"""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 (				lowercase__   ,					unittest.TestCase       ):




     """simple docstring"""

     snake_case__       					=				WavaVecaPhonemeCTCTokenizer
     snake_case__       					=				False







     def 	__lowerCAmelCase		(       self     :			Union[str, Any]    ):
         super().setUp()

         UpperCAmelCase__    =							(
             '<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(' '    )
         UpperCAmelCase__    =							dict(zip(lowerCamelCase__					,range(len(lowerCamelCase__    )    )    )    )

         UpperCAmelCase__    =							{'pad_token': '<pad>', 'unk_token': '<unk>', 'bos_token': '<s>', 'eos_token': '</s>'}

         UpperCAmelCase__    =							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 	__lowerCAmelCase		(       self     :			Dict					,lowerCamelCase__     :			Any					,lowerCamelCase__     :			Dict=False					,lowerCamelCase__     :			Dict=20					,lowerCamelCase__     :			Union[str, Any]=5    ):
         UpperCAmelCase__    =							[(i, tokenizer.decode([i]					,clean_up_tokenization_spaces=lowerCamelCase__    )) for i in range(len(lowerCamelCase__    )    )]
         UpperCAmelCase__    =							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:
             UpperCAmelCase__    =							toks[:max_length]
         if min_length is not None and len(lowerCamelCase__    ) < min_length and len(lowerCamelCase__    ) > 0:
             while len(lowerCamelCase__    ) < min_length:
                 UpperCAmelCase__    =							toks + toks
        # toks_str = [t[1] for t in toks]
         UpperCAmelCase__    =							[t[0] for t in toks]

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







     def 	__lowerCAmelCase		(       self     :			List[Any]					,**lowerCamelCase__     :			Union[str, Any]    ):
         kwargs.update(self.special_tokens_map    )
         return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname					,**lowerCamelCase__    )







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

         # check adding a single token
         tokenizer.add_tokens('xxx'    )
         UpperCAmelCase__    =							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']    )
         UpperCAmelCase__    =							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

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







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

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







     def 	__lowerCAmelCase		(       self     :			Any    ):
         UpperCAmelCase__    =							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'    )

         UpperCAmelCase__    =							'Hello how are you'
         UpperCAmelCase__    =							tokenizer.phonemize(lowerCamelCase__					,phonemizer_lang='en-us'    )
         self.assertEqual(tokenizer(lowerCamelCase__    ).input_ids					,tokenizer(lowerCamelCase__					,do_phonemize=lowerCamelCase__    ).input_ids    )







     def 	__lowerCAmelCase		(       self     :			List[str]    ):
         UpperCAmelCase__    =							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'    )
         UpperCAmelCase__    =							'Hello how are you'
         UpperCAmelCase__    =							tokenizer.phonemize(lowerCamelCase__					,phonemizer_lang='en-us'    )

         UpperCAmelCase__    =							tokenizer.decode(tokenizer(lowerCamelCase__    ).input_ids    )

         self.assertEqual(lowerCamelCase__					,lowerCamelCase__    )







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

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

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







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

         UpperCAmelCase__    =							'Hello how are you'
         UpperCAmelCase__    =							tokenizer.phonemize(lowerCamelCase__					,phonemizer_lang='en-us'    )
         self.assertEqual(tokenizer(lowerCamelCase__    ).input_ids					,tokenizer(lowerCamelCase__					,do_phonemize=lowerCamelCase__    ).input_ids    )







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

         # fmt: off
         UpperCAmelCase__    =							[
             [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
         UpperCAmelCase__    =							tokenizer.decode(sample_ids[0]    )
         UpperCAmelCase__    =							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
         UpperCAmelCase__    =							tokenizer.decode(sample_ids[0]					,filter_word_delimiter_token=lowerCamelCase__    )
         UpperCAmelCase__    =							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 	__lowerCAmelCase		(       self     :			Optional[int]    ):
         UpperCAmelCase__    =							self.tokenizer_class.from_pretrained(
             'facebook/wav2vec2-lv-60-espeak-cv-ft'					,word_delimiter_token='|'    )
         tokenizer.add_tokens('|'    )

         UpperCAmelCase__    =							'Hello how are you'
         UpperCAmelCase__    =							tokenizer.phonemize(lowerCamelCase__					,phonemizer_lang='en-us'    )

         UpperCAmelCase__    =							tokenizer.decode(tokenizer(lowerCamelCase__    ).input_ids					,filter_word_delimiter_token=lowerCamelCase__    )

         self.assertEqual(lowerCamelCase__					,lowerCamelCase__    )







