


'''simple docstring'''






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    __snake_case       (   _SCREAMING_SNAKE_CASE	,unittest.TestCase):







    """simple docstring"""



    lowercase    =					WavaVecaPhonemeCTCTokenizer
    lowercase    =					False

    def __lowercase   (   self    :  Union[str, Any]		)   ->  List[str]:
      super().setUp()

      lowerCAmelCase_			:      List[Any]			=   (
          """<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(""" """		)
      lowerCAmelCase_			:      str			=   dict(zip(lowerCamelCase    ,						range(len(lowerCamelCase		)		)		)		)

      lowerCAmelCase_			:      Optional[Any]			=   {"""pad_token""": """<pad>""", """unk_token""": """<unk>""", """bos_token""": """<s>""", """eos_token""": """</s>"""}

      lowerCAmelCase_			:      str			=   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 __lowercase   (   self    :  int    ,						lowerCamelCase    :  str    ,						lowerCamelCase    :  Dict=False    ,						lowerCamelCase    :  List[str]=20    ,						lowerCamelCase    :  Union[str, Any]=5		)   ->  Tuple[str, list]:
      lowerCAmelCase_			:      Dict			=   [(i, tokenizer.decode([i]    ,						clean_up_tokenization_spaces=lowerCamelCase		)) for i in range(len(lowerCamelCase		)		)]
      lowerCAmelCase_			:      Any			=   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:
        lowerCAmelCase_			:      Union[str, Any]			=   toks[:max_length]
      if min_length is not None and len(lowerCamelCase		) < min_length and len(lowerCamelCase		) > 0:
        while len(lowerCamelCase		) < min_length:
          lowerCAmelCase_			:      Union[str, Any]			=   toks + toks
        # toks_str = [t[1] for t in toks]
      lowerCAmelCase_			:      Union[str, Any]			=   [t[0] for t in toks]

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

    def __lowercase   (   self    :  Tuple    ,						**lowerCamelCase    :  Union[str, Any]		)   ->  Optional[int]:
      kwargs.update(self.special_tokens_map		)
      return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname    ,						**lowerCamelCase		)

    def __lowercase   (   self    :  int		)   ->  List[str]:
      lowerCAmelCase_			:      Union[str, Any]			=   self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""		)

      # check adding a single token
      tokenizer.add_tokens("""xxx"""		)
      lowerCAmelCase_			:      List[Any]			=   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"""]		)
      lowerCAmelCase_			:      Tuple			=   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

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

    def __lowercase   (   self    :  Any		)   ->  List[str]:
      lowerCAmelCase_			:      Union[str, Any]			=   self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""		)

      lowerCAmelCase_			:      Optional[Any]			=   """Hello how are you"""
      lowerCAmelCase_			:      Tuple			=   tokenizer.phonemize(lowerCamelCase    ,						phonemizer_lang="""en-us"""		)
      self.assertEqual(lowerCamelCase    ,						"""h ə l oʊ h aʊ ɑːɹ j uː"""		)

    def __lowercase   (   self    :  int		)   ->  str:
      lowerCAmelCase_			:      Union[str, Any]			=   self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""		)

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

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

      lowerCAmelCase_			:      Union[str, Any]			=   tokenizer.decode(tokenizer(lowerCamelCase		).input_ids		)

      self.assertEqual(lowerCamelCase    ,						lowerCamelCase		)

    def __lowercase   (   self    :  Union[str, Any]		)   ->  Union[str, Any]:
      lowerCAmelCase_			:      Any			=   self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""		)

      lowerCAmelCase_			:      List[str]			=   [
          [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
          [24, 22, 5, 24, 22, 5, 77],
      ]
      lowerCAmelCase_			:      List[Any]			=   tokenizer.decode(sample_ids[0]		)
      lowerCAmelCase_			:      Optional[int]			=   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 __lowercase   (   self    :  Tuple		)   ->  Dict:
      lowerCAmelCase_			:      List[str]			=   self.tokenizer_class.from_pretrained(
          """facebook/wav2vec2-lv-60-espeak-cv-ft"""    ,						word_delimiter_token="""|"""		)
      tokenizer.add_tokens("""|"""		)

