



"""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  ):
   A__		:	Dict           =  WavaVecaPhonemeCTCTokenizer
   A__		:	List[str]           =  False



   def    __UpperCAmelCase    (       self    :	Optional[int]				):



     """simple docstring"""
     super().setUp()

     _snake_case   	=      (
         '''<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(''' '''				)
     _snake_case   	=      dict(zip(__lowerCamelCase							,       range(len(__lowerCamelCase				)				)				)				)

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

     _snake_case   	=      os.path.join(self.tmpdirname							,       VOCAB_FILES_NAMES['''vocab_file''']				)
     with open(self.vocab_file							,       '''w'''							,       encoding='''utf-8'''				) as fp:
       fp.write(json.dumps(__lowerCamelCase				) + '''\n'''				)



   def    __UpperCAmelCase    (       self    :	str							,       __lowerCamelCase    :	Any							,       __lowerCamelCase    :	Dict=False							,       __lowerCamelCase    :	List[Any]=2_0							,       __lowerCamelCase    :	int=5				):



     """simple docstring"""
     _snake_case   	=      [(i, tokenizer.decode([i]							,       clean_up_tokenization_spaces=__lowerCamelCase				)) for i in range(len(__lowerCamelCase				)				)]
     _snake_case   	=      list(filter(lambda __lowerCamelCase				: [t[0]] == tokenizer.encode(t[1]							,       do_phonemize=__lowerCamelCase				)							,       __lowerCamelCase				)				)
     if max_length is not None and len(__lowerCamelCase				) > max_length:
       _snake_case   	=      toks[:max_length]
     if min_length is not None and len(__lowerCamelCase				) < min_length and len(__lowerCamelCase				) > 0:
       while len(__lowerCamelCase				) < min_length:
         _snake_case   	=      toks + toks
        # toks_str = [t[1] for t in toks]
     _snake_case   	=      [t[0] for t in toks]

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



   def    __UpperCAmelCase    (       self    :	List[Any]							,       **__lowerCamelCase    :	Union[str, Any]				):



     """simple docstring"""
     kwargs.update(self.special_tokens_map				)
     return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname							,       **__lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''				)

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

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

     _snake_case   	=      tokenizer('''maɪ c'''							,       do_phonemize=__lowerCamelCase				).input_ids
     self.assertEqual(__lowerCamelCase							,       [3, 2_0_0]				)  # mai should be <unk> (=3)



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''				)

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



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''				)

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



   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''				)
     _snake_case   	=      '''Hello how are you'''
     _snake_case   	=      tokenizer.phonemize(__lowerCamelCase							,       phonemizer_lang='''en-us'''				)

     _snake_case   	=      tokenizer.decode(tokenizer(__lowerCamelCase				).input_ids				)

     self.assertEqual(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''				)

     _snake_case   	=      [
         [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],
     ]
     _snake_case   	=      tokenizer.decode(sample_ids[0]				)
     _snake_case   	=      tokenizer.batch_decode(__lowerCamelCase				)
     self.assertEqual(__lowerCamelCase							,       batch_tokens[0]				)
     self.assertEqual(__lowerCamelCase							,       ['''k s ɾ ɾ l ɭʲ''', '''j ð s j ð s oːɹ''']				)



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft'''							,       word_delimiter_token='''|'''				)
     tokenizer.add_tokens('''|'''				)

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



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft'''							,       word_delimiter_token='''|'''				)
     tokenizer.add_tokens('''|'''				)

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



   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft'''							,       word_delimiter_token='''|'''				)
     tokenizer.add_tokens('''|'''				)

     # fmt: off
     _snake_case   	=      [
         [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
     _snake_case   	=      tokenizer.decode(sample_ids[0]				)
     _snake_case   	=      tokenizer.batch_decode(__lowerCamelCase				)
     self.assertEqual(__lowerCamelCase							,       batch_tokens[0]				)
     self.assertEqual(__lowerCamelCase							,       ['''k s ɾ ɾ l ɭʲ''', '''j ð s j ð s oːɹ''']				)

     # decode with no word_del_token filter
     _snake_case   	=      tokenizer.decode(sample_ids[0]							,       filter_word_delimiter_token=__lowerCamelCase				)
     _snake_case   	=      tokenizer.batch_decode(__lowerCamelCase							,       filter_word_delimiter_token=__lowerCamelCase				)
     self.assertEqual(__lowerCamelCase							,       batch_tokens[0]				)
     self.assertEqual(__lowerCamelCase							,       ['''k s ɾ | ɾ l | ɭʲ''', '''| j ð | s j ð s oːɹ''']				)



