
"""simple docstring"""




def lowercase_						(     _snake_case     ,_snake_case		):
							if len(_snake_case		) != len(_snake_case		):
														raise ValueError("""String lengths must match!"""		)

							SCREAMING_SNAKE_CASE__		: List[Any]     =     0

							for chara, chara in zip(_snake_case     ,_snake_case		):
														if chara != chara:
																					count += 1

							return count


if __name__ == "__main__":
	import doctest

	doctest.testmod()






"""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 			lowerCAmelCase_		(a__				,      unittest.TestCase						):


				"""simple docstring"""



				__UpperCamelCase   :		List[str]       =     WavaVecaPhonemeCTCTokenizer
				__UpperCamelCase   :		int       =     False



				def 			__magic_name__					(self					)      ->	Tuple:



											"""simple docstring"""




											super().setUp()

											SCREAMING_SNAKE_CASE__		: List[str]     =     (
											    """<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(""" """					)
											SCREAMING_SNAKE_CASE__		: List[str]     =     dict(zip(SCREAMING_SNAKE_CASE__     , range(len(SCREAMING_SNAKE_CASE__					)					)					)					)

											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     {"""pad_token""": """<pad>""", """unk_token""": """<unk>""", """bos_token""": """<s>""", """eos_token""": """</s>"""}

											SCREAMING_SNAKE_CASE__		: Dict     =     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(SCREAMING_SNAKE_CASE__					) + """\n"""					)



				def 			__magic_name__					(self     , SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__=False     , SCREAMING_SNAKE_CASE__=20     , SCREAMING_SNAKE_CASE__=5					)      ->	Tuple[str, list]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: List[str]     =     [(i, tokenizer.decode([i]     , clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__					)) for i in range(len(SCREAMING_SNAKE_CASE__					)					)]
											SCREAMING_SNAKE_CASE__		: Tuple     =     list(filter(lambda SCREAMING_SNAKE_CASE__					: [t[0]] == tokenizer.encode(t[1]     , do_phonemize=SCREAMING_SNAKE_CASE__					)     , SCREAMING_SNAKE_CASE__					)					)
											if max_length is not None and len(SCREAMING_SNAKE_CASE__					) > max_length:
																		SCREAMING_SNAKE_CASE__		: Tuple     =     toks[:max_length]
											if min_length is not None and len(SCREAMING_SNAKE_CASE__					) < min_length and len(SCREAMING_SNAKE_CASE__					) > 0:
																		while len(SCREAMING_SNAKE_CASE__					) < min_length:
																									SCREAMING_SNAKE_CASE__		: Optional[Any]     =     toks + toks
        # toks_str = [t[1] for t in toks]
											SCREAMING_SNAKE_CASE__		: Any     =     [t[0] for t in toks]

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



				def 			__magic_name__					(self     , **SCREAMING_SNAKE_CASE__					)      ->	Dict:



											"""simple docstring"""




											kwargs.update(self.special_tokens_map					)
											return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname     , **SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self					)      ->	Tuple:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""					)

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

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

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



				def 			__magic_name__					(self					)      ->	Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Tuple     =     self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""					)

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



				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Optional[int]     =     self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""					)

											SCREAMING_SNAKE_CASE__		: int     =     """Hello how are you"""
											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     tokenizer.phonemize(SCREAMING_SNAKE_CASE__     , phonemizer_lang="""en-us"""					)
											self.assertEqual(tokenizer(SCREAMING_SNAKE_CASE__					).input_ids     , tokenizer(SCREAMING_SNAKE_CASE__     , do_phonemize=SCREAMING_SNAKE_CASE__					).input_ids					)



				def 			__magic_name__					(self					)      ->	Tuple:



											"""simple docstring"""




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

											SCREAMING_SNAKE_CASE__		: Optional[int]     =     tokenizer.decode(tokenizer(SCREAMING_SNAKE_CASE__					).input_ids					)

											self.assertEqual(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self					)      ->	Dict:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Optional[int]     =     self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""					)

											SCREAMING_SNAKE_CASE__		: Dict     =     [
											    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
											    [24, 22, 5, 24, 22, 5, 77],
											]
											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     tokenizer.decode(sample_ids[0]					)
											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     tokenizer.batch_decode(SCREAMING_SNAKE_CASE__					)
											self.assertEqual(SCREAMING_SNAKE_CASE__     , batch_tokens[0]					)
											self.assertEqual(SCREAMING_SNAKE_CASE__     , ["""k s ɾ ɾ l ɭʲ""", """j ð s j ð s oːɹ"""]					)