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

    def __lowercase   (   self    :  List[str]		)   ->  int:
      lowerCAmelCase_			:      Optional[int]			=   self.tokenizer_class.from_pretrained(
          """facebook/wav2vec2-lv-60-espeak-cv-ft"""    ,						word_delimiter_token="""|"""		)
      tokenizer.add_tokens("""|"""		)

      lowerCAmelCase_			:      str			=   """Hello how are you"""
      lowerCAmelCase_			:      List[str]			=   tokenizer.phonemize(lowerCamelCase    ,						phonemizer_lang="""en-us"""		)
      self.assertEqual(tokenizer(lowerCamelCase		).input_ids    ,						tokenizer(lowerCamelCase    ,						do_phonemize=lowerCamelCase		).input_ids		)

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

      # fmt: off
      lowerCAmelCase_			:      Optional[Any]			=   [
          [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
      lowerCAmelCase_			:      List[str]			=   tokenizer.decode(sample_ids[0]		)
      lowerCAmelCase_			:      Optional[int]			=   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
      lowerCAmelCase_			:      Union[str, Any]			=   tokenizer.decode(sample_ids[0]    ,						filter_word_delimiter_token=lowerCamelCase		)
      lowerCAmelCase_			:      Optional[Any]			=   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 __lowercase   (   self    :  Optional[Any]		)   ->  int:
      lowerCAmelCase_			:      Tuple			=   self.tokenizer_class.from_pretrained(
          """facebook/wav2vec2-lv-60-espeak-cv-ft"""    ,						word_delimiter_token="""|"""		)
      tokenizer.add_tokens("""|"""		)

      lowerCAmelCase_			:      Optional[Any]			=   """Hello how are you"""
      lowerCAmelCase_			:      List[Any]			=   tokenizer.phonemize(lowerCamelCase    ,						phonemizer_lang="""en-us"""		)

      lowerCAmelCase_			:      Any			=   tokenizer.decode(tokenizer(lowerCamelCase		).input_ids    ,						filter_word_delimiter_token=lowerCamelCase		)

      self.assertEqual(lowerCamelCase    ,						lowerCamelCase		)

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

      lowerCAmelCase_			:      Union[str, Any]			=   """Hello how are you"""
      lowerCAmelCase_			:      Optional[int]			=   tokenizer.phonemize(lowerCamelCase    ,						phonemizer_lang="""en-us"""		)

      lowerCAmelCase_			:      Dict			=   tokenizer.decode(tokenizer(lowerCamelCase		).input_ids    ,						filter_word_delimiter_token=lowerCamelCase		)

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

    def __lowercase   (   self    :  Optional[int]		)   ->  int:
      lowerCAmelCase_			:      Dict			=   self.tokenizer_class.from_pretrained(
          """facebook/wav2vec2-lv-60-espeak-cv-ft"""    ,						word_delimiter_token=lowerCamelCase		)
      lowerCAmelCase_			:      List[str]			=   """Hello how are you"""

      lowerCAmelCase_			:      Tuple			=   tokenizer(lowerCamelCase    ,						phonemizer_lang="""en-us"""		).input_ids
      lowerCAmelCase_			:      List[Any]			=   tokenizer(lowerCamelCase    ,						phonemizer_lang="""fr-fr"""		).input_ids

      self.assertNotEqual(lowerCamelCase    ,						lowerCamelCase		)

      lowerCAmelCase_			:      Optional[Any]			=   tokenizer.decode(lowerCamelCase		)
      lowerCAmelCase_			:      Optional[int]			=   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 __lowercase   (   self    :  List[Any]		)   ->  List[Any]:
      lowerCAmelCase_			:      List[str]			=   self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""		)
      lowerCAmelCase_			:      Dict			=   """Hello how Are you"""
      lowerCAmelCase_			:      int			=   """hello how are you"""