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

         UpperCAmelCase__    =							'Hello how are you'
         UpperCAmelCase__    =							tokenizer.phonemize(lowerCamelCase__					,phonemizer_lang='en-us'    )

         UpperCAmelCase__    =							tokenizer.decode(tokenizer(lowerCamelCase__    ).input_ids					,filter_word_delimiter_token=lowerCamelCase__    )

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







     def 	__lowerCAmelCase		(       self     :			List[Any]    ):
         UpperCAmelCase__    =							self.tokenizer_class.from_pretrained(
             'facebook/wav2vec2-lv-60-espeak-cv-ft'					,word_delimiter_token=lowerCamelCase__    )
         UpperCAmelCase__    =							'Hello how are you'

         UpperCAmelCase__    =							tokenizer(lowerCamelCase__					,phonemizer_lang='en-us'    ).input_ids
         UpperCAmelCase__    =							tokenizer(lowerCamelCase__					,phonemizer_lang='fr-fr'    ).input_ids

         self.assertNotEqual(lowerCamelCase__					,lowerCamelCase__    )

         UpperCAmelCase__    =							tokenizer.decode(lowerCamelCase__    )
         UpperCAmelCase__    =							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 	__lowerCAmelCase		(       self     :			int    ):
         UpperCAmelCase__    =							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'    )
         UpperCAmelCase__    =							'Hello how Are you'
         UpperCAmelCase__    =							'hello how are you'

         UpperCAmelCase__    =							tokenizer(lowerCamelCase__    ).input_ids
         UpperCAmelCase__    =							tokenizer(lowerCamelCase__    ).input_ids

         self.assertEqual(lowerCamelCase__					,lowerCamelCase__    )







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

         # fmt: off
         UpperCAmelCase__    =							[
             [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

         UpperCAmelCase__    =							tokenizer.batch_decode(lowerCamelCase__    )
         self.assertEqual(lowerCamelCase__					,['k s ɾ ɾ l ɭʲ!?!? $$$', 'j ð s j ð s oːɹ $$$']    )







     @staticmethod
     def 	__lowerCAmelCase		(       lowerCamelCase__     :			Dict					,lowerCamelCase__     :			Optional[Any]    ):
         UpperCAmelCase__    =							[d[key] for d in offsets]
         return retrieved_list







     def 	__lowerCAmelCase		(       self     :			List[str]    ):
         UpperCAmelCase__    =							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"
         UpperCAmelCase__    =							[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

         UpperCAmelCase__    =							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 	__lowerCAmelCase		(       self     :			Tuple    ):
         UpperCAmelCase__    =							self.get_tokenizer(word_delimiter_token='|'    )

         def check_list_tuples_equal(lowerCamelCase__     :			str					,lowerCamelCase__     :			List[Any]    ):
             self.assertTrue(isinstance(lowerCamelCase__					,lowerCamelCase__    )    )
             self.assertTrue(isinstance(outputs_list[0]					,lowerCamelCase__    )    )

             # transform list to ModelOutput
             UpperCAmelCase__    =							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__     :			str					,lowerCamelCase__     :			List[Any]    ):
                 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
         UpperCAmelCase__    =							[
             [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
         UpperCAmelCase__    =							tokenizer.batch_decode(lowerCamelCase__					,output_char_offsets=lowerCamelCase__    )
         UpperCAmelCase__    =							[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 	__lowerCAmelCase		(       self     :			Optional[Any]    ):
         pass







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







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







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







     def 	__lowerCAmelCase		(       self     :			List[str]    ):
         UpperCAmelCase__    =							self.get_tokenizers(do_lower_case=lowerCamelCase__    )
         for tokenizer in tokenizers:
             with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
                 UpperCAmelCase__    =							tokenizer.vocab_size
                 UpperCAmelCase__    =							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)

                 UpperCAmelCase__    =							['aaaaa bbbbbb', 'cccccccccdddddddd']
                 UpperCAmelCase__    =							tokenizer.add_tokens(lowerCamelCase__    )
                 UpperCAmelCase__    =							tokenizer.vocab_size
                 UpperCAmelCase__    =							len(lowerCamelCase__    )

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

                 UpperCAmelCase__    =							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    )

                 UpperCAmelCase__    =							{'eos_token': '>>>>|||<||<<|<<', 'pad_token': '<<<<<|||>|>>>>|>'}
                 UpperCAmelCase__    =							tokenizer.add_special_tokens(lowerCamelCase__    )
                 UpperCAmelCase__    =							tokenizer.vocab_size
                 UpperCAmelCase__    =							len(lowerCamelCase__    )

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

                 UpperCAmelCase__    =							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 	__lowerCAmelCase		(       self     :			int    ):
         pass







