
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__							(				__lowercase     ,						unittest.TestCase):




	'''simple docstring'''




	_A								=     WavaVecaPhonemeCTCTokenizer
	_A								=     False







	def    _lowerCamelCase				(					self		:Tuple						)		-> Optional[Any]:
								super().setUp()

								__UpperCamelCase	:   Tuple			   =					(
								    "<s> <pad> </s> <unk> n s t ə l a i k d m ɛ ɾ e ɪ p o ɐ z ð f j v b ɹ ʁ ʊ iː r w ʌ u ɡ æ aɪ ʃ h ɔ ɑː "
								    "ŋ ɚ eɪ β uː y ɑ̃ oʊ ᵻ eː θ aʊ ts oː ɔ̃ ɣ ɜ ɑ dʒ əl x ɜː ç ʒ tʃ ɔː ɑːɹ ɛ̃ ʎ ɔːɹ ʋ aː ɕ œ ø oːɹ ɲ yː "
								    "ʔ iə i5 s. tɕ ?? nʲ ɛː œ̃ ɭ ɔø ʑ tʲ ɨ ɛɹ ts. rʲ ɪɹ ɭʲ i.5 ɔɪ q sʲ u5 ʊɹ iɜ a5 iɛ5 øː ʕ ja əɜ th ɑ5 "
								    "oɪ dʲ ə5 tɕh ts.h mʲ ɯ dʑ vʲ e̞ tʃʲ ei5 o5 onɡ5 ɑu5 iɑ5 ai5 aɪɚ kh ə1 ʐ i2 ʉ ħ t[ aɪə ʲ ju ə2 u2 oɜ "
								    "pː iɛɜ ou5 y5 uɜ tː uo5 d[ uoɜ tsh ɑɜ ɵ i̪5 uei5 ɟ aɜ ɑɨ i.ɜ eʊ o2 ɐ̃ ä pʲ kʲ n̩ ɒ ph ɑu2 uɨ əɪ ɫ ɬ "
								    "yɜ bʲ ɑ2 s̪ aiɜ χ ɐ̃ʊ̃ 1 ə4 yæɜ a2 ɨː t̪ iouɜ ũ onɡɜ aɨ iɛ2 ɔɨ ɑuɜ o̞ ei2 iou2 c kː y2 ɖ oe dˤ yɛɜ "
								    "əʊ S ɡʲ onɡ2 u\" eiɜ ʈ ɯᵝ iou5 dZ r̝̊ i.2 tS s^ ʝ yə5 iɑɜ uə5 pf ɨu iɑ2 ou2 ər2 fʲ ai2 r̝ uəɜ ɳ əɨ "
								    "ua5 uɪ ɽ bː yu5 uo2 yɛ5 l̩ ɻ ərɜ ʂ i̪2 ouɜ uaɜ a. a.ː yæ5 dː r̩ ee ɪu ər5 i̪ ɜ æi u: i.ː t^ o1 ɪ^ "
								    "ai ueiɜ æː ɛɪ eə i. ɴ ie ua2 ɑ1 o4 tʃː o: ɑ: u1 N i̪1 au yæ2 u. qː yəɜ y: kʰ tʃʰ iʊ sx õ uo tʰ "
								    "uai5 bʰ u.ː uə2 ʊə d^ s̪ː yiɜ dʰ r. oe: i1 ɟː yu2 nʲʲ i̪4 uei2 tsʲ ɸ ĩ ɑ4 t̪ː eɑ u4 e: tsː ʈʰ ɡʰ "
								    "ɯɯ dʒʲ ʂʲ X ɵː uaiɜ tɕʲ ã t^ː ẽː yɛ2 cː i.1 ɛʊ dˤdˤ dʒː i4 ɡː yi ɕʲ ɟʰ pʰ dʑʲ yuɜ ua1 ua4 æiː ɐɐ "
								    "ui iou1 ʊː a1 iou4 cʰ iɛ1 yə2 ɖʰ ẽ ʒʲ ää ər4 iːː ɪː iɑ1 ər1 œː øi ɪuː cʰcʰ əː1 iː1 ũ kʰː o̞o̞ xʲ "
								    "ou1 iɛ4 e̞e̞ y1 dzː dʲʲ dʰː ɯᵝɯᵝ lː uo1 i.4 i: yɛ5ʲ a4"
								).split(" "						)
								__UpperCamelCase	:   Optional[int]			   =					dict(zip(a     ,   range(len(a						)						)						)						)