      lowerCAmelCase_			:      List[str]			=   tokenizer(lowerCamelCase		).input_ids
      lowerCAmelCase_			:      int			=   tokenizer(lowerCamelCase		).input_ids

      self.assertEqual(lowerCamelCase    ,						lowerCamelCase		)

    def __lowercase   (   self    :  Union[str, Any]		)   ->  Optional[int]:
      lowerCAmelCase_			:      Optional[int]			=   self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""		)
      tokenizer.add_tokens(["""!""", """?"""]		)
      tokenizer.add_special_tokens({"""cls_token""": """$$$"""}		)

      # fmt: off
      lowerCAmelCase_			:      Any			=   [
          [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

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

    @staticmethod
    def __lowercase   (   lowerCamelCase    :  Dict    ,						lowerCamelCase    :  Optional[int]		)   ->  Any:
      lowerCAmelCase_			:      Union[str, Any]			=   [d[key] for d in offsets]
      return retrieved_list

    def __lowercase   (   self    :  Union[str, Any]		)   ->  int:
      lowerCAmelCase_			:      Optional[Any]			=   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"
      lowerCAmelCase_			:      Optional[int]			=   [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

      lowerCAmelCase_			:      Optional[int]			=   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 __lowercase   (   self    :  Dict		)   ->  Union[str, Any]:
      lowerCAmelCase_			:      Tuple			=   self.get_tokenizer(word_delimiter_token="""|"""		)

      def check_list_tuples_equal(lowerCamelCase    :  Optional[int]    ,						lowerCamelCase    :  List[str]		):
        self.assertTrue(isinstance(lowerCamelCase    ,						lowerCamelCase		)		)
        self.assertTrue(isinstance(outputs_list[0]    ,						lowerCamelCase		)		)

        # transform list to ModelOutput
        lowerCAmelCase_			:      Optional[int]			=   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    :  Dict    ,						lowerCamelCase    :  Tuple		):
          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
      lowerCAmelCase_			:      Tuple			=   [
          [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
      lowerCAmelCase_			:      Dict			=   tokenizer.batch_decode(lowerCamelCase    ,						output_char_offsets=lowerCamelCase		)
      lowerCAmelCase_			:      Dict			=   [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 __lowercase   (   self    :  Tuple		)   ->  Union[str, Any]:
      pass

    @unittest.skip("""Wav2Vec2PhonemeTokenizer always puts spaces between phonemes"""		)
    def __lowercase   (   self    :  Dict		)   ->  Dict:
      pass

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

    @unittest.skip("""Wav2Vec2PhonemeModel has no max model length => no testing"""		)
    def __lowercase   (   self    :  List[Any]		)   ->  List[str]:
      pass

    def __lowercase   (   self    :  Optional[Any]		)   ->  List[str]:
      lowerCAmelCase_			:      int			=   self.get_tokenizers(do_lower_case=lowerCamelCase		)
      for tokenizer in tokenizers:
        with self.subTest(F'{tokenizer.__class__.__name__}'		):
          lowerCAmelCase_			:      Dict			=   tokenizer.vocab_size
          lowerCAmelCase_			:      Tuple			=   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)

          lowerCAmelCase_			:      Dict			=   ["""aaaaa bbbbbb""", """cccccccccdddddddd"""]
          lowerCAmelCase_			:      List[Any]			=   tokenizer.add_tokens(lowerCamelCase		)
          lowerCAmelCase_			:      Any			=   tokenizer.vocab_size
          lowerCAmelCase_			:      Tuple			=   len(lowerCamelCase		)

