




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    (		_lowerCamelCase				,unittest.TestCase						):






			'''simple docstring'''





			UpperCamelCase__								=WavaVecaPhonemeCTCTokenizer
			UpperCamelCase__								=False

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

								__magic_name__							:	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(''' '''  )
								__magic_name__							:	Union[str, Any]    							=							dict(zip(lowerCamelCase_       ,						range(len(lowerCamelCase_  )  )  )  )

								__magic_name__							:	Optional[int]    							=							{'''pad_token''': '''<pad>''', '''unk_token''': '''<unk>''', '''bos_token''': '''<s>''', '''eos_token''': '''</s>'''}

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

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

			def 							UpperCAmelCase__       ( self			:   Dict       ,						**lowerCamelCase_			:   Union[str, Any]  )						->   Optional[Any]:
								kwargs.update(self.special_tokens_map  )
								return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname       ,						**lowerCamelCase_  )

			def 							UpperCAmelCase__       ( self			:   Optional[Any]  )						->   Optional[Any]:
								__magic_name__							:	Dict    							=							self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )

								# check adding a single token
								tokenizer.add_tokens('''xxx'''  )
								__magic_name__							:	List[str]    							=							tokenizer('''m xxx ɪ'''       ,						do_phonemize=lowerCamelCase_  ).input_ids
								self.assertEqual(lowerCamelCase_       ,						[13, 392, 17]  )  # xxx should be last token

								tokenizer.add_tokens(['''aaa''', '''bbb''', '''ccc''']  )
								__magic_name__							:	List[Any]    							=							tokenizer('''m aaa ɪ ccc'''       ,						do_phonemize=lowerCamelCase_  ).input_ids
								self.assertEqual(lowerCamelCase_       ,						[13, 393, 17, 395]  )  # aaa and ccc should be after xxx and 2 after aaa

								__magic_name__							:	List[Any]    							=							tokenizer('''maɪ c'''       ,						do_phonemize=lowerCamelCase_  ).input_ids
								self.assertEqual(lowerCamelCase_       ,						[3, 200]  )  # mai should be <unk> (=3)

			def 							UpperCAmelCase__       ( self			:   Dict  )						->   Optional[Any]:
								__magic_name__							:	List[str]    							=							self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )

								__magic_name__							:	Any    							=							'''Hello how are you'''
								__magic_name__							:	Any    							=							tokenizer.phonemize(lowerCamelCase_       ,						phonemizer_lang='''en-us'''  )
								self.assertEqual(lowerCamelCase_       ,						'''h ə l oʊ h aʊ ɑːɹ j uː'''  )

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]  )						->   Optional[int]:
								__magic_name__							:	str    							=							self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )

								__magic_name__							:	List[Any]    							=							'''Hello how are you'''
								__magic_name__							:	Dict    							=							tokenizer.phonemize(lowerCamelCase_       ,						phonemizer_lang='''en-us'''  )
								self.assertEqual(tokenizer(lowerCamelCase_  ).input_ids       ,						tokenizer(lowerCamelCase_       ,						do_phonemize=lowerCamelCase_  ).input_ids  )

			def 							UpperCAmelCase__       ( self			:   int  )						->   Tuple:
								__magic_name__							:	Optional[Any]    							=							self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )
								__magic_name__							:	Tuple    							=							'''Hello how are you'''
								__magic_name__							:	Optional[Any]    							=							tokenizer.phonemize(lowerCamelCase_       ,						phonemizer_lang='''en-us'''  )

								__magic_name__							:	List[str]    							=							tokenizer.decode(tokenizer(lowerCamelCase_  ).input_ids  )

								self.assertEqual(lowerCamelCase_       ,						lowerCamelCase_  )

			def 							UpperCAmelCase__       ( self			:   Optional[int]  )						->   Optional[Any]:
								__magic_name__							:	List[str]    							=							self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )

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

								__magic_name__							:	Union[str, Any]    							=							'''Hello how are you'''
								__magic_name__							:	Any    							=							tokenizer.phonemize(lowerCamelCase_       ,						phonemizer_lang='''en-us'''  )
								self.assertEqual(lowerCamelCase_       ,						'''h ə l oʊ | h aʊ | ɑːɹ | j uː |'''  )

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]  )						->   int:
								__magic_name__							:	int    							=							self.tokenizer_class.from_pretrained(
								    '''facebook/wav2vec2-lv-60-espeak-cv-ft'''       ,						word_delimiter_token='''|'''  )
								tokenizer.add_tokens('''|'''  )

								__magic_name__							:	Optional[Any]    							=							'''Hello how are you'''
								__magic_name__							:	str    							=							tokenizer.phonemize(lowerCamelCase_       ,						phonemizer_lang='''en-us'''  )
								self.assertEqual(tokenizer(lowerCamelCase_  ).input_ids       ,						tokenizer(lowerCamelCase_       ,						do_phonemize=lowerCamelCase_  ).input_ids  )

			def 							UpperCAmelCase__       ( self			:   int  )						->   Dict:
								__magic_name__							:	Tuple    							=							self.tokenizer_class.from_pretrained(
								    '''facebook/wav2vec2-lv-60-espeak-cv-ft'''       ,						word_delimiter_token='''|'''  )
								tokenizer.add_tokens('''|'''  )

