerCAmelCase_		,				[13, 3_92, 17]							)  # xxx should be last token

        tokenizer.add_tokens(["""aaa""", """bbb""", """ccc"""]							)
        _A        =  tokenizer("""m aaa ɪ ccc"""		,				do_phonemize=lowerCAmelCase_							).input_ids
        self.assertEqual(lowerCAmelCase_		,				[13, 3_93, 17, 3_95]							)  # aaa and ccc should be after xxx and 2 after aaa

        _A        =  tokenizer("""maɪ c"""		,				do_phonemize=lowerCAmelCase_							).input_ids
        self.assertEqual(lowerCAmelCase_		,				[3, 2_00]							)  # mai should be <unk> (=3)



 def      UpperCAmelCase							(					self							)  ->					int:
        _A        =  self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""							)

        _A        =  """Hello how are you"""
        _A        =  tokenizer.phonemize(lowerCAmelCase_		,				phonemizer_lang="""en-us"""							)
        self.assertEqual(lowerCAmelCase_		,				"""h ə l oʊ h aʊ ɑːɹ j uː"""							)



 def      UpperCAmelCase							(					self							)  ->					List[str]:
        _A        =  self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""							)

        _A        =  """Hello how are you"""
        _A        =  tokenizer.phonemize(lowerCAmelCase_		,				phonemizer_lang="""en-us"""							)
        self.assertEqual(tokenizer(lowerCAmelCase_							).input_ids		,				tokenizer(lowerCAmelCase_		,				do_phonemize=lowerCAmelCase_							).input_ids							)



 def      UpperCAmelCase							(					self							)  ->					List[str]:
        _A        =  self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""							)
        _A        =  """Hello how are you"""
        _A        =  tokenizer.phonemize(lowerCAmelCase_		,				phonemizer_lang="""en-us"""							)

        _A        =  tokenizer.decode(tokenizer(lowerCAmelCase_							).input_ids							)

        self.assertEqual(lowerCAmelCase_		,				lowerCAmelCase_							)



 def      UpperCAmelCase							(					self							)  ->					Tuple:
        _A        =  self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""							)

        _A        =  [
            [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
            [24, 22, 5, 24, 22, 5, 77],
        ]
        _A        =  tokenizer.decode(sample_ids[0]							)
        _A        =  tokenizer.batch_decode(lowerCAmelCase_							)
        self.assertEqual(lowerCAmelCase_		,				batch_tokens[0]							)
        self.assertEqual(lowerCAmelCase_		,				["""k s ɾ ɾ l ɭʲ""", """j ð s j ð s oːɹ"""]							)



 def      UpperCAmelCase							(					self							)  ->					str:
        _A        =  self.tokenizer_class.from_pretrained(
            """facebook/wav2vec2-lv-60-espeak-cv-ft"""		,				word_delimiter_token="""|"""							)
        tokenizer.add_tokens("""|"""							)

        _A        =  """Hello how are you"""
        _A        =  tokenizer.phonemize(lowerCAmelCase_		,				phonemizer_lang="""en-us"""							)
        self.assertEqual(lowerCAmelCase_		,				"""h ə l oʊ | h aʊ | ɑːɹ | j uː |"""							)



 def      UpperCAmelCase							(					self							)  ->					Tuple:
        _A        =  self.tokenizer_class.from_pretrained(
            """facebook/wav2vec2-lv-60-espeak-cv-ft"""		,				word_delimiter_token="""|"""							)
        tokenizer.add_tokens("""|"""							)

        _A        =  """Hello how are you"""
        _A        =  tokenizer.phonemize(lowerCAmelCase_		,				phonemizer_lang="""en-us"""							)
        self.assertEqual(tokenizer(lowerCAmelCase_							).input_ids		,				tokenizer(lowerCAmelCase_		,				do_phonemize=lowerCAmelCase_							).input_ids							)



 def      UpperCAmelCase							(					self							)  ->					List[Any]:
        _A        =  self.tokenizer_class.from_pretrained(
            """facebook/wav2vec2-lv-60-espeak-cv-ft"""		,				word_delimiter_token="""|"""							)
        tokenizer.add_tokens("""|"""							)

        # fmt: off
        _A        =  [
            [11, 5, 15, tokenizer.pad_token_id, tokenizer.word_delimiter_token_id, 15, 8, tokenizer.word_delimiter_token_id, 98],
            [tokenizer.word_delimiter_token_id, 24, 22, tokenizer.word_delimiter_token_id, 5, 24, 22, 5, 77],
        ]
        # fmt: on