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



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: int     =     self.tokenizer_class.from_pretrained(
											    """facebook/wav2vec2-lv-60-espeak-cv-ft"""     , word_delimiter_token="""|"""					)
											tokenizer.add_tokens("""|"""					)

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



				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




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

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



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



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Optional[int]     =     self.tokenizer_class.from_pretrained(
											    """facebook/wav2vec2-lv-60-espeak-cv-ft"""     , word_delimiter_token="""|"""					)
											tokenizer.add_tokens("""|"""					)

											# fmt: off
											SCREAMING_SNAKE_CASE__		: Union[str, 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
											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     tokenizer.decode(sample_ids[0]					)
											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     tokenizer.batch_decode(SCREAMING_SNAKE_CASE__					)
											self.assertEqual(SCREAMING_SNAKE_CASE__     , batch_tokens[0]					)
											self.assertEqual(SCREAMING_SNAKE_CASE__     , ["""k s ɾ ɾ l ɭʲ""", """j ð s j ð s oːɹ"""]					)

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



				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




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

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

											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     tokenizer.decode(tokenizer(SCREAMING_SNAKE_CASE__					).input_ids     , filter_word_delimiter_token=SCREAMING_SNAKE_CASE__					)

											self.assertEqual(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



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



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: int     =     self.tokenizer_class.from_pretrained(
											    """facebook/wav2vec2-lv-60-espeak-cv-ft"""     , word_delimiter_token="""|"""					)
											tokenizer.add_tokens("""|"""					)

											SCREAMING_SNAKE_CASE__		: Optional[int]     =     """Hello how are you"""
											SCREAMING_SNAKE_CASE__		: Optional[int]     =     tokenizer.phonemize(SCREAMING_SNAKE_CASE__     , phonemizer_lang="""en-us"""					)

											SCREAMING_SNAKE_CASE__		: int     =     tokenizer.decode(tokenizer(SCREAMING_SNAKE_CASE__					).input_ids     , filter_word_delimiter_token=SCREAMING_SNAKE_CASE__					)

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



				def 			__magic_name__					(self					)      ->	int:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Any     =     self.tokenizer_class.from_pretrained(
											    """facebook/wav2vec2-lv-60-espeak-cv-ft"""     , word_delimiter_token=SCREAMING_SNAKE_CASE__					)
											SCREAMING_SNAKE_CASE__		: str     =     """Hello how are you"""

											SCREAMING_SNAKE_CASE__		: List[str]     =     tokenizer(SCREAMING_SNAKE_CASE__     , phonemizer_lang="""en-us"""					).input_ids
											SCREAMING_SNAKE_CASE__		: Tuple     =     tokenizer(SCREAMING_SNAKE_CASE__     , phonemizer_lang="""fr-fr"""					).input_ids

											self.assertNotEqual(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)

											SCREAMING_SNAKE_CASE__		: Optional[int]     =     tokenizer.decode(SCREAMING_SNAKE_CASE__					)
											SCREAMING_SNAKE_CASE__		: List[str]     =     tokenizer.decode(SCREAMING_SNAKE_CASE__					)

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



				def 			__magic_name__					(self					)      ->	Tuple:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""					)
											SCREAMING_SNAKE_CASE__		: Tuple     =     """Hello how Are you"""
											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     """hello how are you"""

											SCREAMING_SNAKE_CASE__		: str     =     tokenizer(SCREAMING_SNAKE_CASE__					).input_ids
											SCREAMING_SNAKE_CASE__		: List[str]     =     tokenizer(SCREAMING_SNAKE_CASE__					).input_ids

											self.assertEqual(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



				def 			__magic_name__					(self					)      ->	Tuple:



											"""simple docstring"""




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

											# fmt: off
											SCREAMING_SNAKE_CASE__		: List[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

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



				@staticmethod
				def 			__magic_name__					(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)      ->	Any:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: List[Any]     =     [d[key] for d in offsets]
											return retrieved_list



				def 			__magic_name__					(self					)      ->	int:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Union[str, 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"
											SCREAMING_SNAKE_CASE__		: List[str]     =     [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