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

								__UpperCamelCase	:   List[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		:List[str]     ,   a		:List[str]     ,   a		:Optional[int]=False     ,   a		:str=2_0     ,   a		:Dict=5						)		-> Tuple[str, list]:
								__UpperCamelCase	:   Union[str, Any]			   =					[(i, tokenizer.decode([i]     ,   clean_up_tokenization_spaces=a						)) for i in range(len(a						)						)]
								__UpperCamelCase	:   Union[str, Any]			   =					list(filter(lambda a						: [t[0]] == tokenizer.encode(t[1]     ,   do_phonemize=a						)     ,   a						)						)
								if max_length is not None and len(a						) > max_length:
															__UpperCamelCase	:   str			   =					toks[:max_length]
								if min_length is not None and len(a						) < min_length and len(a						) > 0:
															while len(a						) < min_length:
																						__UpperCamelCase	:   Dict			   =					toks + toks
        # toks_str = [t[1] for t in toks]
								__UpperCamelCase	:   List[Any]			   =					[t[0] for t in toks]

								# Ensure consistency
								__UpperCamelCase	:   Dict			   =					tokenizer.decode(a     ,   clean_up_tokenization_spaces=a						)
								if " " not in output_txt and len(a						) > 1:
															__UpperCamelCase	:   Optional[int]			   =					(
															    tokenizer.decode([toks_ids[0]]     ,   clean_up_tokenization_spaces=a						)
															    + " "
															    + tokenizer.decode(toks_ids[1:]     ,   clean_up_tokenization_spaces=a						)
															)
								if with_prefix_space:
															__UpperCamelCase	:   Tuple			   =					" " + output_txt
								__UpperCamelCase	:   Tuple			   =					tokenizer.encode(a     ,   add_special_tokens=a						)
								return output_txt, output_ids







	def    _lowerCamelCase				(					self		:int     ,   **a		:str						)		-> Tuple:
								kwargs.update(self.special_tokens_map						)
								return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname     ,   **a						)







	def    _lowerCamelCase				(					self		:Union[str, Any]						)		-> List[Any]:
								__UpperCamelCase	:   Union[str, Any]			   =					self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)

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

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

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







	def    _lowerCamelCase				(					self		:str						)		-> int:
								__UpperCamelCase	:   List[str]			   =					self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)

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







	def    _lowerCamelCase				(					self		:Tuple						)		-> int:
								__UpperCamelCase	:   Optional[int]			   =					self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)

								__UpperCamelCase	:   Tuple			   =					"Hello how are you"
								__UpperCamelCase	:   Any			   =					tokenizer.phonemize(a     ,   phonemizer_lang="en-us"						)
								self.assertEqual(tokenizer(a						).input_ids     ,   tokenizer(a     ,   do_phonemize=a						).input_ids						)







	def    _lowerCamelCase				(					self		:Optional[Any]						)		-> Optional[Any]:
								__UpperCamelCase	:   Union[str, Any]			   =					self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)
								__UpperCamelCase	:   Union[str, Any]			   =					"Hello how are you"
								__UpperCamelCase	:   Any			   =					tokenizer.phonemize(a     ,   phonemizer_lang="en-us"						)

								__UpperCamelCase	:   Optional[Any]			   =					tokenizer.decode(tokenizer(a						).input_ids						)

								self.assertEqual(a     ,   a						)







	def    _lowerCamelCase				(					self		:Dict						)		-> str:
								__UpperCamelCase	:   Dict			   =					self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)

								__UpperCamelCase	:   Any			   =					[
								    [1_1, 5, 1_5, tokenizer.pad_token_id, 1_5, 8, 9_8],
								    [2_4, 2_2, 5, 2_4, 2_2, 5, 7_7],
								]
								__UpperCamelCase	:   Any			   =					tokenizer.decode(sample_ids[0]						)
								__UpperCamelCase	:   Optional[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		:Optional[Any]						)		-> Dict:
								__UpperCamelCase	:   str			   =					self.tokenizer_class.from_pretrained(
								    "facebook/wav2vec2-lv-60-espeak-cv-ft"     ,   word_delimiter_token="|"						)
								tokenizer.add_tokens("|"						)

