


'''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 	UpperCamelCase__					( SCREAMING_SNAKE_CASE_    ,					unittest.TestCase	):



     """simple docstring"""






     __magic_name__    			=    WavaVecaPhonemeCTCTokenizer
     __magic_name__    			=    False







     def a	( self   ):

            '''simple docstring'''

            super().setUp()

            _lowerCAmelCase    :							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(' '   )
            _lowerCAmelCase    :							Any   			=       dict(zip(snake_case__      ,	range(len(snake_case__   )   )   )   )

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

            _lowerCAmelCase    :							Optional[Any]   			=       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(snake_case__   ) + '\n'   )







     def a	( self      ,	snake_case__      ,	snake_case__=False      ,	snake_case__=20      ,	snake_case__=5   ):

            '''simple docstring'''

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

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







     def a	( self      ,	**snake_case__   ):

            '''simple docstring'''

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







     def a	( self   ):

            '''simple docstring'''

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

            # check adding a single token
            tokenizer.add_tokens('xxx'   )
            _lowerCAmelCase    :							Optional[int]   			=       tokenizer('m xxx ɪ'      ,	do_phonemize=snake_case__   ).input_ids
            self.assertEqual(snake_case__      ,	[13, 392, 17]   )  # xxx should be last token

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

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







     def a	( self   ):

            '''simple docstring'''

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

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







     def a	( self   ):

            '''simple docstring'''

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

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







     def a	( self   ):

            '''simple docstring'''

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

            _lowerCAmelCase    :							List[str]   			=       tokenizer.decode(tokenizer(snake_case__   ).input_ids   )

            self.assertEqual(snake_case__      ,	snake_case__   )







     def a	( self   ):

            '''simple docstring'''

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

            _lowerCAmelCase    :							int   			=       [
                [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
                [24, 22, 5, 24, 22, 5, 77],
            ]
            _lowerCAmelCase    :							Any   			=       tokenizer.decode(sample_ids[0]   )
            _lowerCAmelCase    :							str   			=       tokenizer.batch_decode(snake_case__   )
            self.assertEqual(snake_case__      ,	batch_tokens[0]   )
            self.assertEqual(snake_case__      ,	['k s ɾ ɾ l ɭʲ', 'j ð s j ð s oːɹ']   )







     def a	( self   ):

            '''simple docstring'''

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

            _lowerCAmelCase    :							Optional[int]   			=       'Hello how are you'
            _lowerCAmelCase    :							Tuple   			=       tokenizer.phonemize(snake_case__      ,	phonemizer_lang='en-us'   )
            self.assertEqual(snake_case__      ,	'h ə l oʊ | h aʊ | ɑːɹ | j uː |'   )







     def a	( self   ):

            '''simple docstring'''

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

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







     def a	( self   ):

            '''simple docstring'''

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

            # fmt: off
            _lowerCAmelCase    :							int   			=       [
                [11, 5, 15, tokenizer.pad_token_id, tokenizer.word_delimiter_token_id, 15, 8, tokenizer.word_delimiter_token_id, 98],
                [tokenizer.word_delimiter_token_id, 24, 22, tokenizer.word_delimiter_token_id, 5, 24, 22, 5, 77],
            ]
            # fmt: on

            # decode with word_del_token filter
            _lowerCAmelCase    :							int   			=       tokenizer.decode(sample_ids[0]   )
            _lowerCAmelCase    :							Dict   			=       tokenizer.batch_decode(snake_case__   )
            self.assertEqual(snake_case__      ,	batch_tokens[0]   )
            self.assertEqual(snake_case__      ,	['k s ɾ ɾ l ɭʲ', 'j ð s j ð s oːɹ']   )

            # decode with no word_del_token filter
            _lowerCAmelCase    :							Union[str, Any]   			=       tokenizer.decode(sample_ids[0]      ,	filter_word_delimiter_token=snake_case__   )
            _lowerCAmelCase    :							Tuple   			=       tokenizer.batch_decode(snake_case__      ,	filter_word_delimiter_token=snake_case__   )
            self.assertEqual(snake_case__      ,	batch_tokens[0]   )
            self.assertEqual(snake_case__      ,	['k s ɾ | ɾ l | ɭʲ', '| j ð | s j ð s oːɹ']   )







     def a	( self   ):

            '''simple docstring'''

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

            _lowerCAmelCase    :							List[str]   			=       'Hello how are you'
            _lowerCAmelCase    :							str   			=       tokenizer.phonemize(snake_case__      ,	phonemizer_lang='en-us'   )

            _lowerCAmelCase    :							int   			=       tokenizer.decode(tokenizer(snake_case__   ).input_ids      ,	filter_word_delimiter_token=snake_case__   )

            self.assertEqual(snake_case__      ,	snake_case__   )







     def a	( self   ):

            '''simple docstring'''

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

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

            _lowerCAmelCase    :							List[Any]   			=       tokenizer.decode(tokenizer(snake_case__   ).input_ids      ,	filter_word_delimiter_token=snake_case__   )

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







     def a	( self   ):

            '''simple docstring'''