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







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

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




"""simple docstring"""






import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device


lowerCAmelCase__						:						Union[str, Any]		  =			False
class        snake_case (				unittest.TestCase       ):




					"""simple docstring"""

					pass






@nightly
@require_torch_gpu
class        snake_case (				unittest.TestCase       ):




					"""simple docstring"""

					def 	__lowerCAmelCase		(       self     :			Any    ):
									# clean up the VRAM after each test
									super().tearDown()
									gc.collect()
									torch.cuda.empty_cache()







					def 	__lowerCAmelCase		(       self     :			Any    ):
									UpperCAmelCase__    =							VersatileDiffusionPipeline.from_pretrained('shi-labs/versatile-diffusion'					,torch_dtype=torch.floataa    )
									pipe.to(lowerCamelCase__    )
									pipe.set_progress_bar_config(disable=lowerCamelCase__    )

									UpperCAmelCase__    =							load_image(
									    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'    )

									UpperCAmelCase__    =							torch.manual_seed(0    )
									UpperCAmelCase__    =							pipe.dual_guided(
									    prompt='first prompt'					,image=lowerCamelCase__					,text_to_image_strength=0.7_5					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=2					,output_type='numpy'					,).images

									with tempfile.TemporaryDirectory() as tmpdirname:
													pipe.save_pretrained(lowerCamelCase__    )
													UpperCAmelCase__    =							VersatileDiffusionPipeline.from_pretrained(lowerCamelCase__					,torch_dtype=torch.floataa    )
									pipe.to(lowerCamelCase__    )
									pipe.set_progress_bar_config(disable=lowerCamelCase__    )

									UpperCAmelCase__    =							generator.manual_seed(0    )
									UpperCAmelCase__    =							pipe.dual_guided(
									    prompt='first prompt'					,image=lowerCamelCase__					,text_to_image_strength=0.7_5					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=2					,output_type='numpy'					,).images

									assert np.abs(image - new_image    ).sum() < 1e-5, "Models don't have the same forward pass"







					def 	__lowerCAmelCase		(       self     :			Optional[int]    ):
									UpperCAmelCase__    =							VersatileDiffusionPipeline.from_pretrained('shi-labs/versatile-diffusion'					,torch_dtype=torch.floataa    )
									pipe.to(lowerCamelCase__    )
									pipe.set_progress_bar_config(disable=lowerCamelCase__    )

									UpperCAmelCase__    =							'cyberpunk 2077'
									UpperCAmelCase__    =							load_image(
									    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'    )
									UpperCAmelCase__    =							torch.manual_seed(0    )
									UpperCAmelCase__    =							pipe.dual_guided(
									    prompt=lowerCamelCase__					,image=lowerCamelCase__					,text_to_image_strength=0.7_5					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=50					,output_type='numpy'					,).images

									UpperCAmelCase__    =							image[0, 253:256, 253:256, -1]

									assert image.shape == (1, 512, 512, 3)
									UpperCAmelCase__    =							np.array([0.1_4_4_8, 0.1_6_1_9, 0.1_7_4_1, 0.1_0_8_6, 0.1_1_4_7, 0.1_1_2_8, 0.1_1_9_9, 0.1_1_6_5, 0.1_0_0_1]    )

									assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-1

									UpperCAmelCase__    =							'A painting of a squirrel eating a burger '
									UpperCAmelCase__    =							torch.manual_seed(0    )
									UpperCAmelCase__    =							pipe.text_to_image(
									    prompt=lowerCamelCase__					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=50					,output_type='numpy'    ).images

									UpperCAmelCase__    =							image[0, 253:256, 253:256, -1]

									assert image.shape == (1, 512, 512, 3)
									UpperCAmelCase__    =							np.array([0.3_3_6_7, 0.3_1_6_9, 0.2_6_5_6, 0.3_8_7_0, 0.4_7_9_0, 0.3_7_9_6, 0.4_0_0_9, 0.4_8_7_8, 0.4_7_7_8]    )

									assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-1

									UpperCAmelCase__    =							pipe.image_variation(lowerCamelCase__					,generator=lowerCamelCase__					,output_type='numpy'    ).images

									UpperCAmelCase__    =							image[0, 253:256, 253:256, -1]

									assert image.shape == (1, 512, 512, 3)
									UpperCAmelCase__    =							np.array([0.3_0_7_6, 0.3_1_2_3, 0.3_2_8_4, 0.3_7_8_2, 0.3_7_7_0, 0.3_8_9_4, 0.4_2_9_7, 0.4_3_3_1, 0.4_4_5_6]    )

									assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-1