        # decode with word_del_token filter
        _A        =  tokenizer.decode(sample_ids[0]							)
        _A        =  tokenizer.batch_decode(lowerCAmelCase_							)
        self.assertEqual(lowerCAmelCase_		,				batch_tokens[0]							)
        self.assertEqual(lowerCAmelCase_		,				["""k s ɾ ɾ l ɭʲ""", """j ð s j ð s oːɹ"""]							)

        # decode with no word_del_token filter
        _A        =  tokenizer.decode(sample_ids[0]		,				filter_word_delimiter_token=lowerCAmelCase_							)
        _A        =  tokenizer.batch_decode(lowerCAmelCase_		,				filter_word_delimiter_token=lowerCAmelCase_							)
        self.assertEqual(lowerCAmelCase_		,				batch_tokens[0]							)
        self.assertEqual(lowerCAmelCase_		,				["""k s ɾ | ɾ l | ɭʲ""", """| j ð | s j ð s oːɹ"""]							)



 def      UpperCAmelCase							(					self							)  ->					Dict:
        _A        =  self.tokenizer_class.from_pretrained(
            """facebook/wav2vec2-lv-60-espeak-cv-ft"""		,				word_delimiter_token="""|"""							)
        tokenizer.add_tokens("""|"""							)

        _A        =  """Hello how are you"""
        _A        =  tokenizer.phonemize(lowerCAmelCase_		,				phonemizer_lang="""en-us"""							)

        _A        =  tokenizer.decode(tokenizer(lowerCAmelCase_							).input_ids		,				filter_word_delimiter_token=lowerCAmelCase_							)

        self.assertEqual(lowerCAmelCase_		,				lowerCAmelCase_							)



 def      UpperCAmelCase							(					self							)  ->					Tuple:
        _A        =  self.tokenizer_class.from_pretrained(
            """facebook/wav2vec2-lv-60-espeak-cv-ft"""		,				word_delimiter_token="""|"""							)
        tokenizer.add_tokens("""|"""							)

        _A        =  """Hello how are you"""
        _A        =  tokenizer.phonemize(lowerCAmelCase_		,				phonemizer_lang="""en-us"""							)

        _A        =  tokenizer.decode(tokenizer(lowerCAmelCase_							).input_ids		,				filter_word_delimiter_token=lowerCAmelCase_							)

        self.assertEqual(""" """.join([p.strip() for p in phonemes.split(""" |"""							)]							).strip()		,				lowerCAmelCase_							)



 def      UpperCAmelCase							(					self							)  ->					Tuple:
        _A        =  self.tokenizer_class.from_pretrained(
            """facebook/wav2vec2-lv-60-espeak-cv-ft"""		,				word_delimiter_token=lowerCAmelCase_							)
        _A        =  """Hello how are you"""

        _A        =  tokenizer(lowerCAmelCase_		,				phonemizer_lang="""en-us"""							).input_ids
        _A        =  tokenizer(lowerCAmelCase_		,				phonemizer_lang="""fr-fr"""							).input_ids

        self.assertNotEqual(lowerCAmelCase_		,				lowerCAmelCase_							)

        _A        =  tokenizer.decode(lowerCAmelCase_							)
        _A        =  tokenizer.decode(lowerCAmelCase_							)

        self.assertEqual(lowerCAmelCase_		,				"""h ə l oʊ h aʊ ɑːɹ j uː"""							)
        self.assertEqual(lowerCAmelCase_		,				"""ɛ l o h aʊ a ʁ j u"""							)



 def      UpperCAmelCase							(					self							)  ->					Any:
        _A        =  self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""							)
        _A        =  """Hello how Are you"""
        _A        =  """hello how are you"""

        _A        =  tokenizer(lowerCAmelCase_							).input_ids
        _A        =  tokenizer(lowerCAmelCase_							).input_ids

        self.assertEqual(lowerCAmelCase_		,				lowerCAmelCase_							)



 def      UpperCAmelCase							(					self							)  ->					List[str]:
        _A        =  self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""							)
        tokenizer.add_tokens(["""!""", """?"""]							)
        tokenizer.add_special_tokens({"""cls_token""": """$$$"""}							)

        # fmt: off
        _A        =  [
            [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98, 3_92, 3_92, 3_93, 3_92, 3_92, 3_93, 3_94, 3_94],
            [24, 22, 5, 24, 22, 5, 77, tokenizer.pad_token_id, 3_94, 3_94],
        ]
        # fmt: on

