'''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 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_						,     unittest.TestCase	):







  '''simple docstring'''






  lowerCamelCase_		:Optional[int]						   =		WavaVecaPhonemeCTCTokenizer
  lowerCamelCase_		:Optional[int]						   =		False


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       super().setUp()

       UpperCAmelCase_							:       int       =				(
           '''<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_							:       List[Any]       =				dict(zip(snake_case_				,		range(len(snake_case_						)						)						)						)

       UpperCAmelCase_							:       List[str]       =				{'''pad_token''': '''<pad>''', '''unk_token''': '''<unk>''', '''bos_token''': '''<s>''', '''eos_token''': '''</s>'''}

       UpperCAmelCase_							:       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(snake_case_						) + '\n'						)


  def _UpperCamelCase					(			self				,		snake_case_				,		snake_case_=False				,		snake_case_=2_0				,		snake_case_=5						):




       '''simple docstring'''

       UpperCAmelCase_							:       Tuple       =				[(i, tokenizer.decode([i]				,		clean_up_tokenization_spaces=snake_case_						)) for i in range(len(snake_case_						)						)]
       UpperCAmelCase_							:       Tuple       =				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:
            UpperCAmelCase_							:       Tuple       =				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:
                 UpperCAmelCase_							:       Optional[Any]       =				toks + toks
        # toks_str = [t[1] for t in toks]
       UpperCAmelCase_							:       Union[str, Any]       =				[t[0] for t in toks]

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


  def _UpperCamelCase					(			self				,		**snake_case_						):




       '''simple docstring'''

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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

       # check adding a single token
       tokenizer.add_tokens('xxx'						)
       UpperCAmelCase_							:       List[str]       =				tokenizer('m xxx ɪ'				,		do_phonemize=snake_case_						).input_ids
       self.assertEqual(snake_case_				,		[1_3, 3_9_2, 1_7]						)  # xxx should be last token

       tokenizer.add_tokens(['aaa', 'bbb', 'ccc']						)
       UpperCAmelCase_							:       Optional[Any]       =				tokenizer('m aaa ɪ ccc'				,		do_phonemize=snake_case_						).input_ids
       self.assertEqual(snake_case_				,		[1_3, 3_9_3, 1_7, 3_9_5]						)  # aaa and ccc should be after xxx and 2 after aaa

       UpperCAmelCase_							:       List[str]       =				tokenizer('maɪ c'				,		do_phonemize=snake_case_						).input_ids
       self.assertEqual(snake_case_				,		[3, 2_0_0]						)  # mai should be <unk> (=3)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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

       UpperCAmelCase_							:       Dict       =				'''Hello how are you'''
       UpperCAmelCase_							:       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 _UpperCamelCase					(			self						):




       '''simple docstring'''

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

       UpperCAmelCase_							:       Dict       =				tokenizer.decode(tokenizer(snake_case_						).input_ids						)

       self.assertEqual(snake_case_				,		snake_case_						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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

       UpperCAmelCase_							:       int       =				[
           [1_1, 5, 1_5, tokenizer.pad_token_id, 1_5, 8, 9_8],
           [2_4, 2_2, 5, 2_4, 2_2, 5, 7_7],
       ]
       UpperCAmelCase_							:       Optional[int]       =				tokenizer.decode(sample_ids[0]						)
       UpperCAmelCase_							:       List[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 _UpperCamelCase					(			self						):




       '''simple docstring'''

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

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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

       UpperCAmelCase_							:       Union[str, Any]       =				'''Hello how are you'''
       UpperCAmelCase_							:       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 _UpperCamelCase					(			self						):




       '''simple docstring'''

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

       # fmt: off
       UpperCAmelCase_							:       int       =				[
           [1_1, 5, 1_5, tokenizer.pad_token_id, tokenizer.word_delimiter_token_id, 1_5, 8, tokenizer.word_delimiter_token_id, 9_8],
           [tokenizer.word_delimiter_token_id, 2_4, 2_2, tokenizer.word_delimiter_token_id, 5, 2_4, 2_2, 5, 7_7],
       ]
       # fmt: on

       # decode with word_del_token filter
       UpperCAmelCase_							:       Tuple       =				tokenizer.decode(sample_ids[0]						)
       UpperCAmelCase_							:       List[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']						)

       # decode with no word_del_token filter
       UpperCAmelCase_							:       Any       =				tokenizer.decode(sample_ids[0]				,		filter_word_delimiter_token=snake_case_						)
       UpperCAmelCase_							:       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 _UpperCamelCase					(			self						):




       '''simple docstring'''

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

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

       UpperCAmelCase_							:       Union[str, Any]       =				tokenizer.decode(tokenizer(snake_case_						).input_ids				,		filter_word_delimiter_token=snake_case_						)

       self.assertEqual(snake_case_				,		snake_case_						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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

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

       UpperCAmelCase_							:       Dict       =				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 _UpperCamelCase					(			self						):




       '''simple docstring'''

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

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

       self.assertNotEqual(snake_case_				,		snake_case_						)

       UpperCAmelCase_							:       Any       =				tokenizer.decode(snake_case_						)
       UpperCAmelCase_							:       Union[str, Any]       =				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 _UpperCamelCase					(			self						):




       '''simple docstring'''

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

       UpperCAmelCase_							:       Any       =				tokenizer(snake_case_						).input_ids
       UpperCAmelCase_							:       Optional[Any]       =				tokenizer(snake_case_						).input_ids

       self.assertEqual(snake_case_				,		snake_case_						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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