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

								__magic_name__							:	List[Any]    							=							'''Hello how are you'''
								__magic_name__							:	Dict    							=							tokenizer.phonemize(lowerCamelCase_       ,						phonemizer_lang='''en-us'''  )

								__magic_name__							:	Optional[Any]    							=							tokenizer.decode(tokenizer(lowerCamelCase_  ).input_ids       ,						filter_word_delimiter_token=lowerCamelCase_  )

								self.assertEqual(lowerCamelCase_       ,						lowerCamelCase_  )

			def 							UpperCAmelCase__       ( self			:   int  )						->   Dict:
								__magic_name__							:	str    							=							self.tokenizer_class.from_pretrained(
								    '''facebook/wav2vec2-lv-60-espeak-cv-ft'''       ,						word_delimiter_token='''|'''  )
								tokenizer.add_tokens('''|'''  )

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

								__magic_name__							:	Tuple    							=							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			:   Union[str, Any]  )						->   Any:
								__magic_name__							:	Optional[int]    							=							self.tokenizer_class.from_pretrained(
								    '''facebook/wav2vec2-lv-60-espeak-cv-ft'''       ,						word_delimiter_token=lowerCamelCase_  )
								__magic_name__							:	List[Any]    							=							'''Hello how are you'''

								__magic_name__							:	Union[str, Any]    							=							tokenizer(lowerCamelCase_       ,						phonemizer_lang='''en-us'''  ).input_ids
								__magic_name__							:	Any    							=							tokenizer(lowerCamelCase_       ,						phonemizer_lang='''fr-fr'''  ).input_ids

								self.assertNotEqual(lowerCamelCase_       ,						lowerCamelCase_  )

								__magic_name__							:	Union[str, Any]    							=							tokenizer.decode(lowerCamelCase_  )
								__magic_name__							:	Dict    							=							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			:   Optional[Any]  )						->   int:
								__magic_name__							:	Optional[Any]    							=							self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )
								__magic_name__							:	int    							=							'''Hello how Are you'''
								__magic_name__							:	Any    							=							'''hello how are you'''

								__magic_name__							:	Union[str, Any]    							=							tokenizer(lowerCamelCase_  ).input_ids
								__magic_name__							:	Dict    							=							tokenizer(lowerCamelCase_  ).input_ids

								self.assertEqual(lowerCamelCase_       ,						lowerCamelCase_  )

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

								# fmt: off
								__magic_name__							:	Union[str, Any]    							=							[
								    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98, 392, 392, 393, 392, 392, 393, 394, 394],
								    [24, 22, 5, 24, 22, 5, 77, tokenizer.pad_token_id, 394, 394],
								]
								# fmt: on

								__magic_name__							:	int    							=							tokenizer.batch_decode(lowerCamelCase_  )
								self.assertEqual(lowerCamelCase_       ,						['''k s ɾ ɾ l ɭʲ!?!? $$$''', '''j ð s j ð s oːɹ $$$''']  )

			@staticmethod
			def 							UpperCAmelCase__       ( lowerCamelCase_			:   List[Any]       ,						lowerCamelCase_			:   Tuple  )						->   Union[str, Any]:
								__magic_name__							:	Optional[int]    							=							[d[key] for d in offsets]
								return retrieved_list

			def 							UpperCAmelCase__       ( self			:   str  )						->   Optional[int]:
								__magic_name__							:	List[str]    							=							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"
								__magic_name__							:	List[Any]    							=							[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

								__magic_name__							:	Dict    							=							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			:   str  )						->   List[Any]:
								__magic_name__							:	Union[str, Any]    							=							self.get_tokenizer(word_delimiter_token='''|'''  )

								def check_list_tuples_equal(lowerCamelCase_			:   Optional[Any]       ,						lowerCamelCase_			:   int  ):
													self.assertTrue(isinstance(lowerCamelCase_       ,						lowerCamelCase_  )  )
													self.assertTrue(isinstance(outputs_list[0]       ,						lowerCamelCase_  )  )

													# transform list to ModelOutput
													__magic_name__							:	str    							=							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_			:   Union[str, Any]       ,						lowerCamelCase_			:   int  ):
																		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
								__magic_name__							:	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
								__magic_name__							:	Any    							=							tokenizer.batch_decode(lowerCamelCase_       ,						output_char_offsets=lowerCamelCase_  )
								__magic_name__							:	List[Any]    							=							[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  )						->   str:
								pass

			@unittest.skip('''Wav2Vec2PhonemeTokenizer always puts spaces between phonemes'''  )
			def 							UpperCAmelCase__       ( self			:   int  )						->   Optional[Any]:
								pass

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

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

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]  )						->   List[str]:
								__magic_name__							:	str    							=							self.get_tokenizers(do_lower_case=lowerCamelCase_  )
								for tokenizer in tokenizers:
													with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
																		__magic_name__							:	Any    							=							tokenizer.vocab_size
																		__magic_name__							:	int    							=							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)

