





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   A			(SCREAMING_SNAKE_CASE   ,     unittest.TestCase    ):
			'''simple docstring'''




			__lowerCamelCase	:       str							=    WavaVecaPhonemeCTCTokenizer
			__lowerCamelCase	:       Optional[Any]							=    False






			def    a_       (			self   :    Tuple   )	->	Any:







					"""simple docstring"""






					super().setUp()

					A__        =   (
					    """<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__        =   dict(zip(__lowerCAmelCase							,	range(len(__lowerCAmelCase   )   )   )   )

					A__        =   {"""pad_token""": """<pad>""", """unk_token""": """<unk>""", """bos_token""": """<s>""", """eos_token""": """</s>"""}

					A__        =   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    a_       (			self   :    Tuple							,	__lowerCAmelCase   :    Optional[Any]							,	__lowerCAmelCase   :    Tuple=False							,	__lowerCAmelCase   :    str=20							,	__lowerCAmelCase   :    Optional[Any]=5   )	->	Tuple[str, list]:







					"""simple docstring"""






					A__        =   [(i, tokenizer.decode([i]							,	clean_up_tokenization_spaces=__lowerCAmelCase   )) for i in range(len(__lowerCAmelCase   )   )]
					A__        =   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:
							A__        =   toks[:max_length]
					if min_length is not None and len(__lowerCAmelCase   ) < min_length and len(__lowerCAmelCase   ) > 0:
							while len(__lowerCAmelCase   ) < min_length:
									A__        =   toks + toks
        # toks_str = [t[1] for t in toks]
					A__        =   [t[0] for t in toks]

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






			def    a_       (			self   :    Any							,	**__lowerCAmelCase   :    str   )	->	Tuple:







					"""simple docstring"""






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






			def    a_       (			self   :    Optional[Any]   )	->	Optional[int]:







					"""simple docstring"""






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

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

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

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






			def    a_       (			self   :    List[Any]   )	->	Optional[int]:







					"""simple docstring"""






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

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






			def    a_       (			self   :    Optional[Any]   )	->	Dict:







					"""simple docstring"""






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

					A__        =   """Hello how are you"""
					A__        =   tokenizer.phonemize(__lowerCAmelCase							,	phonemizer_lang="""en-us"""   )
					self.assertEqual(tokenizer(__lowerCAmelCase   ).input_ids							,	tokenizer(__lowerCAmelCase							,	do_phonemize=__lowerCAmelCase   ).input_ids   )






			def    a_       (			self   :    List[str]   )	->	Optional[Any]:







					"""simple docstring"""






					A__        =   self.tokenizer_class.from_pretrained("""facebook/wav2vec2-lv-60-espeak-cv-ft"""   )
					A__        =   """Hello how are you"""
					A__        =   tokenizer.phonemize(__lowerCAmelCase							,	phonemizer_lang="""en-us"""   )

					A__        =   tokenizer.decode(tokenizer(__lowerCAmelCase   ).input_ids   )

					self.assertEqual(__lowerCAmelCase							,	__lowerCAmelCase   )






			def    a_       (			self   :    List[str]   )	->	Optional[int]:







					"""simple docstring"""






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

					A__        =   [
					    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
					    [24, 22, 5, 24, 22, 5, 77],
					]
					A__        =   tokenizer.decode(sample_ids[0]   )
					A__        =   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    a_       (			self   :    List[Any]   )	->	str:







					"""simple docstring"""






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

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






			def    a_       (			self   :    List[Any]   )	->	Tuple:







					"""simple docstring"""






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

					A__        =   """Hello how are you"""
					A__        =   tokenizer.phonemize(__lowerCAmelCase							,	phonemizer_lang="""en-us"""   )
					self.assertEqual(tokenizer(__lowerCAmelCase   ).input_ids							,	tokenizer(__lowerCAmelCase							,	do_phonemize=__lowerCAmelCase   ).input_ids   )






			def    a_       (			self   :    List[Any]   )	->	Any:







