





"""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"""


 _lowerCamelCase				=					WavaVecaPhonemeCTCTokenizer
 _lowerCamelCase				=					False

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     super().setUp()

     __A   :						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(''' '''  )
     __A   :						Optional[int]									=					dict(zip(__lowerCamelCase ,						range(len(__lowerCamelCase  )  )  )  )

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

     __A   :						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 ,						__lowerCamelCase ,						__lowerCamelCase=False ,						__lowerCamelCase=20 ,						__lowerCamelCase=5  ):



     '''simple docstring'''




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

     # Ensure consistency
     __A   :						List[str]									=					tokenizer.decode(__lowerCamelCase ,						clean_up_tokenization_spaces=__lowerCamelCase  )
     if " " not in output_txt and len(__lowerCamelCase  ) > 1:
         __A   :						List[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:
         __A   :						Dict									=					''' ''' + output_txt
     __A   :						Optional[Any]									=					tokenizer.encode(__lowerCamelCase ,						add_special_tokens=__lowerCamelCase  )
     return output_txt, output_ids

 def  UpperCamelCase__(   self ,						**__lowerCamelCase  ):



     '''simple docstring'''




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

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						List[str]									=					self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )

     # check adding a single token
     tokenizer.add_tokens('''xxx'''  )
     __A   :						Any									=					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''']  )
     __A   :						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

     __A   :						Dict									=					tokenizer('''maɪ c''' ,						do_phonemize=__lowerCamelCase  ).input_ids
     self.assertEqual(__lowerCamelCase ,						[3, 200]  )  # mai should be <unk> (=3)

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Dict									=					self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )

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

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						List[str]									=					self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )

     __A   :						Optional[int]									=					'''Hello how are you'''
     __A   :						int									=					tokenizer.phonemize(__lowerCamelCase ,						phonemizer_lang='''en-us'''  )
     self.assertEqual(tokenizer(__lowerCamelCase  ).input_ids ,						tokenizer(__lowerCamelCase ,						do_phonemize=__lowerCamelCase  ).input_ids  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




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

     __A   :						List[Any]									=					tokenizer.decode(tokenizer(__lowerCamelCase  ).input_ids  )

     self.assertEqual(__lowerCamelCase ,						__lowerCamelCase  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Union[str, Any]									=					self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )

     __A   :						Union[str, Any]									=					[
         [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
         [24, 22, 5, 24, 22, 5, 77],
     ]
     __A   :						List[Any]									=					tokenizer.decode(sample_ids[0]  )
     __A   :						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''']  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Tuple									=					self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft''' ,						word_delimiter_token='''|'''  )
     tokenizer.add_tokens('''|'''  )

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

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




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

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

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Any									=					self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft''' ,						word_delimiter_token='''|'''  )
     tokenizer.add_tokens('''|'''  )

     # fmt: off
     __A   :						str									=					[
         [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   :						Optional[Any]									=					tokenizer.decode(sample_ids[0]  )
     __A   :						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
     __A   :						int									=					tokenizer.decode(sample_ids[0] ,						filter_word_delimiter_token=__lowerCamelCase  )
     __A   :						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  UpperCamelCase__(   self  ):



     '''simple docstring'''




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

     __A   :						int									=					'''Hello how are you'''
     __A   :						Optional[Any]									=					tokenizer.phonemize(__lowerCamelCase ,						phonemizer_lang='''en-us'''  )

     __A   :						List[Any]									=					tokenizer.decode(tokenizer(__lowerCamelCase  ).input_ids ,						filter_word_delimiter_token=__lowerCamelCase  )

     self.assertEqual(__lowerCamelCase ,						__lowerCamelCase  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Tuple									=					self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft''' ,						word_delimiter_token='''|'''  )
     tokenizer.add_tokens('''|'''  )

     __A   :						Optional[Any]									=					'''Hello how are you'''
     __A   :						Optional[int]									=					tokenizer.phonemize(__lowerCamelCase ,						phonemizer_lang='''en-us'''  )