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







	def    _lowerCamelCase				(					self		:List[str]						)		-> Dict:
								__UpperCamelCase	:   Tuple			   =					self.tokenizer_class.from_pretrained(
								    "facebook/wav2vec2-lv-60-espeak-cv-ft"     ,   word_delimiter_token="|"						)
								tokenizer.add_tokens("|"						)

								__UpperCamelCase	:   str			   =					"Hello how are you"
								__UpperCamelCase	:   Dict			   =					tokenizer.phonemize(a     ,   phonemizer_lang="en-us"						)
								self.assertEqual(tokenizer(a						).input_ids     ,   tokenizer(a     ,   do_phonemize=a						).input_ids						)







	def    _lowerCamelCase				(					self		:Dict						)		-> Tuple:
								__UpperCamelCase	:   Any			   =					self.tokenizer_class.from_pretrained(
								    "facebook/wav2vec2-lv-60-espeak-cv-ft"     ,   word_delimiter_token="|"						)
								tokenizer.add_tokens("|"						)

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

								# decode with word_del_token filter
								__UpperCamelCase	:   int			   =					tokenizer.decode(sample_ids[0]						)
								__UpperCamelCase	:   str			   =					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
								__UpperCamelCase	:   int			   =					tokenizer.decode(sample_ids[0]     ,   filter_word_delimiter_token=a						)
								__UpperCamelCase	:   Optional[Any]			   =					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		:List[Any]						)		-> Dict:
								__UpperCamelCase	:   Tuple			   =					self.tokenizer_class.from_pretrained(
								    "facebook/wav2vec2-lv-60-espeak-cv-ft"     ,   word_delimiter_token="|"						)
								tokenizer.add_tokens("|"						)

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

								__UpperCamelCase	:   int			   =					tokenizer.decode(tokenizer(a						).input_ids     ,   filter_word_delimiter_token=a						)

								self.assertEqual(a     ,   a						)







	def    _lowerCamelCase				(					self		:Any						)		-> List[str]:
								__UpperCamelCase	:   Optional[int]			   =					self.tokenizer_class.from_pretrained(
								    "facebook/wav2vec2-lv-60-espeak-cv-ft"     ,   word_delimiter_token="|"						)
								tokenizer.add_tokens("|"						)

								__UpperCamelCase	:   List[Any]			   =					"Hello how are you"
								__UpperCamelCase	:   Dict			   =					tokenizer.phonemize(a     ,   phonemizer_lang="en-us"						)

								__UpperCamelCase	:   int			   =					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		:int						)		-> List[str]:
								__UpperCamelCase	:   Optional[Any]			   =					self.tokenizer_class.from_pretrained(
								    "facebook/wav2vec2-lv-60-espeak-cv-ft"     ,   word_delimiter_token=a						)
								__UpperCamelCase	:   List[Any]			   =					"Hello how are you"

								__UpperCamelCase	:   Union[str, Any]			   =					tokenizer(a     ,   phonemizer_lang="en-us"						).input_ids
								__UpperCamelCase	:   Any			   =					tokenizer(a     ,   phonemizer_lang="fr-fr"						).input_ids

								self.assertNotEqual(a     ,   a						)

								__UpperCamelCase	:   str			   =					tokenizer.decode(a						)
								__UpperCamelCase	:   Union[str, Any]			   =					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		:List[str]						)		-> Union[str, Any]:
								__UpperCamelCase	:   Optional[int]			   =					self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"						)
								__UpperCamelCase	:   List[str]			   =					"Hello how Are you"
								__UpperCamelCase	:   int			   =					"hello how are you"

								__UpperCamelCase	:   int			   =					tokenizer(a						).input_ids
								__UpperCamelCase	:   str			   =					tokenizer(a						).input_ids

								self.assertEqual(a     ,   a						)







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

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

								__UpperCamelCase	:   Optional[int]			   =					tokenizer.batch_decode(a						)
								self.assertEqual(a     ,   ["k s ɾ ɾ l ɭʲ!?!? $$$", "j ð s j ð s oːɹ $$$"]						)