					"""simple docstring"""






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

					# fmt: off
					A__        =   [
					    [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__        =   tokenizer.decode(sample_ids[0]   )
					A__        =   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
					A__        =   tokenizer.decode(sample_ids[0]							,	filter_word_delimiter_token=__lowerCAmelCase   )
					A__        =   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    a_       (			self   :    Dict   )	->	Tuple:







					"""simple docstring"""






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

					A__        =   """Hello how are you"""
					A__        =   tokenizer.phonemize(__lowerCAmelCase							,	phonemizer_lang="""en-us"""   )

					A__        =   tokenizer.decode(tokenizer(__lowerCAmelCase   ).input_ids							,	filter_word_delimiter_token=__lowerCAmelCase   )

					self.assertEqual(__lowerCAmelCase							,	__lowerCAmelCase   )






			def    a_       (			self   :    Dict   )	->	Union[str, Any]:







					"""simple docstring"""






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

					A__        =   """Hello how are you"""
					A__        =   tokenizer.phonemize(__lowerCAmelCase							,	phonemizer_lang="""en-us"""   )

					A__        =   tokenizer.decode(tokenizer(__lowerCAmelCase   ).input_ids							,	filter_word_delimiter_token=__lowerCAmelCase   )

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






			def    a_       (			self   :    List[str]   )	->	Any:







					"""simple docstring"""






					A__        =   self.tokenizer_class.from_pretrained(
					    """facebook/wav2vec2-lv-60-espeak-cv-ft"""							,	word_delimiter_token=__lowerCAmelCase   )
					A__        =   """Hello how are you"""

					A__        =   tokenizer(__lowerCAmelCase							,	phonemizer_lang="""en-us"""   ).input_ids
					A__        =   tokenizer(__lowerCAmelCase							,	phonemizer_lang="""fr-fr"""   ).input_ids

					self.assertNotEqual(__lowerCAmelCase							,	__lowerCAmelCase   )

					A__        =   tokenizer.decode(__lowerCAmelCase   )
					A__        =   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    a_       (			self   :    List[Any]   )	->	Optional[Any]:







					"""simple docstring"""






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

					A__        =   tokenizer(__lowerCAmelCase   ).input_ids
					A__        =   tokenizer(__lowerCAmelCase   ).input_ids

					self.assertEqual(__lowerCAmelCase							,	__lowerCAmelCase   )






			def    a_       (			self   :    Union[str, Any]   )	->	Tuple:







					"""simple docstring"""






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

					# fmt: off
					A__        =   [
					    [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__        =   tokenizer.batch_decode(__lowerCAmelCase   )
					self.assertEqual(__lowerCAmelCase							,	["""k s ɾ ɾ l ɭʲ!?!? $$$""", """j ð s j ð s oːɹ $$$"""]   )






			@staticmethod
			def    a_       (			__lowerCAmelCase   :    Tuple							,	__lowerCAmelCase   :    int   )	->	List[Any]:







					"""simple docstring"""






					A__        =   [d[key] for d in offsets]
					return retrieved_list






			def    a_       (			self   :    Dict   )	->	int:







					"""simple docstring"""






					A__        =   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__        =   [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__        =   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, 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   :    Dict   )	->	Union[str, Any]:







					"""simple docstring"""






					A__        =   self.get_tokenizer(word_delimiter_token="""|"""   )

					def check_list_tuples_equal(__lowerCAmelCase   :    Any							,	__lowerCAmelCase   :    Tuple   ):
							self.assertTrue(isinstance(__lowerCAmelCase							,	__lowerCAmelCase   )   )
							self.assertTrue(isinstance(outputs_list[0]							,	__lowerCAmelCase   )   )

