





import json
import os
import unittest
from typing import Tuple

from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from transformers.testing_utils import require_phonemizer

from ...test_tokenization_common import TokenizerTesterMixin


@require_phonemizer
class 						lowerCamelCase       (__lowerCamelCase							,     unittest.TestCase      ):







							"""simple docstring"""




							UpperCAmelCase_      						=   WavaVecaPhonemeCTCTokenizer
							UpperCAmelCase_      						=   False






							def  A_     ( self     :					List[str]						)				->			Dict:





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

														SCREAMING_SNAKE_CASE__       :      Optional[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(" "						)
														SCREAMING_SNAKE_CASE__       :      Any     =						dict(zip(_UpperCAmelCase,			range(len(_UpperCAmelCase						)						)						)						)

														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						{"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

														SCREAMING_SNAKE_CASE__       :      Dict     =						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(_UpperCAmelCase						) + "\n"						)






							def  A_     ( self     :					str,			_UpperCAmelCase     :					Union[str, Any],			_UpperCAmelCase     :					Optional[Any]=False,			_UpperCAmelCase     :					str=2_0,			_UpperCAmelCase     :					Tuple=5						)				->			Tuple[str, list]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						[(i, tokenizer.decode([i],			clean_up_tokenization_spaces=_UpperCAmelCase						)) for i in range(len(_UpperCAmelCase						)						)]
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						list(filter(lambda _UpperCAmelCase						: [t[0]] == tokenizer.encode(t[1],			do_phonemize=_UpperCAmelCase						),			_UpperCAmelCase						)						)
														if max_length is not None and len(_UpperCAmelCase						) > max_length:
																					SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						toks[:max_length]
														if min_length is not None and len(_UpperCAmelCase						) < min_length and len(_UpperCAmelCase						) > 0:
																					while len(_UpperCAmelCase						) < min_length:
																												SCREAMING_SNAKE_CASE__       :      Dict     =						toks + toks
        # toks_str = [t[1] for t in toks]
														SCREAMING_SNAKE_CASE__       :      Any     =						[t[0] for t in toks]

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






							def  A_     ( self     :					Any,			**_UpperCAmelCase     :					Tuple						)				->			int:





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






							def  A_     ( self     :					int						)				->			Optional[int]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)

														# check adding a single token
														tokenizer.add_tokens("xxx"						)
														SCREAMING_SNAKE_CASE__       :      Tuple     =						tokenizer("m xxx ɪ",			do_phonemize=_UpperCAmelCase						).input_ids
														self.assertEqual(_UpperCAmelCase,			[1_3, 3_9_2, 1_7]						)  # xxx should be last token

														tokenizer.add_tokens(["aaa", "bbb", "ccc"]						)
														SCREAMING_SNAKE_CASE__       :      str     =						tokenizer("m aaa ɪ ccc",			do_phonemize=_UpperCAmelCase						).input_ids
														self.assertEqual(_UpperCAmelCase,			[1_3, 3_9_3, 1_7, 3_9_5]						)  # aaa and ccc should be after xxx and 2 after aaa

														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						tokenizer("maɪ c",			do_phonemize=_UpperCAmelCase						).input_ids
														self.assertEqual(_UpperCAmelCase,			[3, 2_0_0]						)  # mai should be <unk> (=3)






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





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)

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






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





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Tuple     =						self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)

														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						"Hello how are you"
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						tokenizer.phonemize(_UpperCAmelCase,			phonemizer_lang="en-us"						)
														self.assertEqual(tokenizer(_UpperCAmelCase						).input_ids,			tokenizer(_UpperCAmelCase,			do_phonemize=_UpperCAmelCase						).input_ids						)






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





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      List[str]     =						self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)
														SCREAMING_SNAKE_CASE__       :      str     =						"Hello how are you"
														SCREAMING_SNAKE_CASE__       :      int     =						tokenizer.phonemize(_UpperCAmelCase,			phonemizer_lang="en-us"						)

														SCREAMING_SNAKE_CASE__       :      str     =						tokenizer.decode(tokenizer(_UpperCAmelCase						).input_ids						)

														self.assertEqual(_UpperCAmelCase,			_UpperCAmelCase						)






							def  A_     ( self     :					Optional[int]						)				->			Optional[int]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Tuple     =						self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)