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

            _lowerCAmelCase    :							Optional[int]   			=       tokenizer(snake_case__      ,	phonemizer_lang='en-us'   ).input_ids
            _lowerCAmelCase    :							Union[str, Any]   			=       tokenizer(snake_case__      ,	phonemizer_lang='fr-fr'   ).input_ids

            self.assertNotEqual(snake_case__      ,	snake_case__   )

            _lowerCAmelCase    :							List[Any]   			=       tokenizer.decode(snake_case__   )
            _lowerCAmelCase    :							str   			=       tokenizer.decode(snake_case__   )

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







     def a	( self   ):

            '''simple docstring'''

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

            _lowerCAmelCase    :							Optional[Any]   			=       tokenizer(snake_case__   ).input_ids
            _lowerCAmelCase    :							Optional[int]   			=       tokenizer(snake_case__   ).input_ids

            self.assertEqual(snake_case__      ,	snake_case__   )







     def a	( self   ):

            '''simple docstring'''

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

            # fmt: off
            _lowerCAmelCase    :							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

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







     @staticmethod
     def a	( snake_case__      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							int   			=       [d[key] for d in offsets]
            return retrieved_list







     def a	( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							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"
            _lowerCAmelCase    :							Union[str, 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

            _lowerCAmelCase    :							Tuple   			=       tokenizer.decode(snake_case__      ,	output_char_offsets=snake_case__      ,	filter_word_delimiter_token=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(snake_case__      ,	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 a	( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Any   			=       self.get_tokenizer(word_delimiter_token='|'   )

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

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

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

        # fmt: off
            _lowerCAmelCase    :							str   			=       [
                [11, 5, 15, tokenizer.pad_token_id, 15, 4, 8, 98, 32, 32, 32, 32, 4, 33, tokenizer.word_delimiter_token_id, 32, 32, 33, 34, 34],
                [24, 22, 5, tokenizer.word_delimiter_token_id, tokenizer.word_delimiter_token_id, 24, 22, 22, 22, 4, 5, 77, tokenizer.pad_token_id, 22, 22, 4, 34, 34, 34, 34],
            ]
            # fmt: on

            # We assume that `decode` works as expected. All we will check now is
            # the output type is correct and the output is identical to `decode`

            # char
            _lowerCAmelCase    :							Union[str, Any]   			=       tokenizer.batch_decode(snake_case__      ,	output_char_offsets=snake_case__   )
            _lowerCAmelCase    :							Dict   			=       [tokenizer.decode(snake_case__      ,	output_char_offsets=snake_case__   ) for ids in sample_ids]
            check_list_tuples_equal(snake_case__      ,	snake_case__   )







     @unittest.skip('Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes'   )
     def a	( self   ):

            '''simple docstring'''

            pass







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

            '''simple docstring'''

            pass







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

            '''simple docstring'''

            pass







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

            '''simple docstring'''

            pass







     def a	( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Dict   			=       self.get_tokenizers(do_lower_case=snake_case__   )
            for tokenizer in tokenizers:
                   with self.subTest(F'{tokenizer.__class__.__name__}'   ):
                          _lowerCAmelCase    :							Any   			=       tokenizer.vocab_size
                          _lowerCAmelCase    :							List[Any]   			=       len(snake_case__   )

                          self.assertNotEqual(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)

                          _lowerCAmelCase    :							Optional[Any]   			=       ['aaaaa bbbbbb', 'cccccccccdddddddd']
                          _lowerCAmelCase    :							Optional[Any]   			=       tokenizer.add_tokens(snake_case__   )
                          _lowerCAmelCase    :							Optional[Any]   			=       tokenizer.vocab_size
                          _lowerCAmelCase    :							Optional[int]   			=       len(snake_case__   )

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

                          _lowerCAmelCase    :							Optional[Any]   			=       tokenizer.encode('aaaaa bbbbbb low cccccccccdddddddd l'      ,	add_special_tokens=snake_case__   )

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

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

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

                          _lowerCAmelCase    :							Tuple   			=       tokenizer.encode(
                              '>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l'      ,	add_special_tokens=snake_case__   )

                          self.assertGreaterEqual(len(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 a	( self   ):

            '''simple docstring'''

            pass







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

            '''simple docstring'''

            pass







     def a	( self   ):

            '''simple docstring'''

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

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





'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase    :     Any					=						{
    """configuration_x_clip""": [
        """XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XCLIPConfig""",
        """XCLIPTextConfig""",
        """XCLIPVisionConfig""",
    ],
    """processing_x_clip""": ["""XCLIPProcessor"""],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     Optional[Any]					=						[
           """XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """XCLIPModel""",
           """XCLIPPreTrainedModel""",
           """XCLIPTextModel""",
           """XCLIPVisionModel""",
       ]

if TYPE_CHECKING:
       from .configuration_x_clip import (
           XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
           XCLIPConfig,
           XCLIPTextConfig,
           XCLIPVisionConfig,
       )
       from .processing_x_clip import XCLIPProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_x_clip import (
                  XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  XCLIPModel,
                  XCLIPPreTrainedModel,
                  XCLIPTextModel,
                  XCLIPVisionModel,
              )

else:
       import sys

       lowerCAmelCase    :     Dict					=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