											SCREAMING_SNAKE_CASE__		: int     =     tokenizer.decode(SCREAMING_SNAKE_CASE__     , output_char_offsets=SCREAMING_SNAKE_CASE__     , filter_word_delimiter_token=SCREAMING_SNAKE_CASE__					)
											# 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(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)					)

											# 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 			__magic_name__					(self					)      ->	str:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Dict     =     self.get_tokenizer(word_delimiter_token="""|"""					)

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

																		# transform list to ModelOutput
																		SCREAMING_SNAKE_CASE__		: 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(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					):
																									if isinstance(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					):
																																[recursive_check(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					) for la, la in zip(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)]
																									self.assertEqual(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)

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

        # fmt: off
											SCREAMING_SNAKE_CASE__		: List[Any]     =     [
											    [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
											SCREAMING_SNAKE_CASE__		: int     =     tokenizer.batch_decode(SCREAMING_SNAKE_CASE__     , output_char_offsets=SCREAMING_SNAKE_CASE__					)
											SCREAMING_SNAKE_CASE__		: Optional[int]     =     [tokenizer.decode(SCREAMING_SNAKE_CASE__     , output_char_offsets=SCREAMING_SNAKE_CASE__					) for ids in sample_ids]
											check_list_tuples_equal(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					)



				@unittest.skip("""Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes"""					)
				def 			__magic_name__					(self					)      ->	Optional[int]:



											"""simple docstring"""




											pass



				@unittest.skip("""Wav2Vec2PhonemeTokenizer always puts spaces between phonemes"""					)
				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




											pass



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



											"""simple docstring"""




											pass



				@unittest.skip("""Wav2Vec2PhonemeModel has no max model length => no testing"""					)
				def 			__magic_name__					(self					)      ->	Any:



											"""simple docstring"""




											pass



				def 			__magic_name__					(self					)      ->	int:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Tuple     =     self.get_tokenizers(do_lower_case=SCREAMING_SNAKE_CASE__					)
											for tokenizer in tokenizers:
																		with self.subTest(F'''{tokenizer.__class__.__name__}'''					):
																									SCREAMING_SNAKE_CASE__		: Tuple     =     tokenizer.vocab_size
																									SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     len(SCREAMING_SNAKE_CASE__					)

																									self.assertNotEqual(SCREAMING_SNAKE_CASE__     , 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__		: Tuple     =     ["""aaaaa bbbbbb""", """cccccccccdddddddd"""]
																									SCREAMING_SNAKE_CASE__		: Tuple     =     tokenizer.add_tokens(SCREAMING_SNAKE_CASE__					)
																									SCREAMING_SNAKE_CASE__		: List[Any]     =     tokenizer.vocab_size
																									SCREAMING_SNAKE_CASE__		: List[Any]     =     len(SCREAMING_SNAKE_CASE__					)

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

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

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

																									SCREAMING_SNAKE_CASE__		: List[Any]     =     {"""eos_token""": """>>>>|||<||<<|<<""", """pad_token""": """<<<<<|||>|>>>>|>"""}
																									SCREAMING_SNAKE_CASE__		: Any     =     tokenizer.add_special_tokens(SCREAMING_SNAKE_CASE__					)
																									SCREAMING_SNAKE_CASE__		: Any     =     tokenizer.vocab_size
																									SCREAMING_SNAKE_CASE__		: Any     =     len(SCREAMING_SNAKE_CASE__					)

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

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

																									self.assertGreaterEqual(len(SCREAMING_SNAKE_CASE__					)     , 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 			__magic_name__					(self					)      ->	Union[str, Any]:



											"""simple docstring"""




											pass



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



											"""simple docstring"""




											pass



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



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__		: Tuple     =     self.get_tokenizers(fast=SCREAMING_SNAKE_CASE__     , do_lower_case=SCREAMING_SNAKE_CASE__					)
											for tokenizer in tokenizers:
																		with self.subTest(F'''{tokenizer.__class__.__name__}'''					):
																									SCREAMING_SNAKE_CASE__		: List[Any]     =     ["""ð""", """ɪ""", """s""", """ɪ""", """z""", """ɐ""", """t""", """ɛ""", """k""", """s""", """t"""]
																									SCREAMING_SNAKE_CASE__		: List[str]     =     tokenizer.convert_tokens_to_string(SCREAMING_SNAKE_CASE__					)

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