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft'''							,       word_delimiter_token='''|'''				)
     tokenizer.add_tokens('''|'''				)

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

     _snake_case   	=      tokenizer.decode(tokenizer(__lowerCamelCase				).input_ids							,       filter_word_delimiter_token=__lowerCamelCase				)

     self.assertEqual(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft'''							,       word_delimiter_token='''|'''				)
     tokenizer.add_tokens('''|'''				)

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

     _snake_case   	=      tokenizer.decode(tokenizer(__lowerCamelCase				).input_ids							,       filter_word_delimiter_token=__lowerCamelCase				)

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



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained(
         '''facebook/wav2vec2-lv-60-espeak-cv-ft'''							,       word_delimiter_token=__lowerCamelCase				)
     _snake_case   	=      '''Hello how are you'''

     _snake_case   	=      tokenizer(__lowerCamelCase							,       phonemizer_lang='''en-us'''				).input_ids
     _snake_case   	=      tokenizer(__lowerCamelCase							,       phonemizer_lang='''fr-fr'''				).input_ids

     self.assertNotEqual(__lowerCamelCase							,       __lowerCamelCase				)

     _snake_case   	=      tokenizer.decode(__lowerCamelCase				)
     _snake_case   	=      tokenizer.decode(__lowerCamelCase				)

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



   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     _snake_case   	=      self.tokenizer_class.from_pretrained('''facebook/wav2vec2-lv-60-espeak-cv-ft'''				)
     _snake_case   	=      '''Hello how Are you'''
     _snake_case   	=      '''hello how are you'''

     _snake_case   	=      tokenizer(__lowerCamelCase				).input_ids
     _snake_case   	=      tokenizer(__lowerCamelCase				).input_ids

     self.assertEqual(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Tuple				):



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

     # fmt: off
     _snake_case   	=      [
         [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

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



   @staticmethod
   def    __UpperCAmelCase    (       __lowerCamelCase    :	List[Any]							,       __lowerCamelCase    :	str				):



     """simple docstring"""
     _snake_case   	=      [d[key] for d in offsets]
     return retrieved_list



   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     _snake_case   	=      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"
     _snake_case   	=      [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

     _snake_case   	=      tokenizer.decode(__lowerCamelCase							,       output_char_offsets=__lowerCamelCase							,       filter_word_delimiter_token=__lowerCamelCase				)
     # check Wav2Vec2CTCTokenizerOutput keys for char
     self.assertEqual(len(outputs.keys()				)							,       2				)
     self.assertTrue('''text''' in outputs				)
     self.assertTrue('''char_offsets''' in outputs				)
     self.assertTrue(isinstance(__lowerCamelCase							,       __lowerCamelCase				)				)

     # check that order of chars is correct and identical for both outputs
     self.assertEqual(''' '''.join(self.get_from_offsets(outputs['''char_offsets''']							,       '''char'''				)				)							,       outputs.text				)
     self.assertListEqual(
         self.get_from_offsets(outputs['''char_offsets''']							,       '''char'''				)							,       ['''k''', '''s''', '''ɾ''', '''ɾ''', '''|''', '''ɾ''', '''l''', '''|''', '''ɭʲ''']				)

     # check that offsets are actually correct for char
     # 0-1 is 11, 1-4 is 5, 4-6 is first 15, 6-7 is <pad> (thus not shown), 7-9 is second 15, 9-10 is word_delimiter_token,
     # 10-11 is <pad> (thus not shown), 11-12 is third 15, 12-15 is 8, 15-16 is word_delimiter_token, 16-17 is 98
     self.assertListEqual(
         self.get_from_offsets(outputs['''char_offsets''']							,       '''start_offset'''				)							,       [0, 1, 4, 7, 9, 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    :	Optional[int]				):



     """simple docstring"""
     _snake_case   	=      self.get_tokenizer(word_delimiter_token='''|'''				)

     def check_list_tuples_equal(__lowerCamelCase    :	Optional[int]							,       __lowerCamelCase    :	Union[str, Any]				):
       self.assertTrue(isinstance(__lowerCamelCase							,       __lowerCamelCase				)				)
       self.assertTrue(isinstance(outputs_list[0]							,       __lowerCamelCase				)				)