							# transform list to ModelOutput
							A__        =   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   :    List[str]							,	__lowerCAmelCase   :    int   ):
									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
					A__        =   [
					    [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__        =   tokenizer.batch_decode(__lowerCAmelCase							,	output_char_offsets=__lowerCAmelCase   )
					A__        =   [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    a_       (			self   :    Any   )	->	List[str]:







					"""simple docstring"""






					pass






			@unittest.skip("""Wav2Vec2PhonemeTokenizer always puts spaces between phonemes"""   )
			def    a_       (			self   :    Optional[int]   )	->	List[str]:







					"""simple docstring"""






					pass






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







					"""simple docstring"""






					pass






			@unittest.skip("""Wav2Vec2PhonemeModel has no max model length => no testing"""   )
			def    a_       (			self   :    Any   )	->	Union[str, Any]:







					"""simple docstring"""






					pass






			def    a_       (			self   :    str   )	->	str:







					"""simple docstring"""






					A__        =   self.get_tokenizers(do_lower_case=__lowerCAmelCase   )
					for tokenizer in tokenizers:
							with self.subTest(f'{tokenizer.__class__.__name__}'   ):
									A__        =   tokenizer.vocab_size
									A__        =   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)

									A__        =   ["""aaaaa bbbbbb""", """cccccccccdddddddd"""]
									A__        =   tokenizer.add_tokens(__lowerCAmelCase   )
									A__        =   tokenizer.vocab_size
									A__        =   len(__lowerCAmelCase   )

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

									A__        =   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   )

									A__        =   {"""eos_token""": """>>>>|||<||<<|<<""", """pad_token""": """<<<<<|||>|>>>>|>"""}
									A__        =   tokenizer.add_special_tokens(__lowerCAmelCase   )
									A__        =   tokenizer.vocab_size
									A__        =   len(__lowerCAmelCase   )

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

									A__        =   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    a_       (			self   :    Any   )	->	Union[str, Any]:







					"""simple docstring"""






					pass






			@unittest.skip("""The tokenizer shouldn't be used to encode input IDs (except for labels), only to decode."""   )
			def    a_       (			self   :    Any   )	->	int:







					"""simple docstring"""






					pass







			def    a_       (			self   :    List[Any]   )	->	Union[str, Any]:







					"""simple docstring"""






					A__        =   self.get_tokenizers(fast=__lowerCAmelCase							,	do_lower_case=__lowerCAmelCase   )
					for tokenizer in tokenizers:
							with self.subTest(f'{tokenizer.__class__.__name__}'   ):
									A__        =   ["""ð""", """ɪ""", """s""", """ɪ""", """z""", """ɐ""", """t""", """ɛ""", """k""", """s""", """t"""]
									A__        =   tokenizer.convert_tokens_to_string(__lowerCAmelCase   )

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










# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py

import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile







def    __lowerCamelCase					(							__a   :List[str]    ,     __a   :List[Any]    ,     __a   :Union[str, Any]    ,     __a   :List[Any]    )		->				Dict:






		"""simple docstring"""

		A__        =   multiprocessing.Manager()
		A__        =   manager.list()

		A__        =   multiprocessing.Process(target=__a    ,     args=(check_program, result, timeout)    )
		p.start()
		p.join(timeout=timeout + 1    )
		if p.is_alive():
				p.kill()

		if not result:
				result.append("""timed out"""    )

		return {
		    "task_id": task_id,
		    "passed": result[0] == "passed",
		    "result": result[0],
		    "completion_id": completion_id,
		}







def    __lowerCamelCase					(							__a   :Optional[Any]    ,     __a   :Any    ,     __a   :List[Any]    )		->				Union[str, Any]:






		"""simple docstring"""

		with create_tempdir():
				# These system calls are needed when cleaning up tempdir.
				import os
				import shutil

				A__        =   shutil.rmtree
				A__        =   os.rmdir
				A__        =   os.chdir

