




"""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 lowerCAmelCase__      (	lowercase,      unittest.TestCase		):






			'''simple docstring'''



			lowerCamelCase__ =     WavaVecaPhonemeCTCTokenizer
			lowerCamelCase__ =     False
			def    A_       (    self    ):
							super().setUp()

							_lowerCamelCase	:     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(' '    )
							_lowerCamelCase	:     str       =       dict(zip(lowercase    , range(len(lowercase    )    )    )    )

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

							_lowerCamelCase	:     Optional[int]       =       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(lowercase    ) + '\n'    )
			def    A_       (    self    , lowercase    , lowercase=False    , lowercase=20    , lowercase=5    ):
							_lowerCamelCase	:     Dict       =       [(i, tokenizer.decode([i]    , clean_up_tokenization_spaces=lowercase    )) for i in range(len(lowercase    )    )]
							_lowerCamelCase	:     List[Any]       =       list(filter(lambda lowercase    : [t[0]] == tokenizer.encode(t[1]    , do_phonemize=lowercase    )    , lowercase    )    )
							if max_length is not None and len(lowercase    ) > max_length:
											_lowerCamelCase	:     int       =       toks[:max_length]
							if min_length is not None and len(lowercase    ) < min_length and len(lowercase    ) > 0:
											while len(lowercase    ) < min_length:
															_lowerCamelCase	:     Dict       =       toks + toks
        # toks_str = [t[1] for t in toks]
							_lowerCamelCase	:     Tuple       =       [t[0] for t in toks]

							# Ensure consistency
							_lowerCamelCase	:     int       =       tokenizer.decode(lowercase    , clean_up_tokenization_spaces=lowercase    )
							if " " not in output_txt and len(lowercase    ) > 1:
											_lowerCamelCase	:     Any       =       (
											    tokenizer.decode([toks_ids[0]]    , clean_up_tokenization_spaces=lowercase    )
											    + ' '
											    + tokenizer.decode(toks_ids[1:]    , clean_up_tokenization_spaces=lowercase    )
											)
							if with_prefix_space:
											_lowerCamelCase	:     int       =       ' ' + output_txt
							_lowerCamelCase	:     Any       =       tokenizer.encode(lowercase    , add_special_tokens=lowercase    )
							return output_txt, output_ids
			def    A_       (    self    , **lowercase    ):
							kwargs.update(self.special_tokens_map    )
							return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname    , **lowercase    )
			def    A_       (    self    ):
							_lowerCamelCase	:     Optional[Any]       =       self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'    )

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

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

							_lowerCamelCase	:     List[Any]       =       tokenizer('maɪ c'    , do_phonemize=lowercase    ).input_ids
							self.assertEqual(lowercase    , [3, 200]    )  # mai should be <unk> (=3)
			def    A_       (    self    ):
							_lowerCamelCase	:     Tuple       =       self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'    )

							_lowerCamelCase	:     int       =       'Hello how are you'
							_lowerCamelCase	:     List[Any]       =       tokenizer.phonemize(lowercase    , phonemizer_lang='en-us'    )
							self.assertEqual(lowercase    , 'h ə l oʊ h aʊ ɑːɹ j uː'    )
			def    A_       (    self    ):
							_lowerCamelCase	:     Any       =       self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'    )

							_lowerCamelCase	:     List[str]       =       'Hello how are you'
							_lowerCamelCase	:     int       =       tokenizer.phonemize(lowercase    , phonemizer_lang='en-us'    )
							self.assertEqual(tokenizer(lowercase    ).input_ids    , tokenizer(lowercase    , do_phonemize=lowercase    ).input_ids    )
			def    A_       (    self    ):
							_lowerCamelCase	:     List[str]       =       self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'    )
							_lowerCamelCase	:     Dict       =       'Hello how are you'
							_lowerCamelCase	:     List[Any]       =       tokenizer.phonemize(lowercase    , phonemizer_lang='en-us'    )

							_lowerCamelCase	:     str       =       tokenizer.decode(tokenizer(lowercase    ).input_ids    )

							self.assertEqual(lowercase    , lowercase    )
			def    A_       (    self    ):
							_lowerCamelCase	:     List[Any]       =       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	:     Optional[Any]       =       tokenizer.decode(sample_ids[0]    )
							_lowerCamelCase	:     str       =       tokenizer.batch_decode(lowercase    )
							self.assertEqual(lowercase    , batch_tokens[0]    )
							self.assertEqual(lowercase    , ['k s ɾ ɾ l ɭʲ', 'j ð s j ð s oːɹ']    )
			def    A_       (    self    ):
							_lowerCamelCase	:     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	:     Tuple       =       tokenizer.phonemize(lowercase    , phonemizer_lang='en-us'    )
							self.assertEqual(lowercase    , 'h ə l oʊ | h aʊ | ɑːɹ | j uː |'    )
			def    A_       (    self    ):
							_lowerCamelCase	:     Union[str, 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	:     List[Any]       =       tokenizer.phonemize(lowercase    , phonemizer_lang='en-us'    )
							self.assertEqual(tokenizer(lowercase    ).input_ids    , tokenizer(lowercase    , do_phonemize=lowercase    ).input_ids    )
			def    A_       (    self    ):
							_lowerCamelCase	:     int       =       self.tokenizer_class.from_pretrained(
							    'facebook/wav2vec2-lv-60-espeak-cv-ft'    , word_delimiter_token='|'    )
							tokenizer.add_tokens('|'    )