        _A        =  tokenizer.batch_decode(lowerCAmelCase_							)
        self.assertEqual(lowerCAmelCase_		,				["""k s ɾ ɾ l ɭʲ!?!? $$$""", """j ð s j ð s oːɹ $$$"""]							)



 @staticmethod
 def      UpperCAmelCase							(					lowerCAmelCase_		,				lowerCAmelCase_							)  ->					List[str]:
        _A        =  [d[key] for d in offsets]
        return retrieved_list



 def      UpperCAmelCase							(					self							)  ->					Tuple:
        _A        =  self.get_tokenizer(word_delimiter_token="""|"""							)
        tokenizer.add_tokens("""|"""							)

        # fmt: off
        # ksssɾɾ|ɾɾ<pad>ɾɾ|<pad>ɾlll|ɭʲ -> k s ɾ ɾ | ɾ l | ɭʲ"
        _A        =  [11, 5, 5, 5, 15, 15, tokenizer.pad_token_id, 15, 15, tokenizer.word_delimiter_token_id, tokenizer.pad_token_id, 15, 8, 8, 8, tokenizer.word_delimiter_token_id, 98]
        # fmt: on

        _A        =  tokenizer.decode(lowerCAmelCase_		,				output_char_offsets=lowerCAmelCase_		,				filter_word_delimiter_token=lowerCAmelCase_							)
        # check Wav2Vec2CTCTokenizerOutput keys for char
        self.assertEqual(len(outputs.keys()							)		,				2							)
        self.assertTrue("""text""" in outputs							)
        self.assertTrue("""char_offsets""" in outputs							)
        self.assertTrue(isinstance(lowerCAmelCase_		,				lowerCAmelCase_							)							)

        # check that order of chars is correct and identical for both outputs
        self.assertEqual(""" """.join(self.get_from_offsets(outputs["""char_offsets"""]		,				"""char"""							)							)		,				outputs.text							)
        self.assertListEqual(
            self.get_from_offsets(outputs["""char_offsets"""]		,				"""char"""							)		,				["""k""", """s""", """ɾ""", """ɾ""", """|""", """ɾ""", """l""", """|""", """ɭʲ"""]							)

        # check that offsets are actually correct for char
        # 0-1 is 11, 1-4 is 5, 4-6 is first 15, 6-7 is <pad> (thus not shown), 7-9 is second 15, 9-10 is word_delimiter_token,
        # 10-11 is <pad> (thus not shown), 11-12 is third 15, 12-15 is 8, 15-16 is word_delimiter_token, 16-17 is 98
        self.assertListEqual(
            self.get_from_offsets(outputs["""char_offsets"""]		,				"""start_offset"""							)		,				[0, 1, 4, 7, 9, 11, 12, 15, 16]							)
        self.assertListEqual(
            self.get_from_offsets(outputs["""char_offsets"""]		,				"""end_offset"""							)		,				[1, 4, 6, 9, 10, 12, 15, 16, 17]							)



 def      UpperCAmelCase							(					self							)  ->					Optional[int]:
        _A        =  self.get_tokenizer(word_delimiter_token="""|"""							)

        def check_list_tuples_equal(lowerCAmelCase_		,				lowerCAmelCase_							):
               self.assertTrue(isinstance(lowerCAmelCase_		,				lowerCAmelCase_							)							)
               self.assertTrue(isinstance(outputs_list[0]		,				lowerCAmelCase_							)							)

               # transform list to ModelOutput
               _A        =  WavaVecaPhonemeCTCTokenizerOutput(
                   {k: [d[k] for d in outputs_list] for k in outputs_list[0]}							)

               self.assertListEqual(outputs_batch["""text"""]		,				outputs_batch_a["""text"""]							)

               def recursive_check(lowerCAmelCase_		,				lowerCAmelCase_							):
                      if isinstance(lowerCAmelCase_		,				lowerCAmelCase_							):
                             [recursive_check(lowerCAmelCase_		,				lowerCAmelCase_							) for la, la in zip(lowerCAmelCase_		,				lowerCAmelCase_							)]
                      self.assertEqual(lowerCAmelCase_		,				lowerCAmelCase_							)

               if "char_offsets" in outputs_batch:
                      recursive_check(outputs_batch["""char_offsets"""]		,				outputs_batch_a["""char_offsets"""]							)