				# Disable functionalities that can make destructive changes to the test.
				reliability_guard()

				# Run program.
				try:
						A__        =   {}
						with swallow_io():
								with time_limit(__a    ):
										exec(__a    ,     __a    )
						result.append("""passed"""    )
				except TimeoutException:
						result.append("""timed out"""    )
				except BaseException as e:
						result.append(F'failed: {e}'    )

				# Needed for cleaning up.
				A__        =   rmtree
				A__        =   rmdir
				A__        =   chdir







@contextlib.contextmanager
def    __lowerCamelCase					(							__a   :List[str]    )		->				Dict:






		"""simple docstring"""

		def signal_handler(__a   :List[Any]    ,     __a   :Optional[Any]    ):
				raise TimeoutException("""Timed out!"""    )

		signal.setitimer(signal.ITIMER_REAL    ,     __a    )
		signal.signal(signal.SIGALRM    ,     __a    )
		try:
				yield
		finally:
				signal.setitimer(signal.ITIMER_REAL    ,     0    )







@contextlib.contextmanager
def    __lowerCamelCase					(							)		->				Union[str, Any]:






		"""simple docstring"""

		A__        =   WriteOnlyStringIO()
		with contextlib.redirect_stdout(__a    ):
				with contextlib.redirect_stderr(__a    ):
						with redirect_stdin(__a    ):
								yield







@contextlib.contextmanager
def    __lowerCamelCase					(							)		->				Dict:






		"""simple docstring"""

		with tempfile.TemporaryDirectory() as dirname:
				with chdir(__a    ):
						yield dirname


class   A			(SCREAMING_SNAKE_CASE    ):
			'''simple docstring'''




			pass


class   A			(io.StringIO    ):
			'''simple docstring'''




			def    a_       (			self   :    Any							,	*__lowerCAmelCase   :    List[str]							,	**__lowerCAmelCase   :    str   )	->	Dict:







					"""simple docstring"""






					raise OSError






			def    a_       (			self   :    Optional[Any]							,	*__lowerCAmelCase   :    Any							,	**__lowerCAmelCase   :    Optional[int]   )	->	str:







					"""simple docstring"""






					raise OSError






			def    a_       (			self   :    Optional[Any]							,	*__lowerCAmelCase   :    Any							,	**__lowerCAmelCase   :    Any   )	->	int:







					"""simple docstring"""






					raise OSError







			def    a_       (			self   :    str							,	*__lowerCAmelCase   :    Any							,	**__lowerCAmelCase   :    Union[str, Any]   )	->	int:







					"""simple docstring"""






					return False


class   A			(contextlib._RedirectStream    ):  # type: ignore
			'''simple docstring'''




			__lowerCamelCase	:       Union[str, Any]							=    '''stdin'''







@contextlib.contextmanager
def    __lowerCamelCase					(							__a   :Union[str, Any]    )		->				List[str]:






		"""simple docstring"""

		if root == ".":
				yield
				return
		A__        =   os.getcwd()
		os.chdir(__a    )
		try:
				yield
		except BaseException as exc:
				raise exc
		finally:
				os.chdir(__a    )







def    __lowerCamelCase					(							__a   :Union[str, Any]=None    )		->				Dict:






		"""simple docstring"""

		if maximum_memory_bytes is not None:
				import resource

				resource.setrlimit(resource.RLIMIT_AS    ,     (maximum_memory_bytes, maximum_memory_bytes)    )
				resource.setrlimit(resource.RLIMIT_DATA    ,     (maximum_memory_bytes, maximum_memory_bytes)    )
				if not platform.uname().system == "Darwin":
						resource.setrlimit(resource.RLIMIT_STACK    ,     (maximum_memory_bytes, maximum_memory_bytes)    )

		faulthandler.disable()

		import builtins

		A__        =   None
		A__        =   None

		import os

		A__        =   """1"""

		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None

		import shutil

		A__        =   None
		A__        =   None
		A__        =   None

		import subprocess

		A__        =   None  # type: ignore

		A__        =   None

		import sys

		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None
		A__        =   None