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

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

							# decode with no word_del_token filter
							_lowerCamelCase	:     Optional[int]       =       tokenizer.decode(sample_ids[0]    , filter_word_delimiter_token=lowercase    )
							_lowerCamelCase	:     Dict       =       tokenizer.batch_decode(lowercase    , filter_word_delimiter_token=lowercase    )
							self.assertEqual(lowercase    , batch_tokens[0]    )
							self.assertEqual(lowercase    , ['k s ɾ | ɾ l | ɭʲ', '| j ð | s j ð s oːɹ']    )
			def    A_       (    self    ):
							_lowerCamelCase	:     Optional[Any]       =       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	:     Tuple       =       tokenizer.phonemize(lowercase    , phonemizer_lang='en-us'    )

							_lowerCamelCase	:     Any       =       tokenizer.decode(tokenizer(lowercase    ).input_ids    , filter_word_delimiter_token=lowercase    )

							self.assertEqual(lowercase    , lowercase    )
			def    A_       (    self    ):
							_lowerCamelCase	:     List[Any]       =       self.tokenizer_class.from_pretrained(
							    'facebook/wav2vec2-lv-60-espeak-cv-ft'    , word_delimiter_token='|'    )
							tokenizer.add_tokens('|'    )

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

							_lowerCamelCase	:     List[str]       =       tokenizer.decode(tokenizer(lowercase    ).input_ids    , filter_word_delimiter_token=lowercase    )

							self.assertEqual(' '.join([p.strip() for p in phonemes.split(' |'    )]    ).strip()    , lowercase    )
			def    A_       (    self    ):
							_lowerCamelCase	:     int       =       self.tokenizer_class.from_pretrained(
							    'facebook/wav2vec2-lv-60-espeak-cv-ft'    , word_delimiter_token=lowercase    )
							_lowerCamelCase	:     Union[str, Any]       =       'Hello how are you'

							_lowerCamelCase	:     List[str]       =       tokenizer(lowercase    , phonemizer_lang='en-us'    ).input_ids
							_lowerCamelCase	:     int       =       tokenizer(lowercase    , phonemizer_lang='fr-fr'    ).input_ids

							self.assertNotEqual(lowercase    , lowercase    )

							_lowerCamelCase	:     Any       =       tokenizer.decode(lowercase    )
							_lowerCamelCase	:     Union[str, Any]       =       tokenizer.decode(lowercase    )

							self.assertEqual(lowercase    , 'h ə l oʊ h aʊ ɑːɹ j uː'    )
							self.assertEqual(lowercase    , 'ɛ l o h aʊ a ʁ j u'    )
			def    A_       (    self    ):
							_lowerCamelCase	:     List[str]       =       self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'    )
							_lowerCamelCase	:     Tuple       =       'Hello how Are you'
							_lowerCamelCase	:     Optional[int]       =       'hello how are you'

							_lowerCamelCase	:     Union[str, Any]       =       tokenizer(lowercase    ).input_ids
							_lowerCamelCase	:     List[Any]       =       tokenizer(lowercase    ).input_ids

							self.assertEqual(lowercase    , lowercase    )
			def    A_       (    self    ):
							_lowerCamelCase	:     List[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	:     Tuple       =       [
							    [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	:     List[Any]       =       tokenizer.batch_decode(lowercase    )
							self.assertEqual(lowercase    , ['k s ɾ ɾ l ɭʲ!?!? $$$', 'j ð s j ð s oːɹ $$$']    )
			@staticmethod
			def    A_       (    lowercase    , lowercase    ):
							_lowerCamelCase	:     Tuple       =       [d[key] for d in offsets]
							return retrieved_list
			def    A_       (    self    ):
							_lowerCamelCase	:     List[str]       =       self.get_tokenizer(word_delimiter_token='|'    )
							tokenizer.add_tokens('|'    )

							# fmt: off
							# ksssɾɾ|ɾɾ<pad>ɾɾ|<pad>ɾlll|ɭʲ -> k s ɾ ɾ | ɾ l | ɭʲ"
							_lowerCamelCase	:     List[str]       =       [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	:     Optional[Any]       =       tokenizer.decode(lowercase    , output_char_offsets=lowercase    , filter_word_delimiter_token=lowercase    )
							# 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(lowercase    , lowercase    )    )