        # fmt: off
        _A        =  [
            [11, 5, 15, tokenizer.pad_token_id, 15, 4, 8, 98, 32, 32, 32, 32, 4, 33, tokenizer.word_delimiter_token_id, 32, 32, 33, 34, 34],
            [24, 22, 5, tokenizer.word_delimiter_token_id, tokenizer.word_delimiter_token_id, 24, 22, 22, 22, 4, 5, 77, tokenizer.pad_token_id, 22, 22, 4, 34, 34, 34, 34],
        ]
        # fmt: on

        # We assume that `decode` works as expected. All we will check now is
        # the output type is correct and the output is identical to `decode`

        # char
        _A        =  tokenizer.batch_decode(lowerCAmelCase_		,				output_char_offsets=lowerCAmelCase_							)
        _A        =  [tokenizer.decode(lowerCAmelCase_		,				output_char_offsets=lowerCAmelCase_							) for ids in sample_ids]
        check_list_tuples_equal(lowerCAmelCase_		,				lowerCAmelCase_							)



 @unittest.skip("""Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes"""							)
 def      UpperCAmelCase							(					self							)  ->					int:
        pass



 @unittest.skip("""Wav2Vec2PhonemeTokenizer always puts spaces between phonemes"""							)
 def      UpperCAmelCase							(					self							)  ->					List[str]:
        pass



 @unittest.skip("""encodes to text to ids, but decodes ids to phonemes -> not possible to have internal consistency"""							)
 def      UpperCAmelCase							(					self							)  ->					List[Any]:
        pass



 @unittest.skip("""Wav2Vec2PhonemeModel has no max model length => no testing"""							)
 def      UpperCAmelCase							(					self							)  ->					Optional[int]:
        pass



 def      UpperCAmelCase							(					self							)  ->					List[Any]:
        _A        =  self.get_tokenizers(do_lower_case=lowerCAmelCase_							)
        for tokenizer in tokenizers:
               with self.subTest(F'''{tokenizer.__class__.__name__}'''							):
                      _A        =  tokenizer.vocab_size
                      _A        =  len(lowerCAmelCase_							)

                      self.assertNotEqual(lowerCAmelCase_		,				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)

                      _A        =  ["""aaaaa bbbbbb""", """cccccccccdddddddd"""]
                      _A        =  tokenizer.add_tokens(lowerCAmelCase_							)
                      _A        =  tokenizer.vocab_size
                      _A        =  len(lowerCAmelCase_							)

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

                      _A        =  tokenizer.encode("""aaaaa bbbbbb low cccccccccdddddddd l"""		,				add_special_tokens=lowerCAmelCase_							)

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

                      _A        =  {"""eos_token""": """>>>>|||<||<<|<<""", """pad_token""": """<<<<<|||>|>>>>|>"""}
                      _A        =  tokenizer.add_special_tokens(lowerCAmelCase_							)
                      _A        =  tokenizer.vocab_size
                      _A        =  len(lowerCAmelCase_							)

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

                      _A        =  tokenizer.encode(
                          """>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l"""		,				add_special_tokens=lowerCAmelCase_							)

                      self.assertGreaterEqual(len(lowerCAmelCase_							)		,				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							)



 @unittest.skip("""The tokenizer shouldn't be used to encode input IDs (except for labels), only to decode."""							)
 def      UpperCAmelCase							(					self							)  ->					List[Any]:
        pass



 @unittest.skip("""The tokenizer shouldn't be used to encode input IDs (except for labels), only to decode."""							)
 def      UpperCAmelCase							(					self							)  ->					Union[str, Any]:
        pass



 def      UpperCAmelCase							(					self							)  ->					str:
        # The default common tokenizer tests assumes that the output of `convert_tokens_to_string` is a string which
        # is not the case for Wav2Vec2PhonemeCTCTokenizer.
        _A        =  self.get_tokenizers(fast=lowerCAmelCase_		,				do_lower_case=lowerCAmelCase_							)
        for tokenizer in tokenizers:
               with self.subTest(F'''{tokenizer.__class__.__name__}'''							):
                      _A        =  ["""ð""", """ɪ""", """s""", """ɪ""", """z""", """ɐ""", """t""", """ɛ""", """k""", """s""", """t"""]
                      _A        =  tokenizer.convert_tokens_to_string(lowerCAmelCase_							)

                      self.assertIsInstance(output["""text"""]		,				lowerCAmelCase_							)