																		__magic_name__							:	Any    							=							['''aaaaa bbbbbb''', '''cccccccccdddddddd''']
																		__magic_name__							:	Union[str, Any]    							=							tokenizer.add_tokens(lowerCamelCase_  )
																		__magic_name__							:	Optional[Any]    							=							tokenizer.vocab_size
																		__magic_name__							:	Optional[Any]    							=							len(lowerCamelCase_  )

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

																		__magic_name__							:	Tuple    							=							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  )

																		__magic_name__							:	Dict    							=							{'''eos_token''': '''>>>>|||<||<<|<<''', '''pad_token''': '''<<<<<|||>|>>>>|>'''}
																		__magic_name__							:	Union[str, Any]    							=							tokenizer.add_special_tokens(lowerCamelCase_  )
																		__magic_name__							:	Any    							=							tokenizer.vocab_size
																		__magic_name__							:	Tuple    							=							len(lowerCamelCase_  )

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

																		__magic_name__							:	List[str]    							=							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			:   int  )						->   List[Any]:
								pass

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


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

																		self.assertIsInstance(output['''text''']       ,						lowerCamelCase_  )









from sklearn.metrics import mean_squared_error

import datasets


__lowerCamelCase   :						List[str]				=			'''\
@article{scikit-learn,
 title={Scikit-learn: Machine Learning in {P}ython},
 author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
         and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
         and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
         Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
 journal={Journal of Machine Learning Research},
 volume={12},
 pages={2825--2830},
 year={2011}
}
'''

__lowerCamelCase   :						Optional[int]				=			'''\
Mean Squared Error(MSE) is the average of the square of difference between the predicted
and actual values.
'''


__lowerCamelCase   :						str				=			'''
Args:
    predictions: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Estimated target values.
    references: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Ground truth (correct) target values.
    sample_weight: array-like of shape (n_samples,), default=None
        Sample weights.
    multioutput: {"raw_values", "uniform_average"} or array-like of shape (n_outputs,), default="uniform_average"
        Defines aggregating of multiple output values. Array-like value defines weights used to average errors.

        "raw_values" : Returns a full set of errors in case of multioutput input.

        "uniform_average" : Errors of all outputs are averaged with uniform weight.

    squared : bool, default=True
        If True returns MSE value, if False returns RMSE (Root Mean Squared Error) value.

Returns:
    mse : mean squared error.
Examples:

    >>> mse_metric = datasets.load_metric("mse")
    >>> predictions = [2.5, 0.0, 2, 8]
    >>> references = [3, -0.5, 2, 7]
    >>> results = mse_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'mse\': 0.375}
    >>> rmse_result = mse_metric.compute(predictions=predictions, references=references, squared=False)
    >>> print(rmse_result)
    {\'mse\': 0.6123724356957945}

    If you\'re using multi-dimensional lists, then set the config as follows :

    >>> mse_metric = datasets.load_metric("mse", "multilist")
    >>> predictions = [[0.5, 1], [-1, 1], [7, -6]]
    >>> references = [[0, 2], [-1, 2], [8, -5]]
    >>> results = mse_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'mse\': 0.7083333333333334}
    >>> results = mse_metric.compute(predictions=predictions, references=references, multioutput=\'raw_values\')
    >>> print(results) # doctest: +NORMALIZE_WHITESPACE
    {\'mse\': array([0.41666667, 1. ])}
'''


@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION				,_KWARGS_DESCRIPTION						)
class    lowerCamelCase    (		datasets.Metric						):






			'''simple docstring'''





			def 							UpperCAmelCase__       ( self			:   Dict  )						->   Tuple:
								return datasets.MetricInfo(
								    description=_DESCRIPTION       ,						citation=_CITATION       ,						inputs_description=_KWARGS_DESCRIPTION       ,						features=datasets.Features(self._get_feature_types()  )       ,						reference_urls=[
								        '''https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html'''
								    ]       ,						)

			def 							UpperCAmelCase__       ( self			:   List[Any]  )						->   Any:
								if self.config_name == "multilist":
													return {
													    "predictions": datasets.Sequence(datasets.Value('''float'''  )  ),
													    "references": datasets.Sequence(datasets.Value('''float'''  )  ),
													}
								else:
													return {
													    "predictions": datasets.Value('''float'''  ),
													    "references": datasets.Value('''float'''  ),
													}


			def 							UpperCAmelCase__       ( self			:   Union[str, Any]       ,						lowerCamelCase_			:   Optional[Any]       ,						lowerCamelCase_			:   int       ,						lowerCamelCase_			:   int=None       ,						lowerCamelCase_			:   List[Any]="uniform_average"       ,						lowerCamelCase_			:   List[str]=True  )						->   List[str]:
								__magic_name__							:	Tuple    							=							mean_squared_error(
								    lowerCamelCase_       ,						lowerCamelCase_       ,						sample_weight=lowerCamelCase_       ,						multioutput=lowerCamelCase_       ,						squared=lowerCamelCase_  )

								return {"mse": mse}