       # fmt: off
       UpperCAmelCase_							:       Optional[int]       =				[
           [1_1, 5, 1_5, tokenizer.pad_token_id, 1_5, 8, 9_8, 3_9_2, 3_9_2, 3_9_3, 3_9_2, 3_9_2, 3_9_3, 3_9_4, 3_9_4],
           [2_4, 2_2, 5, 2_4, 2_2, 5, 7_7, tokenizer.pad_token_id, 3_9_4, 3_9_4],
       ]
       # fmt: on

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


  @staticmethod
  def _UpperCamelCase					(			snake_case_				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       Any       =				[d[key] for d in offsets]
       return retrieved_list


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[int]       =				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_							:       Optional[Any]       =				[1_1, 5, 5, 5, 1_5, 1_5, tokenizer.pad_token_id, 1_5, 1_5, tokenizer.word_delimiter_token_id, tokenizer.pad_token_id, 1_5, 8, 8, 8, tokenizer.word_delimiter_token_id, 9_8]
       # fmt: on

       UpperCAmelCase_							:       Optional[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, 1_1, 1_2, 1_5, 1_6]						)
       self.assertListEqual(
           self.get_from_offsets(outputs['char_offsets']				,		'end_offset'						)				,		[1, 4, 6, 9, 1_0, 1_2, 1_5, 1_6, 1_7]						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Tuple       =				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
            UpperCAmelCase_							:       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
       UpperCAmelCase_							:       List[str]       =				[
           [1_1, 5, 1_5, tokenizer.pad_token_id, 1_5, 4, 8, 9_8, 3_2, 3_2, 3_2, 3_2, 4, 3_3, tokenizer.word_delimiter_token_id, 3_2, 3_2, 3_3, 3_4, 3_4],
           [2_4, 2_2, 5, tokenizer.word_delimiter_token_id, tokenizer.word_delimiter_token_id, 2_4, 2_2, 2_2, 2_2, 4, 5, 7_7, tokenizer.pad_token_id, 2_2, 2_2, 4, 3_4, 3_4, 3_4, 3_4],
       ]
       # 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_							:       List[Any]       =				tokenizer.batch_decode(snake_case_				,		output_char_offsets=snake_case_						)
       UpperCAmelCase_							:       List[Any]       =				[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 _UpperCamelCase					(			self						):




       '''simple docstring'''

       pass


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




       '''simple docstring'''

       pass


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




       '''simple docstring'''

       pass


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




       '''simple docstring'''

       pass


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[int]       =				self.get_tokenizers(do_lower_case=snake_case_						)
       for tokenizer in tokenizers:
            with self.subTest(F'''{tokenizer.__class__.__name__}'''						):
                 UpperCAmelCase_							:       List[str]       =				tokenizer.vocab_size
                 UpperCAmelCase_							:       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)

                 UpperCAmelCase_							:       Optional[Any]       =				['''aaaaa bbbbbb''', '''cccccccccdddddddd''']
                 UpperCAmelCase_							:       Dict       =				tokenizer.add_tokens(snake_case_						)
                 UpperCAmelCase_							:       Dict       =				tokenizer.vocab_size
                 UpperCAmelCase_							:       Tuple       =				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_						)						)

                 UpperCAmelCase_							:       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						)

                 UpperCAmelCase_							:       Optional[Any]       =				{'''eos_token''': '''>>>>|||<||<<|<<''', '''pad_token''': '''<<<<<|||>|>>>>|>'''}
                 UpperCAmelCase_							:       Optional[Any]       =				tokenizer.add_special_tokens(snake_case_						)
                 UpperCAmelCase_							:       Dict       =				tokenizer.vocab_size
                 UpperCAmelCase_							:       Tuple       =				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_						)						)

                 UpperCAmelCase_							:       Any       =				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 _UpperCamelCase					(			self						):




       '''simple docstring'''

       pass


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




       '''simple docstring'''

       pass






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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

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


'''simple docstring'''


import os
import time

import numpy as np
import onnxruntime as ort


snake_case__					:      Optional[int]				      =  '''1'''
snake_case__					:      str				      =  '''0'''
snake_case__					:      List[str]				      =  '''1'''

snake_case__					:      List[str]				      =  ort.SessionOptions()
snake_case__					:      str				      =  ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print('''Create inference session...''')
snake_case__					:      Dict				      =  ['''TensorrtExecutionProvider''', '''CUDAExecutionProvider''']
snake_case__					:      Dict				      =  ort.InferenceSession('''model.onnx''', sess_options=sess_opt, providers=execution_provider)
snake_case__					:      str				      =  ort.RunOptions()

snake_case__					:      List[Any]				      =  128
snake_case__					:      Union[str, Any]				      =  1
snake_case__					:      Tuple				      =  np.ones((batch, sequence), dtype=np.intaa)
snake_case__					:      Tuple				      =  np.ones((batch, sequence), dtype=np.intaa)
snake_case__					:      Union[str, Any]				      =  np.ones((batch, sequence), dtype=np.intaa)

print('''Warm up phase...''')
sess.run(
    None,
    {
        sess.get_inputs()[0].name: input_ids,
        sess.get_inputs()[1].name: attention_mask,
        sess.get_inputs()[2].name: token_type_ids,
    },
    run_options=run_opt,
)

print('''Start inference...''')
snake_case__					:      Union[str, Any]				      =  time.time()
snake_case__					:      str				      =  2000
snake_case__					:      Tuple				      =  {}
for iter in range(max_iters):
 snake_case__					:      str				      =  sess.run(
     None,
     {
         sess.get_inputs()[0].name: input_ids,
         sess.get_inputs()[1].name: attention_mask,
         sess.get_inputs()[2].name: token_type_ids,
     },
     run_options=run_opt,
 )
print('''Average Inference Time = {:.3f} ms'''.format((time.time() - start_time) * 1000 / max_iters))