														SCREAMING_SNAKE_CASE__       :      str     =						[
														    [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],
														]
														SCREAMING_SNAKE_CASE__       :      Tuple     =						tokenizer.decode(sample_ids[0]						)
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						tokenizer.batch_decode(_UpperCAmelCase						)
														self.assertEqual(_UpperCAmelCase,			batch_tokens[0]						)
														self.assertEqual(_UpperCAmelCase,			["k s ɾ ɾ l ɭʲ", "j ð s j ð s oːɹ"]						)






							def  A_     ( self     :					int						)				->			Any:





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

														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						"Hello how are you"
														SCREAMING_SNAKE_CASE__       :      Tuple     =						tokenizer.phonemize(_UpperCAmelCase,			phonemizer_lang="en-us"						)
														self.assertEqual(_UpperCAmelCase,			"h ə l oʊ | h aʊ | ɑːɹ | j uː |"						)






							def  A_     ( self     :					Dict						)				->			List[str]:





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

														SCREAMING_SNAKE_CASE__       :      List[Any]     =						"Hello how are you"
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						tokenizer.phonemize(_UpperCAmelCase,			phonemizer_lang="en-us"						)
														self.assertEqual(tokenizer(_UpperCAmelCase						).input_ids,			tokenizer(_UpperCAmelCase,			do_phonemize=_UpperCAmelCase						).input_ids						)






							def  A_     ( self     :					Union[str, Any]						)				->			int:





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

														# fmt: off
														SCREAMING_SNAKE_CASE__       :      Tuple     =						[
														    [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
														SCREAMING_SNAKE_CASE__       :      int     =						tokenizer.decode(sample_ids[0]						)
														SCREAMING_SNAKE_CASE__       :      int     =						tokenizer.batch_decode(_UpperCAmelCase						)
														self.assertEqual(_UpperCAmelCase,			batch_tokens[0]						)
														self.assertEqual(_UpperCAmelCase,			["k s ɾ ɾ l ɭʲ", "j ð s j ð s oːɹ"]						)

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






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





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

														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						"Hello how are you"
														SCREAMING_SNAKE_CASE__       :      int     =						tokenizer.phonemize(_UpperCAmelCase,			phonemizer_lang="en-us"						)

														SCREAMING_SNAKE_CASE__       :      List[str]     =						tokenizer.decode(tokenizer(_UpperCAmelCase						).input_ids,			filter_word_delimiter_token=_UpperCAmelCase						)

														self.assertEqual(_UpperCAmelCase,			_UpperCAmelCase						)






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





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

														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						"Hello how are you"
														SCREAMING_SNAKE_CASE__       :      Tuple     =						tokenizer.phonemize(_UpperCAmelCase,			phonemizer_lang="en-us"						)

														SCREAMING_SNAKE_CASE__       :      str     =						tokenizer.decode(tokenizer(_UpperCAmelCase						).input_ids,			filter_word_delimiter_token=_UpperCAmelCase						)

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






							def  A_     ( self     :					Any						)				->			str:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.tokenizer_class.from_pretrained(
														    "facebook/wav2vec2-lv-60-espeak-cv-ft",			word_delimiter_token=_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						"Hello how are you"

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

														self.assertNotEqual(_UpperCAmelCase,			_UpperCAmelCase						)

														SCREAMING_SNAKE_CASE__       :      Any     =						tokenizer.decode(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						tokenizer.decode(_UpperCAmelCase						)

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






							def  A_     ( self     :					Optional[int]						)				->			Union[str, Any]:





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

														SCREAMING_SNAKE_CASE__       :      Dict     =						tokenizer(_UpperCAmelCase						).input_ids
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						tokenizer(_UpperCAmelCase						).input_ids

														self.assertEqual(_UpperCAmelCase,			_UpperCAmelCase						)






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





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

														# fmt: off
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						[
														    [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

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






							@staticmethod
							def  A_     ( _UpperCAmelCase     :					Any,			_UpperCAmelCase     :					List[Any]						)				->			Optional[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      str     =						[d[key] for d in offsets]
														return retrieved_list






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





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      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"
														SCREAMING_SNAKE_CASE__       :      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

														SCREAMING_SNAKE_CASE__       :      Any     =						tokenizer.decode(_UpperCAmelCase,			output_char_offsets=_UpperCAmelCase,			filter_word_delimiter_token=_UpperCAmelCase						)
														# 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(_UpperCAmelCase,			_UpperCAmelCase						)						)

														# 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  A_     ( self     :					Tuple						)				->			List[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Dict     =						self.get_tokenizer(word_delimiter_token="|"						)

