


"""simple docstring"""


import json
import os
import unittest
from typing import Tuple

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

from ...test_tokenization_common import TokenizerTesterMixin
@require_phonemizer
class   _UpperCamelCase  (   lowerCAmelCase__       ,unittest.TestCase		):
							'''simple docstring'''







							__UpperCAmelCase						:    List[str]				      =WavaVecaPhonemeCTCTokenizer
							__UpperCAmelCase						:    Union[str, Any]				      =False

							def 			snake_case				(     self	):
										super().setUp()

										__lowerCAmelCase				    =			(
										    "<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(" "	)
										__lowerCAmelCase				    =			dict(zip(__a    ,   range(len(__a	)	)	)	)

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

										__lowerCAmelCase				    =			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 			snake_case				(     self    ,   __a    ,   __a=False    ,   __a=20    ,   __a=5	):
										__lowerCAmelCase				    =			[(i, tokenizer.decode([i]    ,   clean_up_tokenization_spaces=__a	)) for i in range(len(__a	)	)]
										__lowerCAmelCase				    =			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:
													__lowerCAmelCase				    =			toks[:max_length]
										if min_length is not None and len(__a	) < min_length and len(__a	) > 0:
													while len(__a	) < min_length:
																__lowerCAmelCase				    =			toks + toks
        # toks_str = [t[1] for t in toks]
										__lowerCAmelCase				    =			[t[0] for t in toks]

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

							def 			snake_case				(     self    ,   **__a	):
										kwargs.update(self.special_tokens_map	)
										return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname    ,   **__a	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"	)

										# check adding a single token
										tokenizer.add_tokens("xxx"	)
										__lowerCAmelCase				    =			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"]	)
										__lowerCAmelCase				    =			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

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

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"	)

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

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"	)

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

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

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

										self.assertEqual(__a    ,   __a	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"	)

										__lowerCAmelCase				    =			[
										    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
										    [24, 22, 5, 24, 22, 5, 77],
										]
										__lowerCAmelCase				    =			tokenizer.decode(sample_ids[0]	)
										__lowerCAmelCase				    =			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 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer_class.from_pretrained(
										    "facebook/wav2vec2-lv-60-espeak-cv-ft"    ,   word_delimiter_token="|"	)
										tokenizer.add_tokens("|"	)

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

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

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

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

										# fmt: off
										__lowerCAmelCase				    =			[
										    [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
										__lowerCAmelCase				    =			tokenizer.decode(sample_ids[0]	)
										__lowerCAmelCase				    =			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
										__lowerCAmelCase				    =			tokenizer.decode(sample_ids[0]    ,   filter_word_delimiter_token=__a	)
										__lowerCAmelCase				    =			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 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer_class.from_pretrained(
										    "facebook/wav2vec2-lv-60-espeak-cv-ft"    ,   word_delimiter_token="|"	)
										tokenizer.add_tokens("|"	)

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

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

										self.assertEqual(__a    ,   __a	)

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

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

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

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

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

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

										self.assertNotEqual(__a    ,   __a	)

										__lowerCAmelCase				    =			tokenizer.decode(__a	)
										__lowerCAmelCase				    =			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 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft"	)
										__lowerCAmelCase				    =			"Hello how Are you"
										__lowerCAmelCase				    =			"hello how are you"

										__lowerCAmelCase				    =			tokenizer(__a	).input_ids
										__lowerCAmelCase				    =			tokenizer(__a	).input_ids

										self.assertEqual(__a    ,   __a	)

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

										# fmt: off
										__lowerCAmelCase				    =			[
										    [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

										__lowerCAmelCase				    =			tokenizer.batch_decode(__a	)
										self.assertEqual(__a    ,   ["k s ɾ ɾ l ɭʲ!?!? $$$", "j ð s j ð s oːɹ $$$"]	)

							@staticmethod
							def 			snake_case				(     __a    ,   __a	):
										__lowerCAmelCase				    =			[d[key] for d in offsets]
										return retrieved_list

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			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"
										__lowerCAmelCase				    =			[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

										__lowerCAmelCase				    =			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 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_tokenizer(word_delimiter_token="|"	)

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

													# transform list to ModelOutput
													__lowerCAmelCase				    =			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    ,   __a	):
																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
										__lowerCAmelCase				    =			[
										    [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
										__lowerCAmelCase				    =			tokenizer.batch_decode(__a    ,   output_char_offsets=__a	)
										__lowerCAmelCase				    =			[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 			snake_case				(     self	):
										pass

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

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

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

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_tokenizers(do_lower_case=__a	)
										for tokenizer in tokenizers:
													with self.subTest(f"{tokenizer.__class__.__name__}"	):
																__lowerCAmelCase				    =			tokenizer.vocab_size
																__lowerCAmelCase				    =			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)

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

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

																__lowerCAmelCase				    =			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	)

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

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

																__lowerCAmelCase				    =			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 			snake_case				(     self	):
										pass

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



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

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








"""simple docstring"""


import argparse

import pytorch_lightning as pl
import torch
from torch import nn

from transformers import LongformerForQuestionAnswering, LongformerModel
class   _UpperCamelCase  (   pl.LightningModule		):
							'''simple docstring'''







							def __init__(     self    ,   __a	):
										super().__init__()
										__lowerCAmelCase				    =			model
										__lowerCAmelCase				    =			2
										__lowerCAmelCase				    =			nn.Linear(self.model.config.hidden_size    ,   self.num_labels	)



							def 			snake_case				(     self	):
										pass


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			LongformerModel.from_pretrained(_UpperCamelCase      )
			__lowerCAmelCase				    =			LightningModel(_UpperCamelCase      )

			__lowerCAmelCase				    =			torch.load(_UpperCamelCase    , map_location=torch.device("cpu"      )      )
			lightning_model.load_state_dict(ckpt["state_dict"]      )

			# init longformer question answering model
			__lowerCAmelCase				    =			LongformerForQuestionAnswering.from_pretrained(_UpperCamelCase      )

			# transfer weights
			longformer_for_qa.longformer.load_state_dict(lightning_model.model.state_dict()      )
			longformer_for_qa.qa_outputs.load_state_dict(lightning_model.qa_outputs.state_dict()      )
			longformer_for_qa.eval()

			# save model
			longformer_for_qa.save_pretrained(_UpperCamelCase      )

			print(f"Conversion successful. Model saved under {pytorch_dump_folder_path}"      )


if __name__ == "__main__":
	A     :   Tuple			    =			argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    "--longformer_model",
	    default=None,
	    type=str,
	    required=True,
	    help="model identifier of longformer. Should be either `longformer-base-4096` or `longformer-large-4096`.",
	)
	parser.add_argument(
	    "--longformer_question_answering_ckpt_path",
	    default=None,
	    type=str,
	    required=True,
	    help="Path the official PyTorch Lightning Checkpoint.",
	)
	parser.add_argument(
	    "--pytorch_dump_folder_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
	)
	A     :   Optional[int]			    =			parser.parse_args()
	convert_longformer_qa_checkpoint_to_pytorch(
	    args.longformer_model, args.longformer_question_answering_ckpt_path, args.pytorch_dump_folder_path
	)




