
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 ( snake_case__	,unittest.TestCase    ):

     """simple docstring"""

     a_    	=					WavaVecaPhonemeCTCTokenizer
     a_    	=					False


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       super().setUp()

       a_      :	List[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(""" """ )
       a_      :	Tuple      =							dict(zip(_A							,		range(len(_A ) ) ) )

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

       a_      :	str      =							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(_A ) + """\n""" )


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_=False							,		lowerCAmelCase_=20							,		lowerCAmelCase_=5 ):

       '''simple docstring'''

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

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


     def 							_lowerCAmelCase  (      self							,		**lowerCAmelCase_ ):

       '''simple docstring'''

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


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

       # check adding a single token
       tokenizer.add_tokens("""xxx""" )
       a_      :	List[Any]      =							tokenizer("""m xxx ɪ"""							,		do_phonemize=_A ).input_ids
       self.assertEqual(_A							,		[13, 3_92, 17] )  # xxx should be last token

       tokenizer.add_tokens(["""aaa""", """bbb""", """ccc"""] )
       a_      :	Tuple      =							tokenizer("""m aaa ɪ ccc"""							,		do_phonemize=_A ).input_ids
       self.assertEqual(_A							,		[13, 3_93, 17, 3_95] )  # aaa and ccc should be after xxx and 2 after aaa

       a_      :	int      =							tokenizer("""maɪ c"""							,		do_phonemize=_A ).input_ids
       self.assertEqual(_A							,		[3, 2_00] )  # mai should be <unk> (=3)


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

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


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

       a_      :	Tuple      =							'Hello how are you'
       a_      :	Optional[int]      =							tokenizer.phonemize(_A							,		phonemizer_lang="""en-us""" )
       self.assertEqual(tokenizer(_A ).input_ids							,		tokenizer(_A							,		do_phonemize=_A ).input_ids )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	Dict      =							self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft""" )
       a_      :	Optional[int]      =							'Hello how are you'
       a_      :	Dict      =							tokenizer.phonemize(_A							,		phonemizer_lang="""en-us""" )

       a_      :	Any      =							tokenizer.decode(tokenizer(_A ).input_ids )

       self.assertEqual(_A							,		_A )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

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


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	List[str]      =							self.tokenizer_class.from_pretrained(
           """facebook/wav2vec2-lv-60-espeak-cv-ft"""							,		word_delimiter_token="""|""" )
       tokenizer.add_tokens("""|""" )

       a_      :	str      =							'Hello how are you'
       a_      :	Any      =							tokenizer.phonemize(_A							,		phonemizer_lang="""en-us""" )
       self.assertEqual(_A							,		"""h ə l oʊ | h aʊ | ɑːɹ | j uː |""" )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

       a_      :	Tuple      =							'Hello how are you'
       a_      :	Dict      =							tokenizer.phonemize(_A							,		phonemizer_lang="""en-us""" )
       self.assertEqual(tokenizer(_A ).input_ids							,		tokenizer(_A							,		do_phonemize=_A ).input_ids )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	List[str]      =							self.tokenizer_class.from_pretrained(
           """facebook/wav2vec2-lv-60-espeak-cv-ft"""							,		word_delimiter_token="""|""" )
       tokenizer.add_tokens("""|""" )

       # fmt: off
       a_      :	str      =							[
           [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
       a_      :	Dict      =							tokenizer.decode(sample_ids[0] )
       a_      :	Any      =							tokenizer.batch_decode(_A )
       self.assertEqual(_A							,		batch_tokens[0] )
       self.assertEqual(_A							,		["""k s ɾ ɾ l ɭʲ""", """j ð s j ð s oːɹ"""] )

       # decode with no word_del_token filter
       a_      :	List[Any]      =							tokenizer.decode(sample_ids[0]							,		filter_word_delimiter_token=_A )
       a_      :	List[str]      =							tokenizer.batch_decode(_A							,		filter_word_delimiter_token=_A )
       self.assertEqual(_A							,		batch_tokens[0] )
       self.assertEqual(_A							,		["""k s ɾ | ɾ l | ɭʲ""", """| j ð | s j ð s oːɹ"""] )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

       a_      :	Dict      =							'Hello how are you'
       a_      :	List[str]      =							tokenizer.phonemize(_A							,		phonemizer_lang="""en-us""" )

       a_      :	Dict      =							tokenizer.decode(tokenizer(_A ).input_ids							,		filter_word_delimiter_token=_A )

       self.assertEqual(_A							,		_A )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

       a_      :	Any      =							'Hello how are you'
       a_      :	Dict      =							tokenizer.phonemize(_A							,		phonemizer_lang="""en-us""" )

       a_      :	Optional[Any]      =							tokenizer.decode(tokenizer(_A ).input_ids							,		filter_word_delimiter_token=_A )