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

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

       def recursive_check(__lowerCamelCase    :	Union[str, Any]							,       __lowerCamelCase    :	Optional[Any]				):
         if isinstance(__lowerCamelCase							,       __lowerCamelCase				):
           [recursive_check(__lowerCamelCase							,       __lowerCamelCase				) for la, la in zip(__lowerCamelCase							,       __lowerCamelCase				)]
         self.assertEqual(__lowerCamelCase							,       __lowerCamelCase				)

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

        # fmt: off
     _snake_case   	=      [
         [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
     _snake_case   	=      tokenizer.batch_decode(__lowerCamelCase							,       output_char_offsets=__lowerCamelCase				)
     _snake_case   	=      [tokenizer.decode(__lowerCamelCase							,       output_char_offsets=__lowerCamelCase				) for ids in sample_ids]
     check_list_tuples_equal(__lowerCamelCase							,       __lowerCamelCase				)



   @unittest.skip('''Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes'''				)
   def    __UpperCAmelCase    (       self    :	List[str]				):



     """simple docstring"""
     pass



   @unittest.skip('''Wav2Vec2PhonemeTokenizer always puts spaces between phonemes'''				)
   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""
     pass



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



     """simple docstring"""
     pass



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



     """simple docstring"""
     pass



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     _snake_case   	=      self.get_tokenizers(do_lower_case=__lowerCamelCase				)
     for tokenizer in tokenizers:
       with self.subTest(f"""{tokenizer.__class__.__name__}"""				):
         _snake_case   	=      tokenizer.vocab_size
         _snake_case   	=      len(__lowerCamelCase				)

         self.assertNotEqual(__lowerCamelCase							,       0				)

         # We usually have added tokens from the start in tests because our vocab fixtures are
         # smaller than the original vocabs - let's not assert this
         # self.assertEqual(vocab_size, all_size)

         _snake_case   	=      ['''aaaaa bbbbbb''', '''cccccccccdddddddd''']
         _snake_case   	=      tokenizer.add_tokens(__lowerCamelCase				)
         _snake_case   	=      tokenizer.vocab_size
         _snake_case   	=      len(__lowerCamelCase				)

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

         _snake_case   	=      tokenizer.encode('''aaaaa bbbbbb low cccccccccdddddddd l'''							,       add_special_tokens=__lowerCamelCase				)

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

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

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

         _snake_case   	=      tokenizer.encode(
             '''>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l'''							,       add_special_tokens=__lowerCamelCase				)

         self.assertGreaterEqual(len(__lowerCamelCase				)							,       6				)
         self.assertGreater(tokens[0]							,       tokenizer.vocab_size - 1				)
         self.assertGreater(tokens[0]							,       tokens[1]				)
         self.assertGreater(tokens[-3]							,       tokenizer.vocab_size - 1				)
         self.assertGreater(tokens[-3]							,       tokens[-4]				)
         self.assertEqual(tokens[0]							,       tokenizer.eos_token_id				)
         self.assertEqual(tokens[-3]							,       tokenizer.pad_token_id				)



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



     """simple docstring"""
     pass



   @unittest.skip('''The tokenizer shouldn\'t be used to encode input IDs (except for labels), only to decode.'''				)
   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""
     pass





   def    __UpperCAmelCase    (       self    :	Tuple				):



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

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







"""simple docstring"""

import functools
import operator

from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_            =    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_            =    {
    '''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json''',
    # See all SEW-D models at https://huggingface.co/models?filter=sew-d
}
class   _UpperCAmelCase				(		SCREAMING_SNAKE_CASE_				):
      __SCREAMING_SNAKE_CASE :				List[str]				   =						"sew-d"