	@staticmethod
	def    _lowerCamelCase				(					a		:List[Any]     ,   a		:str						)		-> List[str]:
								__UpperCamelCase	:   str			   =					[d[key] for d in offsets]
								return retrieved_list







	def    _lowerCamelCase				(					self		:int						)		-> Dict:
								__UpperCamelCase	:   str			   =					self.get_tokenizer(word_delimiter_token="|"						)
								tokenizer.add_tokens("|"						)

								# fmt: off
								# ksssɾɾ|ɾɾ<pad>ɾɾ|<pad>ɾlll|ɭʲ -> k s ɾ ɾ | ɾ l | ɭʲ"
								__UpperCamelCase	:   Any			   =					[1_1, 5, 5, 5, 1_5, 1_5, tokenizer.pad_token_id, 1_5, 1_5, tokenizer.word_delimiter_token_id, tokenizer.pad_token_id, 1_5, 8, 8, 8, tokenizer.word_delimiter_token_id, 9_8]
								# fmt: on

								__UpperCamelCase	:   Tuple			   =					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, 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    _lowerCamelCase				(					self		:Any						)		-> Tuple:
								__UpperCamelCase	:   Optional[int]			   =					self.get_tokenizer(word_delimiter_token="|"						)

								def check_list_tuples_equal(a		:Dict     ,   a		:Optional[Any]						):
															self.assertTrue(isinstance(a     ,   a						)						)
															self.assertTrue(isinstance(outputs_list[0]     ,   a						)						)

															# transform list to ModelOutput
															__UpperCamelCase	:   Optional[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(a		:Optional[int]     ,   a		:List[Any]						):
																						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
								__UpperCamelCase	:   Tuple			   =					[
								    [1_1, 5, 1_5, tokenizer.pad_token_id, 1_5, 4, 8, 9_8, 3_2, 3_2, 3_2, 3_2, 4, 3_3, tokenizer.word_delimiter_token_id, 3_2, 3_2, 3_3, 3_4, 3_4],
								    [2_4, 2_2, 5, tokenizer.word_delimiter_token_id, tokenizer.word_delimiter_token_id, 2_4, 2_2, 2_2, 2_2, 4, 5, 7_7, tokenizer.pad_token_id, 2_2, 2_2, 4, 3_4, 3_4, 3_4, 3_4],
								]
								# fmt: on

								# We assume that `decode` works as expected. All we will check now is
								# the output type is correct and the output is identical to `decode`

								# char
								__UpperCamelCase	:   int			   =					tokenizer.batch_decode(a     ,   output_char_offsets=a						)
								__UpperCamelCase	:   List[Any]			   =					[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		:int						)		-> List[str]:
								pass







	@unittest.skip("Wav2Vec2PhonemeTokenizer always puts spaces between phonemes"						)
	def    _lowerCamelCase				(					self		:Dict						)		-> List[str]:
								pass







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







	@unittest.skip("Wav2Vec2PhonemeModel has no max model length => no testing"						)
	def    _lowerCamelCase				(					self		:Dict						)		-> Optional[Any]:
								pass







	def    _lowerCamelCase				(					self		:Optional[Any]						)		-> Dict:
								__UpperCamelCase	:   Dict			   =					self.get_tokenizers(do_lower_case=a						)
								for tokenizer in tokenizers:
															with self.subTest(f'{tokenizer.__class__.__name__}'						):
																						__UpperCamelCase	:   Optional[int]			   =					tokenizer.vocab_size
																						__UpperCamelCase	:   Any			   =					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)

																						__UpperCamelCase	:   Dict			   =					["aaaaa bbbbbb", "cccccccccdddddddd"]
																						__UpperCamelCase	:   int			   =					tokenizer.add_tokens(a						)
																						__UpperCamelCase	:   Any			   =					tokenizer.vocab_size
																						__UpperCamelCase	:   List[Any]			   =					len(a						)

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

																						__UpperCamelCase	:   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						)

																						__UpperCamelCase	:   List[str]			   =					{"eos_token": ">>>>|||<||<<|<<", "pad_token": "<<<<<|||>|>>>>|>"}
																						__UpperCamelCase	:   List[Any]			   =					tokenizer.add_special_tokens(a						)
																						__UpperCamelCase	:   Union[str, Any]			   =					tokenizer.vocab_size
																						__UpperCamelCase	:   Tuple			   =					len(a						)