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

          lowerCAmelCase_			:      Any			=   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		)

          lowerCAmelCase_			:      List[str]			=   {"""eos_token""": """>>>>|||<||<<|<<""", """pad_token""": """<<<<<|||>|>>>>|>"""}
          lowerCAmelCase_			:      int			=   tokenizer.add_special_tokens(lowerCamelCase		)
          lowerCAmelCase_			:      Dict			=   tokenizer.vocab_size
          lowerCAmelCase_			:      List[Any]			=   len(lowerCamelCase		)

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

          lowerCAmelCase_			:      Dict			=   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 __lowercase   (   self    :  Dict		)   ->  int:
      pass

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





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

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







'''simple docstring'''






import re
import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase    =					['image_processor', 'tokenizer']
    lowercase    =					'AutoImageProcessor'
    lowercase    =					'AutoTokenizer'

    def __init__(   self    :  int    ,						lowerCamelCase    :  List[str]=None    ,						lowerCamelCase    :  Union[str, Any]=None    ,						**lowerCamelCase    :  str		)   ->  Tuple:
      lowerCAmelCase_			:      str			=   None
      if "feature_extractor" in kwargs:
        warnings.warn(
            """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
            """ instead."""    ,						lowerCamelCase    ,						)
        lowerCAmelCase_			:      Tuple			=   kwargs.pop("""feature_extractor"""		)

      lowerCAmelCase_			:      Tuple			=   image_processor if image_processor is not None else feature_extractor
      if image_processor is None:
        raise ValueError("""You need to specify an `image_processor`."""		)
      if tokenizer is None:
        raise ValueError("""You need to specify a `tokenizer`."""		)

      super().__init__(lowerCamelCase    ,						lowerCamelCase		)
      lowerCAmelCase_			:      Optional[int]			=   self.image_processor
      lowerCAmelCase_			:      Any			=   False

    def __call__(   self    :  List[Any]    ,						*lowerCamelCase    :  str    ,						**lowerCamelCase    :  Tuple		)   ->  Union[str, Any]:
      # For backward compatibility
      if self._in_target_context_manager:
        return self.current_processor(*lowerCamelCase    ,						**lowerCamelCase		)

      lowerCAmelCase_			:      Any			=   kwargs.pop("""images"""    ,						lowerCamelCase		)
      lowerCAmelCase_			:      Dict			=   kwargs.pop("""text"""    ,						lowerCamelCase		)
      if len(lowerCamelCase		) > 0:
        lowerCAmelCase_			:      str			=   args[0]
        lowerCAmelCase_			:      Dict			=   args[1:]

      if images is None and text is None:
        raise ValueError("""You need to specify either an `images` or `text` input to process."""		)

      if images is not None:
        lowerCAmelCase_			:      Any			=   self.image_processor(lowerCamelCase    ,						*lowerCamelCase    ,						**lowerCamelCase		)
      if text is not None:
        lowerCAmelCase_			:      str			=   self.tokenizer(lowerCamelCase    ,						**lowerCamelCase		)

      if text is None:
        return inputs
      elif images is None:
        return encodings
      else:
        lowerCAmelCase_			:      Dict			=   encodings["""input_ids"""]
        return inputs

    def __lowercase   (   self    :  str    ,						*lowerCamelCase    :  Union[str, Any]    ,						**lowerCamelCase    :  Union[str, Any]		)   ->  List[str]:
      return self.tokenizer.batch_decode(*lowerCamelCase    ,						**lowerCamelCase		)

    def __lowercase   (   self    :  List[Any]    ,						*lowerCamelCase    :  Any    ,						**lowerCamelCase    :  Union[str, Any]		)   ->  List[str]:
      return self.tokenizer.decode(*lowerCamelCase    ,						**lowerCamelCase		)