     __A   :						List[str]									=					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  ):



     '''simple docstring'''




     __A   :						int									=					self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft''' ,						word_delimiter_token=__lowerCamelCase  )
     __A   :						Optional[int]									=					'''Hello how are you'''

     __A   :						str									=					tokenizer(__lowerCamelCase ,						phonemizer_lang='''en-us'''  ).input_ids
     __A   :						Optional[Any]									=					tokenizer(__lowerCamelCase ,						phonemizer_lang='''fr-fr'''  ).input_ids

     self.assertNotEqual(__lowerCamelCase ,						__lowerCamelCase  )

     __A   :						Optional[Any]									=					tokenizer.decode(__lowerCamelCase  )
     __A   :						List[str]									=					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  ):



     '''simple docstring'''




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

     __A   :						Union[str, Any]									=					tokenizer(__lowerCamelCase  ).input_ids
     __A   :						List[str]									=					tokenizer(__lowerCamelCase  ).input_ids

     self.assertEqual(__lowerCamelCase ,						__lowerCamelCase  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						int									=					self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''  )
     tokenizer.add_tokens(['''!''', '''?''']  )
     tokenizer.add_special_tokens({'''cls_token''': '''$$$'''}  )

     # fmt: off
     __A   :						Optional[int]									=					[
         [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

     __A   :						Optional[Any]									=					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  ):



     '''simple docstring'''




     __A   :						Dict									=					[d[key] for d in offsets]
     return retrieved_list

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						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"
     __A   :						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

     __A   :						Tuple									=					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  ):



     '''simple docstring'''




     __A   :						Dict									=					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   :						Dict									=					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   :						Union[str, 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
     __A   :						int									=					tokenizer.batch_decode(__lowerCamelCase ,						output_char_offsets=__lowerCamelCase  )
     __A   :						Optional[int]									=					[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  ):



     '''simple docstring'''




     pass

 @unittest.skip('''Wav2Vec2PhonemeTokenizer always puts spaces between phonemes'''  )
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     pass

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



     '''simple docstring'''




     pass

 @unittest.skip('''Wav2Vec2PhonemeModel has no max model length => no testing'''  )
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     pass

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Union[str, Any]									=					self.get_tokenizers(do_lower_case=__lowerCamelCase  )
     for tokenizer in tokenizers:
         with self.subTest(F"""{tokenizer.__class__.__name__}"""  ):
             __A   :						Tuple									=					tokenizer.vocab_size
             __A   :						Optional[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)

             __A   :						Optional[Any]									=					['''aaaaa bbbbbb''', '''cccccccccdddddddd''']
             __A   :						str									=					tokenizer.add_tokens(__lowerCamelCase  )
             __A   :						Tuple									=					tokenizer.vocab_size
             __A   :						str									=					len(__lowerCamelCase  )

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

             __A   :						int									=					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   :						int									=					{'''eos_token''': '''>>>>|||<||<<|<<''', '''pad_token''': '''<<<<<|||>|>>>>|>'''}
             __A   :						Dict									=					tokenizer.add_special_tokens(__lowerCamelCase  )
             __A   :						Optional[int]									=					tokenizer.vocab_size
             __A   :						str									=					len(__lowerCamelCase  )

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

             __A   :						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  ):



     '''simple docstring'''




     pass

 @unittest.skip('''The tokenizer shouldn\'t be used to encode input IDs (except for labels), only to decode.'''  )
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     pass







 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




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

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











"""simple docstring"""



# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


a_			=      {
    """configuration_vivit""": ["""VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VivitConfig"""],
}
try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a_			=      ["""VivitImageProcessor"""]


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a_			=      [
           """VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """VivitModel""",
           """VivitPreTrainedModel""",
           """VivitForVideoClassification""",
       ]


if TYPE_CHECKING:
       from .configuration_vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_vivit import VivitImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vivit import (
                  VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  VivitForVideoClassification,
                  VivitModel,
                  VivitPreTrainedModel,
              )


else:
       import sys

       a_			=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