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

																						__UpperCamelCase	:   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		:Union[str, Any]						)		-> Optional[int]:
								pass







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







	def    _lowerCamelCase				(					self		:Dict						)		-> Union[str, Any]:
								# The default common tokenizer tests assumes that the output of `convert_tokens_to_string` is a string which
								# is not the case for Wav2Vec2PhonemeCTCTokenizer.
								__UpperCamelCase	:   Optional[Any]			   =					self.get_tokenizers(fast=a     ,   do_lower_case=a						)
								for tokenizer in tokenizers:
															with self.subTest(f'{tokenizer.__class__.__name__}'						):
																						__UpperCamelCase	:   Union[str, Any]			   =					["ð", "ɪ", "s", "ɪ", "z", "ɐ", "t", "ɛ", "k", "s", "t"]
																						__UpperCamelCase	:   List[str]			   =					tokenizer.convert_tokens_to_string(a						)

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

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


lowercase  :					List[Any]													=       logging.get_logger(__name__)

lowercase  :					Any													=       {
    'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}




class  lowerCamelCase__							(				__lowercase):




	'''simple docstring'''




	_A								=     'pegasus'
	_A								=     ['past_key_values']
	_A								=     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}







	def __init__(					self		:Dict     ,   a		:Dict=5_0_2_6_5     ,   a		:Dict=1_0_2_4     ,   a		:Union[str, Any]=1_2     ,   a		:Any=4_0_9_6     ,   a		:str=1_6     ,   a		:str=1_2     ,   a		:Optional[Any]=4_0_9_6     ,   a		:int=1_6     ,   a		:Optional[int]=0.0     ,   a		:Optional[int]=0.0     ,   a		:List[Any]=True     ,   a		:Union[str, Any]=True     ,   a		:int="gelu"     ,   a		:Dict=1_0_2_4     ,   a		:List[Any]=0.1     ,   a		:List[str]=0.0     ,   a		:List[Any]=0.0     ,   a		:str=0.02     ,   a		:int=0     ,   a		:Any=False     ,   a		:Dict=0     ,   a		:int=1     ,   a		:Optional[Any]=1     ,   **a		:Optional[int]     ,   )		-> str:
								__UpperCamelCase	:   List[Any]			   =					vocab_size
								__UpperCamelCase	:   Union[str, Any]			   =					max_position_embeddings
								__UpperCamelCase	:   str			   =					d_model
								__UpperCamelCase	:   Dict			   =					encoder_ffn_dim
								__UpperCamelCase	:   int			   =					encoder_layers
								__UpperCamelCase	:   int			   =					encoder_attention_heads
								__UpperCamelCase	:   List[Any]			   =					decoder_ffn_dim
								__UpperCamelCase	:   List[Any]			   =					decoder_layers
								__UpperCamelCase	:   List[str]			   =					decoder_attention_heads
								__UpperCamelCase	:   str			   =					dropout
								__UpperCamelCase	:   Union[str, Any]			   =					attention_dropout
								__UpperCamelCase	:   List[str]			   =					activation_dropout
								__UpperCamelCase	:   Optional[Any]			   =					activation_function
								__UpperCamelCase	:   Tuple			   =					init_std
								__UpperCamelCase	:   Optional[int]			   =					encoder_layerdrop
								__UpperCamelCase	:   Union[str, Any]			   =					decoder_layerdrop
								__UpperCamelCase	:   Optional[Any]			   =					use_cache
								__UpperCamelCase	:   Union[str, Any]			   =					encoder_layers
								__UpperCamelCase	:   int			   =					scale_embedding  # scale factor will be sqrt(d_model) if True
								super().__init__(
								    pad_token_id=a     ,   eos_token_id=a     ,   is_encoder_decoder=a     ,   decoder_start_token_id=a     ,   forced_eos_token_id=a     ,   **a     ,   )







	@property
	def    _lowerCamelCase				(					self		:Dict						)		-> int:
								return self.encoder_attention_heads







	@property
	def    _lowerCamelCase				(					self		:Optional[Any]						)		-> int:
								return self.d_model