


'''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     :				Tuple       =							(
                '<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     :				Dict       =							dict(zip(snake_case__   ,						range(len(snake_case__ ) ) ) )

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

            _lowerCAmelCase     :				Union[str, 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     :				Optional[Any]       =							[(i, tokenizer.decode([i]   ,						clean_up_tokenization_spaces=snake_case__ )) for i in range(len(snake_case__ ) )]
            _lowerCAmelCase     :				Optional[int]       =							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     :				Optional[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     :				Tuple       =							toks + toks
        # toks_str = [t[1] for t in toks]
            _lowerCAmelCase     :				str       =							[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     :				Optional[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     :				Optional[Any]       =							' ' + output_txt
            _lowerCAmelCase     :				Optional[int]       =							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     :				List[str]       =							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )

            # check adding a single token
            tokenizer.add_tokens('xxx' )
            _lowerCAmelCase     :				Optional[Any]       =							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     :				List[str]       =							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     :				Optional[int]       =							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     :				Optional[Any]       =							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft' )

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

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

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

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

            _lowerCAmelCase     :				int       =							'Hello how are you'
            _lowerCAmelCase     :				List[str]       =							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     :				Dict       =							self.tokenizer_class.from_pretrained(
                'facebook/wav2vec2-lv-60-espeak-cv-ft'   ,						word_delimiter_token='|' )
            tokenizer.add_tokens('|' )

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

            # decode with word_del_token filter
            _lowerCAmelCase     :				List[Any]       =							tokenizer.decode(sample_ids[0] )
            _lowerCAmelCase     :				Tuple       =							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     :				int       =							tokenizer.decode(sample_ids[0]   ,						filter_word_delimiter_token=snake_case__ )
            _lowerCAmelCase     :				Optional[Any]       =							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     :				Dict       =							'Hello how are you'
            _lowerCAmelCase     :				Any       =							tokenizer.phonemize(snake_case__   ,						phonemizer_lang='en-us' )

            _lowerCAmelCase     :				str       =							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     :				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     :				int       =							tokenizer.phonemize(snake_case__   ,						phonemizer_lang='en-us' )

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

            _lowerCAmelCase     :				Any       =							tokenizer(snake_case__   ,						phonemizer_lang='en-us' ).input_ids
            _lowerCAmelCase     :				Any       =							tokenizer(snake_case__   ,						phonemizer_lang='fr-fr' ).input_ids

            self.assertNotEqual(snake_case__   ,						snake_case__ )

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

            _lowerCAmelCase     :				Dict       =							tokenizer(snake_case__ ).input_ids
            _lowerCAmelCase     :				Union[str, Any]       =							tokenizer(snake_case__ ).input_ids

            self.assertEqual(snake_case__   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

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

            # fmt: off
            _lowerCAmelCase     :				List[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     :				Optional[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     :				Any       =							[d[key] for d in offsets]
            return retrieved_list







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Tuple       =							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     :				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

            _lowerCAmelCase     :				List[Any]       =							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     :				str       =							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     :				List[Any]       =							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     :				int       =							[
                [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     :				List[Any]       =							tokenizer.batch_decode(snake_case__   ,						output_char_offsets=snake_case__ )
            _lowerCAmelCase     :				int       =							[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     :				List[Any]       =							self.get_tokenizers(do_lower_case=snake_case__ )
            for tokenizer in tokenizers:
                   with self.subTest(F'{tokenizer.__class__.__name__}' ):
                          _lowerCAmelCase     :				List[Any]       =							tokenizer.vocab_size
                          _lowerCAmelCase     :				Tuple       =							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     :				Any       =							tokenizer.add_tokens(snake_case__ )
                          _lowerCAmelCase     :				Any       =							tokenizer.vocab_size
                          _lowerCAmelCase     :				Optional[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 + len(snake_case__ ) )

                          _lowerCAmelCase     :				List[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     :				int       =							{'eos_token': '>>>>|||<||<<|<<', 'pad_token': '<<<<<|||>|>>>>|>'}
                          _lowerCAmelCase     :				Union[str, Any]       =							tokenizer.add_special_tokens(snake_case__ )
                          _lowerCAmelCase     :				str       =							tokenizer.vocab_size
                          _lowerCAmelCase     :				str       =							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     :				List[str]       =							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     :				str       =							['ð', 'ɪ', 's', 'ɪ', 'z', 'ɐ', 't', 'ɛ', 'k', 's', 't']
                          _lowerCAmelCase     :				Optional[Any]       =							tokenizer.convert_tokens_to_string(snake_case__ )