							# 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    ):
							_lowerCamelCase	:     Union[str, Any]       =       self.get_tokenizer(word_delimiter_token='|'    )

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

											# transform list to ModelOutput
											_lowerCamelCase	:     List[str]       =       WavaVecaPhonemeCTCTokenizerOutput(
											    {k: [d[k] for d in outputs_list] for k in outputs_list[0]}    )

											self.assertListEqual(outputs_batch['text']    , outputs_batch_a['text']    )

											def recursive_check(lowercase    , lowercase    ):
															if isinstance(lowercase    , lowercase    ):
																			[recursive_check(lowercase    , lowercase    ) for la, la in zip(lowercase    , lowercase    )]
															self.assertEqual(lowercase    , lowercase    )

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

        # fmt: off
							_lowerCamelCase	:     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
							_lowerCamelCase	:     List[str]       =       tokenizer.batch_decode(lowercase    , output_char_offsets=lowercase    )
							_lowerCamelCase	:     Any       =       [tokenizer.decode(lowercase    , output_char_offsets=lowercase    ) for ids in sample_ids]
							check_list_tuples_equal(lowercase    , lowercase    )
			@unittest.skip('Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes'    )
			def    A_       (    self    ):
							pass
			@unittest.skip('Wav2Vec2PhonemeTokenizer always puts spaces between phonemes'    )
			def    A_       (    self    ):
							pass
			@unittest.skip('encodes to text to ids, but decodes ids to phonemes -> not possible to have internal consistency'    )
			def    A_       (    self    ):
							pass
			@unittest.skip('Wav2Vec2PhonemeModel has no max model length => no testing'    )
			def    A_       (    self    ):
							pass
			def    A_       (    self    ):
							_lowerCamelCase	:     List[str]       =       self.get_tokenizers(do_lower_case=lowercase    )
							for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''    ):
															_lowerCamelCase	:     Union[str, Any]       =       tokenizer.vocab_size
															_lowerCamelCase	:     Union[str, Any]       =       len(lowercase    )

															self.assertNotEqual(lowercase    , 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	:     List[str]       =       ['aaaaa bbbbbb', 'cccccccccdddddddd']
															_lowerCamelCase	:     Optional[Any]       =       tokenizer.add_tokens(lowercase    )
															_lowerCamelCase	:     str       =       tokenizer.vocab_size
															_lowerCamelCase	:     List[Any]       =       len(lowercase    )

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

															_lowerCamelCase	:     List[Any]       =       tokenizer.encode('aaaaa bbbbbb low cccccccccdddddddd l'    , add_special_tokens=lowercase    )

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

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

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

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

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






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

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





"""simple docstring"""






import argparse

import intel_extension_for_pytorch as ipex
import torch

from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline


lowercase__			=		argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
parser.add_argument("""--dpm""", action="""store_true""", help="""Enable DPMSolver or not""")
parser.add_argument("""--steps""", default=None, type=int, help="""Num inference steps""")
lowercase__			=		parser.parse_args()


lowercase__			=		"""cpu"""
lowercase__			=		"""a lovely <dicoo> in red dress and hat, in the snowly and brightly night, with many brighly buildings"""

lowercase__			=		"""path-to-your-trained-model"""
lowercase__			=		StableDiffusionPipeline.from_pretrained(model_id)
if args.dpm:
			lowercase__			=		DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
lowercase__			=		pipe.to(device)

# to channels last
lowercase__			=		pipe.unet.to(memory_format=torch.channels_last)
lowercase__			=		pipe.vae.to(memory_format=torch.channels_last)
lowercase__			=		pipe.text_encoder.to(memory_format=torch.channels_last)
if pipe.requires_safety_checker:
			lowercase__			=		pipe.safety_checker.to(memory_format=torch.channels_last)

# optimize with ipex
lowercase__			=		torch.randn(2, 4, 64, 64)
lowercase__			=		torch.rand(1) * 999
lowercase__			=		torch.randn(2, 77, 768)
lowercase__			=		(sample, timestep, encoder_hidden_status)
try:
			lowercase__			=		ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True, sample_input=input_example)
except Exception:
			lowercase__			=		ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True)
lowercase__			=		ipex.optimize(pipe.vae.eval(), dtype=torch.bfloataa, inplace=True)
lowercase__			=		ipex.optimize(pipe.text_encoder.eval(), dtype=torch.bfloataa, inplace=True)
if pipe.requires_safety_checker:
			lowercase__			=		ipex.optimize(pipe.safety_checker.eval(), dtype=torch.bfloataa, inplace=True)

# compute
lowercase__			=		666
lowercase__			=		torch.Generator(device).manual_seed(seed)
lowercase__			=		{"""generator""": generator}
if args.steps is not None:
			lowercase__			=		args.steps

with torch.cpu.amp.autocast(enabled=True, dtype=torch.bfloataa):
			lowercase__			=		pipe(prompt, **generate_kwargs).images[0]

# save image
image.save("""generated.png""")