    @contextmanager
    def __lowercase   (   self    :  str		)   ->  Union[str, Any]:
      warnings.warn(
          """`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your """
          """labels by using the argument `text` of the regular `__call__` method (either in the same call as """
          """your images inputs, or in a separate call."""		)
      lowerCAmelCase_			:      List[str]			=   True
      lowerCAmelCase_			:      Optional[Any]			=   self.tokenizer
      yield
      lowerCAmelCase_			:      List[Any]			=   self.image_processor
      lowerCAmelCase_			:      List[str]			=   False

    def __lowercase   (   self    :  Dict    ,						lowerCamelCase    :  List[str]    ,						lowerCamelCase    :  str=False    ,						lowerCamelCase    :  List[Any]=None		)   ->  Optional[int]:
      if added_vocab is None:
        lowerCAmelCase_			:      str			=   self.tokenizer.get_added_vocab()

      lowerCAmelCase_			:      Union[str, Any]			=   {}

      while tokens:
        lowerCAmelCase_			:      Dict			=   re.search(R"""<s_(.*?)>"""    ,						lowerCamelCase    ,						re.IGNORECASE		)
        if start_token is None:
          break
        lowerCAmelCase_			:      Tuple			=   start_token.group(1		)
        lowerCAmelCase_			:      Tuple			=   re.search(RF'</s_{key}>'    ,						lowerCamelCase    ,						re.IGNORECASE		)
        lowerCAmelCase_			:      Tuple			=   start_token.group()
        if end_token is None:
          lowerCAmelCase_			:      str			=   tokens.replace(lowerCamelCase    ,						""""""		)
        else:
          lowerCAmelCase_			:      List[str]			=   end_token.group()
          lowerCAmelCase_			:      Dict			=   re.escape(lowerCamelCase		)
          lowerCAmelCase_			:      int			=   re.escape(lowerCamelCase		)
          lowerCAmelCase_			:      Dict			=   re.search(F'{start_token_escaped}(.*?){end_token_escaped}'    ,						lowerCamelCase    ,						re.IGNORECASE		)
          if content is not None:
            lowerCAmelCase_			:      str			=   content.group(1		).strip()
            if r"<s_" in content and r"</s_" in content:  # non-leaf node
              lowerCAmelCase_			:      str			=   self.tokenajson(lowerCamelCase    ,						is_inner_value=lowerCamelCase    ,						added_vocab=lowerCamelCase		)
              if value:
                if len(lowerCamelCase		) == 1:
                  lowerCAmelCase_			:      List[Any]			=   value[0]
                lowerCAmelCase_			:      Optional[Any]			=   value
            else:  # leaf nodes
              lowerCAmelCase_			:      List[str]			=   []
              for leaf in content.split(R"""<sep/>"""		):
                lowerCAmelCase_			:      Union[str, Any]			=   leaf.strip()
                if leaf in added_vocab and leaf[0] == "<" and leaf[-2:] == "/>":
                  lowerCAmelCase_			:      Any			=   leaf[1:-2]  # for categorical special tokens
                output[key].append(lowerCamelCase		)
              if len(output[key]		) == 1:
                lowerCAmelCase_			:      Optional[Any]			=   output[key][0]

          lowerCAmelCase_			:      List[Any]			=   tokens[tokens.find(lowerCamelCase		) + len(lowerCamelCase		) :].strip()
          if tokens[:6] == r"<sep/>":  # non-leaf nodes
            return [output] + self.tokenajson(tokens[6:]    ,						is_inner_value=lowerCamelCase    ,						added_vocab=lowerCamelCase		)

      if len(lowerCamelCase		):
        return [output] if is_inner_value else output
      else:
        return [] if is_inner_value else {"text_sequence": tokens}

    @property
    def __lowercase   (   self    :  Dict		)   ->  int:
      warnings.warn(
          """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""    ,						lowerCamelCase    ,						)
      return self.image_processor_class





    @property
    def __lowercase   (   self    :  Dict		)   ->  Optional[Any]:
      warnings.warn(
          """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""    ,						lowerCamelCase    ,						)
      return self.image_processor