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





'''simple docstring'''







from __future__ import annotations

from math import gcd






def       lowercase					(_A ,    _A = 2 ,    _A = 1 ,    _A = 3 ,    ):







       """simple docstring"""







       if num < 2:
              raise ValueError('The input value cannot be less than 2'       )

       # Because of the relationship between ``f(f(x))`` and ``f(x)``, this
       # algorithm struggles to find factors that are divisible by two.
       # As a workaround, we specifically check for two and even inputs.
       #   See: https://math.stackexchange.com/a/2856214/165820
       if num > 2 and num % 2 == 0:
              return 2

       # Pollard's Rho algorithm requires a function that returns pseudorandom
       # values between 0 <= X < ``num``.  It doesn't need to be random in the
       # sense that the output value is cryptographically secure or difficult
       # to calculate, it only needs to be random in the sense that all output
       # values should be equally likely to appear.
       # For this reason, Pollard suggested using ``f(x) = (x**2 - 1) % num``
       # However, the success of Pollard's algorithm isn't guaranteed and is
       # determined in part by the initial seed and the chosen random function.
       # To make retries easier, we will instead use ``f(x) = (x**2 + C) % num``
       # where ``C`` is a value that we can modify between each attempt.
       def rand_fn(_A ,    _A ,    _A       ) -> int:
              return (pow(_A ,    2       ) + step) % modulus

       for _ in range(_A       ):
              # These track the position within the cycle detection logic.
              _lowerCAmelCase     :				Dict       =							seed
              _lowerCAmelCase     :				int       =							seed

              while True:
                     # At each iteration, the tortoise moves one step and the hare moves two.
                     _lowerCAmelCase     :				str       =							rand_fn(_A ,    _A ,    _A       )
                     _lowerCAmelCase     :				Optional[int]       =							rand_fn(_A ,    _A ,    _A       )
                     _lowerCAmelCase     :				Union[str, Any]       =							rand_fn(_A ,    _A ,    _A       )

                     # At some point both the tortoise and the hare will enter a cycle whose
                     # length ``p`` is a divisor of ``num``.  Once in that cycle, at some point
                     # the tortoise and hare will end up on the same value modulo ``p``.
                     # We can detect when this happens because the position difference between
                     # the tortoise and the hare will share a common divisor with ``num``.
                     _lowerCAmelCase     :				Optional[int]       =							gcd(hare - tortoise ,    _A       )

                     if divisor == 1:
                            # No common divisor yet, just keep searching.
                            continue
                     else:
                            # We found a common divisor!
                            if divisor == num:
                                   # Unfortunately, the divisor is ``num`` itself and is useless.
                                   break
                            else:
                                   # The divisor is a nontrivial factor of ``num``!
                                   return divisor

        # If we made it here, then this attempt failed.
        # We need to pick a new starting seed for the tortoise and hare
        # in addition to a new step value for the random function.
        # To keep this example implementation deterministic, the
        # new values will be generated based on currently available
        # values instead of using something like ``random.randint``.

        # We can use the hare's position as the new seed.
        # This is actually what Richard Brent's the "optimized" variant does.
              _lowerCAmelCase     :				Tuple       =							hare

              # The new step value for the random function can just be incremented.
              # At first the results will be similar to what the old function would
              # have produced, but the value will quickly diverge after a bit.
              step += 1

       # We haven't found a divisor within the requested number of attempts.
       # We were unlucky or ``num`` itself is actually prime.
       return None


if __name__ == "__main__":
       import argparse

       lowerCAmelCase     :  Tuple											=    argparse.ArgumentParser()
       parser.add_argument(
           """num""",
           type=int,
           help="""The value to find a divisor of""",
       )
       parser.add_argument(
           """--attempts""",
           type=int,
           default=3,
           help="""The number of attempts before giving up""",
       )
       lowerCAmelCase     :  List[str]											=    parser.parse_args()

       lowerCAmelCase     :  List[str]											=    pollard_rho(args.num, attempts=args.attempts)
       if divisor is None:
              print(F'''{args.num} is probably prime''')
       else:
              lowerCAmelCase     :  Union[str, Any]											=    args.num // divisor
              print(F'''{args.num} = {divisor} * {quotient}''')