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

																					# transform list to ModelOutput
																					SCREAMING_SNAKE_CASE__       :      Tuple     =						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(_UpperCAmelCase     :					Optional[Any],			_UpperCAmelCase     :					Union[str, Any]						):
																												if isinstance(_UpperCAmelCase,			_UpperCAmelCase						):
																																			[recursive_check(_UpperCAmelCase,			_UpperCAmelCase						) for la, la in zip(_UpperCAmelCase,			_UpperCAmelCase						)]
																												self.assertEqual(_UpperCAmelCase,			_UpperCAmelCase						)

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

        # fmt: off
														SCREAMING_SNAKE_CASE__       :      Dict     =						[
														    [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
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						tokenizer.batch_decode(_UpperCAmelCase,			output_char_offsets=_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						[tokenizer.decode(_UpperCAmelCase,			output_char_offsets=_UpperCAmelCase						) for ids in sample_ids]
														check_list_tuples_equal(_UpperCAmelCase,			_UpperCAmelCase						)






							@unittest.skip("Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes"						)
							def  A_     ( self     :					Any						)				->			int:





														"""simple docstring"""
														pass






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





														"""simple docstring"""
														pass






							@unittest.skip("encodes to text to ids, but decodes ids to phonemes -> not possible to have internal consistency"						)
							def  A_     ( self     :					str						)				->			List[Any]:





														"""simple docstring"""
														pass






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





														"""simple docstring"""
														pass






							def  A_     ( self     :					Tuple						)				->			Optional[int]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						self.get_tokenizers(do_lower_case=_UpperCAmelCase						)
														for tokenizer in tokenizers:
																					with self.subTest(F'''{tokenizer.__class__.__name__}'''						):
																												SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						tokenizer.vocab_size
																												SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						len(_UpperCAmelCase						)

																												self.assertNotEqual(_UpperCAmelCase,			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)

																												SCREAMING_SNAKE_CASE__       :      List[str]     =						["aaaaa bbbbbb", "cccccccccdddddddd"]
																												SCREAMING_SNAKE_CASE__       :      int     =						tokenizer.add_tokens(_UpperCAmelCase						)
																												SCREAMING_SNAKE_CASE__       :      List[Any]     =						tokenizer.vocab_size
																												SCREAMING_SNAKE_CASE__       :      List[str]     =						len(_UpperCAmelCase						)

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

																												SCREAMING_SNAKE_CASE__       :      Dict     =						tokenizer.encode("aaaaa bbbbbb low cccccccccdddddddd l",			add_special_tokens=_UpperCAmelCase						)

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

																												SCREAMING_SNAKE_CASE__       :      Optional[int]     =						{"eos_token": ">>>>|||<||<<|<<", "pad_token": "<<<<<|||>|>>>>|>"}
																												SCREAMING_SNAKE_CASE__       :      Any     =						tokenizer.add_special_tokens(_UpperCAmelCase						)
																												SCREAMING_SNAKE_CASE__       :      str     =						tokenizer.vocab_size
																												SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						len(_UpperCAmelCase						)

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

																												SCREAMING_SNAKE_CASE__       :      List[str]     =						tokenizer.encode(
																												    ">>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l",			add_special_tokens=_UpperCAmelCase						)

																												self.assertGreaterEqual(len(_UpperCAmelCase						),			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     :					Optional[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     :					Union[str, Any]						)				->			List[str]:





														"""simple docstring"""
														pass






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





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

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













import requests
from bsa import BeautifulSoup




def _a (  SCREAMING_SNAKE_CASE__      :  str			,				SCREAMING_SNAKE_CASE__      :  dict       )	->    str:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      Any     =						BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE__			,				params=SCREAMING_SNAKE_CASE__       ).content			,				"html.parser"       )
							SCREAMING_SNAKE_CASE__       :      str     =						soup.find("div"			,				attrs={"class": "gs_ri"}       )
							SCREAMING_SNAKE_CASE__       :      int     =						div.find("div"			,				attrs={"class": "gs_fl"}       ).find_all("a"       )
							return anchors[2].get_text()


if __name__ == "__main__":
		_lowerCamelCase :    Any  							= {
		    '''title''': (
		        '''Precisely geometry controlled microsupercapacitors for ultrahigh areal '''
		        '''capacitance, volumetric capacitance, and energy density'''
		    ),
		    '''journal''': '''Chem. Mater.''',
		    '''volume''': 3_0,
		    '''pages''': '''3979-3990''',
		    '''year''': 2_0_1_8,
		    '''hl''': '''en''',
		}
		print(get_citation('''https://scholar.google.com/scholar_lookup''', params=params))