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


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

       a_      :	List[str]      =							tokenizer(_A							,		phonemizer_lang="""en-us""" ).input_ids
       a_      :	str      =							tokenizer(_A							,		phonemizer_lang="""fr-fr""" ).input_ids

       self.assertNotEqual(_A							,		_A )

       a_      :	List[Any]      =							tokenizer.decode(_A )
       a_      :	Optional[int]      =							tokenizer.decode(_A )

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


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	Tuple      =							self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft""" )
       a_      :	Union[str, Any]      =							'Hello how Are you'
       a_      :	Union[str, Any]      =							'hello how are you'

       a_      :	List[str]      =							tokenizer(_A ).input_ids
       a_      :	Optional[int]      =							tokenizer(_A ).input_ids

       self.assertEqual(_A							,		_A )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

       # fmt: off
       a_      :	Optional[int]      =							[
           [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98, 3_92, 3_92, 3_93, 3_92, 3_92, 3_93, 3_94, 3_94],
           [24, 22, 5, 24, 22, 5, 77, tokenizer.pad_token_id, 3_94, 3_94],
       ]
       # fmt: on

       a_      :	Any      =							tokenizer.batch_decode(_A )
       self.assertEqual(_A							,		["""k s ɾ ɾ l ɭʲ!?!? $$$""", """j ð s j ð s oːɹ $$$"""] )


     @staticmethod
     def 							_lowerCAmelCase  (      lowerCAmelCase_							,		lowerCAmelCase_ ):

       '''simple docstring'''

       a_      :	str      =							[d[key] for d in offsets]
       return retrieved_list


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	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"
       a_      :	Tuple      =							[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

       a_      :	int      =							tokenizer.decode(_A							,		output_char_offsets=_A							,		filter_word_delimiter_token=_A )
       # 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(_A							,		_A ) )

       # 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 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	List[str]      =							self.get_tokenizer(word_delimiter_token="""|""" )

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

         # transform list to ModelOutput
         a_      :	Union[str, 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(lowerCAmelCase_							,		lowerCAmelCase_ ):
           if isinstance(_A							,		_A ):
             [recursive_check(_A							,		_A ) for la, la in zip(_A							,		_A )]
           self.assertEqual(_A							,		_A )

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

        # fmt: off
       a_      :	Dict      =							[
           [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
       a_      :	List[str]      =							tokenizer.batch_decode(_A							,		output_char_offsets=_A )
       a_      :	Tuple      =							[tokenizer.decode(_A							,		output_char_offsets=_A ) for ids in sample_ids]
       check_list_tuples_equal(_A							,		_A )


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

       '''simple docstring'''

       pass


     @unittest.skip("""Wav2Vec2PhonemeTokenizer always puts spaces between phonemes""" )
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       pass


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

       '''simple docstring'''

       pass


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

       '''simple docstring'''

       pass


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	List[str]      =							self.get_tokenizers(do_lower_case=_A )
       for tokenizer in tokenizers:
         with self.subTest(f'''{tokenizer.__class__.__name__}''' ):
           a_      :	Optional[Any]      =							tokenizer.vocab_size
           a_      :	List[str]      =							len(_A )

           self.assertNotEqual(_A							,		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)

           a_      :	int      =							['aaaaa bbbbbb', 'cccccccccdddddddd']
           a_      :	Tuple      =							tokenizer.add_tokens(_A )
           a_      :	Optional[int]      =							tokenizer.vocab_size
           a_      :	Union[str, Any]      =							len(_A )

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

           a_      :	str      =							tokenizer.encode("""aaaaa bbbbbb low cccccccccdddddddd l"""							,		add_special_tokens=_A )

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

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

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

           a_      :	Any      =							tokenizer.encode(
               """>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l"""							,		add_special_tokens=_A )

           self.assertGreaterEqual(len(_A )							,		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 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       pass


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

       '''simple docstring'''

       pass






     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	Optional[Any]      =							self.get_tokenizers(fast=_A							,		do_lower_case=_A )
       for tokenizer in tokenizers:
         with self.subTest(f'''{tokenizer.__class__.__name__}''' ):
           a_      :	Dict      =							['ð', 'ɪ', 's', 'ɪ', 'z', 'ɐ', 't', 'ɛ', 'k', 's', 't']
           a_      :	Union[str, Any]      =							tokenizer.convert_tokens_to_string(_A )

           self.assertIsInstance(output["""text"""]							,		_A )




'''simple docstring'''

from torch import nn






def 	_snake_case						(      A_       :    Dict   ):
  """simple docstring"""







  if act_fn in ["swish", "silu"]:
    return nn.SiLU()
  elif act_fn == "mish":
    return nn.Mish()
  elif act_fn == "gelu":
    return nn.GELU()
  else:
    raise ValueError(f'''Unsupported activation function: {act_fn}'''   )