      def __init__(				self ,							lowercase_=3_2 ,							lowercase_=7_6_8 ,							lowercase_=1_2 ,							lowercase_=1_2 ,							lowercase_=3_0_7_2 ,							lowercase_=2 ,							lowercase_=5_1_2 ,							lowercase_=2_5_6 ,							lowercase_=True ,							lowercase_=True ,							lowercase_=("p2c", "c2p") ,							lowercase_="layer_norm" ,							lowercase_="gelu_python" ,							lowercase_=0.1 ,							lowercase_=0.1 ,							lowercase_=0.1 ,							lowercase_=0.0 ,							lowercase_=0.1 ,							lowercase_=0.0_2 ,							lowercase_=1E-7 ,							lowercase_=1E-5 ,							lowercase_="group" ,							lowercase_="gelu" ,							lowercase_=(6_4, 1_2_8, 1_2_8, 1_2_8, 1_2_8, 2_5_6, 2_5_6, 2_5_6, 2_5_6, 5_1_2, 5_1_2, 5_1_2, 5_1_2) ,							lowercase_=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1) ,							lowercase_=(1_0, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1) ,							lowercase_=False ,							lowercase_=1_2_8 ,							lowercase_=1_6 ,							lowercase_=True ,							lowercase_=0.0_5 ,							lowercase_=1_0 ,							lowercase_=2 ,							lowercase_=0.0 ,							lowercase_=1_0 ,							lowercase_=0 ,							lowercase_="mean" ,							lowercase_=False ,							lowercase_=False ,							lowercase_=2_5_6 ,							lowercase_=0 ,							lowercase_=1 ,							lowercase_=2 ,							**lowercase_ ,							)    ->       Dict:
          super().__init__(**lowercase_ ,							pad_token_id=lowercase_ ,							bos_token_id=lowercase_ ,							eos_token_id=lowercase_				)
          UpperCAmelCase          =       hidden_size
          UpperCAmelCase          =       feat_extract_norm
          UpperCAmelCase          =       feat_extract_activation
          UpperCAmelCase          =       list(lowercase_				)
          UpperCAmelCase          =       list(lowercase_				)
          UpperCAmelCase          =       list(lowercase_				)
          UpperCAmelCase          =       conv_bias
          UpperCAmelCase          =       num_conv_pos_embeddings
          UpperCAmelCase          =       num_conv_pos_embedding_groups
          UpperCAmelCase          =       len(self.conv_dim				)
          UpperCAmelCase          =       num_hidden_layers
          UpperCAmelCase          =       intermediate_size
          UpperCAmelCase          =       squeeze_factor
          UpperCAmelCase          =       max_position_embeddings
          UpperCAmelCase          =       position_buckets
          UpperCAmelCase          =       share_att_key
          UpperCAmelCase          =       relative_attention
          UpperCAmelCase          =       norm_rel_ebd
          UpperCAmelCase          =       list(lowercase_				)
          UpperCAmelCase          =       hidden_act
          UpperCAmelCase          =       num_attention_heads
          UpperCAmelCase          =       hidden_dropout
          UpperCAmelCase          =       attention_dropout
          UpperCAmelCase          =       activation_dropout
          UpperCAmelCase          =       feat_proj_dropout
          UpperCAmelCase          =       final_dropout
          UpperCAmelCase          =       layer_norm_eps
          UpperCAmelCase          =       feature_layer_norm_eps
          UpperCAmelCase          =       initializer_range
          UpperCAmelCase          =       vocab_size

          if (
              (len(self.conv_stride				) != self.num_feat_extract_layers)
              or (len(self.conv_kernel				) != self.num_feat_extract_layers)
              or (len(self.conv_dim				) != self.num_feat_extract_layers)
          ):
              raise ValueError(
                  'Configuration for convolutional layers is incorrect.'
                  'It is required that `len(config.conv_dim)` == `len(config.conv_stride)` == `len(config.conv_kernel)`,'
                  F"but is `len(config.conv_dim) = {len(self.conv_dim				)}`, `len(config.conv_stride)"
                  F"= {len(self.conv_stride				)}`, `len(config.conv_kernel) = {len(self.conv_kernel				)}`."				)

          # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
          UpperCAmelCase          =       apply_spec_augment
          UpperCAmelCase          =       mask_time_prob
          UpperCAmelCase          =       mask_time_length
          UpperCAmelCase          =       mask_time_min_masks
          UpperCAmelCase          =       mask_feature_prob
          UpperCAmelCase          =       mask_feature_length
          UpperCAmelCase          =       mask_feature_min_masks

          # ctc loss
          UpperCAmelCase          =       ctc_loss_reduction
          UpperCAmelCase          =       ctc_zero_infinity

          # sequence classification
          UpperCAmelCase          =       use_weighted_layer_sum
          UpperCAmelCase          =       classifier_proj_size




      @property
      def      a_   (				self				)    ->       Tuple:
          return functools.reduce(operator.mul ,							self.conv_stride ,							1				)



