Upload test_tokenization_wav2vec2_phoneme.py

test_tokenization_wav2vec2_phoneme.py

@@ -0,0 +1,440 @@
+
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Tests for the Wav2Vec2Phoneme tokenizer."""
+import json
+import os
+import unittest
+from typing import Tuple
+
+from transformers import Wav2Vec2PhonemeCTCTokenizer
+from transformers.models.wav2vec2.tokenization_wav2vec2 import VOCAB_FILES_NAMES
+from transformers.models.wav2vec2_phoneme.tokenization_wav2vec2_phoneme import Wav2Vec2PhonemeCTCTokenizerOutput
+from transformers.testing_utils import require_phonemizer
+
+from test_tokenization_common import TokenizerTesterMixin
+
+
+@require_phonemizer
+class Wav2Vec2PhonemeCTCTokenizerTest(TokenizerTesterMixin, unittest.TestCase):
+    from_pretrained_id = "facebook/wav2vec2-lv-60-espeak-cv-ft"
+    tokenizer_class = Wav2Vec2PhonemeCTCTokenizer
+    test_rust_tokenizer = False
+
+    def setUp(self):
+        super().setUp()
+
+        vocab = (
+            "<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(" ")
+        vocab_tokens = dict(zip(vocab, range(len(vocab))))
+
+        self.special_tokens_map = {"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}
+
+        self.vocab_file = 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(vocab_tokens) + "\n")
+
+    # overwrite since phonemes require specific creation
+    def get_clean_sequence(self, tokenizer, with_prefix_space=False, max_length=20, min_length=5) -> Tuple[str, list]:
+        toks = [(i, tokenizer.decode([i], clean_up_tokenization_spaces=False)) for i in range(len(tokenizer))]
+        toks = list(filter(lambda t: [t[0]] == tokenizer.encode(t[1], do_phonemize=False), toks))
+        if max_length is not None and len(toks) > max_length:
+            toks = toks[:max_length]
+        if min_length is not None and len(toks) < min_length and len(toks) > 0:
+            while len(toks) < min_length:
+                toks = toks + toks
+        # toks_str = [t[1] for t in toks]
+        toks_ids = [t[0] for t in toks]
+
+        # Ensure consistency
+        output_txt = tokenizer.decode(toks_ids, clean_up_tokenization_spaces=False)
+        if " " not in output_txt and len(toks_ids) > 1:
+            output_txt = (
+                tokenizer.decode([toks_ids[0]], clean_up_tokenization_spaces=False)
+                + " "
+                + tokenizer.decode(toks_ids[1:], clean_up_tokenization_spaces=False)
+            )
+        if with_prefix_space:
+            output_txt = " " + output_txt
+        output_ids = tokenizer.encode(output_txt, add_special_tokens=False)
+        return output_txt, output_ids
+
+    def get_tokenizer(self, **kwargs):
+        kwargs.update(self.special_tokens_map)
+        return Wav2Vec2PhonemeCTCTokenizer.from_pretrained(self.tmpdirname, **kwargs)
+
+    def test_tokenizer_add_new_tokens(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+
+        # check adding a single token
+        tokenizer.add_tokens("xxx")
+        token_ids = tokenizer("m xxx ɪ", do_phonemize=False).input_ids
+        self.assertEqual(token_ids, [13, 392, 17])  # xxx should be last token
+
+        tokenizer.add_tokens(["aaa", "bbb", "ccc"])
+        token_ids = tokenizer("m aaa ɪ ccc", do_phonemize=False).input_ids
+        self.assertEqual(token_ids, [13, 393, 17, 395])  # aaa and ccc should be after xxx and 2 after aaa
+
+        token_ids = tokenizer("maɪ c", do_phonemize=False).input_ids
+        self.assertEqual(token_ids, [3, 200])  # mai should be <unk> (=3)
+
+    def test_phonemize(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+        self.assertEqual(phonemes, "h ə l oʊ h aʊ ɑːɹ j uː")
+
+    def test_encode(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+        self.assertEqual(tokenizer(input_text).input_ids, tokenizer(phonemes, do_phonemize=False).input_ids)
+
+    def test_encode_decode(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+
+        phonemes_enc_dec = tokenizer.decode(tokenizer(input_text).input_ids)
+
+        self.assertEqual(phonemes, phonemes_enc_dec)
+
+    def test_decode(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+
+        sample_ids = [
+            [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
+            [24, 22, 5, 24, 22, 5, 77],
+        ]
+        tokens = tokenizer.decode(sample_ids[0])
+        batch_tokens = tokenizer.batch_decode(sample_ids)
+        self.assertEqual(tokens, batch_tokens[0])
+        self.assertEqual(batch_tokens, ["k s ɾ ɾ l ɭʲ", "j ð s j ð s oːɹ"])
+
+    def test_phonemize_with_word_del(self):
+        tokenizer = self.tokenizer_class.from_pretrained(
+            "facebook/wav2vec2-lv-60-espeak-cv-ft", word_delimiter_token="|"
+        )
+        tokenizer.add_tokens("|")
+
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+        self.assertEqual(phonemes, "h ə l oʊ | h aʊ | ɑːɹ | j uː |")
+
+    def test_encode_with_del(self):
+        tokenizer = self.tokenizer_class.from_pretrained(
+            "facebook/wav2vec2-lv-60-espeak-cv-ft", word_delimiter_token="|"
+        )
+        tokenizer.add_tokens("|")
+
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+        self.assertEqual(tokenizer(input_text).input_ids, tokenizer(phonemes, do_phonemize=False).input_ids)input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+        self.assertEqual(tokenizer(input_text).input_ids, tokenizer(phonemes, do_phonemize=False).input_ids)
+
+    def test_encode_decode(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+
+        phonemes_enc_dec = tokenizer.decode(tokenizer(input_text).input_ids)
+
+        self.assertEqual(phonemes, phonemes_enc_dec)
+
+    def test_decode(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+
+        sample_ids = [
+            [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
+            [24, 22, 5, 24, 22, 5, 77],
+        ]
+        tokens = tokenizer.decode(sample_ids[0])
+        batch_tokens = tokenizer.batch_decode(sample_ids)
+        self.assertEqual(tokens, batch_tokens[0])
+        self.assertEqual(batch_tokens, ["k s ɾ ɾ l ɭʲ", "j ð s j ð s oːɹ"])
+
+    def test_phonemize_with_word_del(self):
+        tokenizer = self.tokenizer_class.from_pretrained(
+            "facebook/wav2vec2-lv-60-espeak-cv-ft", word_delimiter_token="|"
+        )
+        tokenizer.add_tokens("|")
+
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+        self.assertEqual(phonemes, "h ə l oʊ | h aʊ | ɑːɹ | j uː |")
+
+    def test_encode_with_del(self):
+        tokenizer = self.tokenizer_class.from_pretrained(
+            "facebook/wav2vec2-lv-60-espeak-cv-ft", word_delimiter_token="|"
+        )
+        tokenizer.add_tokens("|")
+
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+        self.assertEqual(tokenizer(input_text).input_ids, tokenizer(phonemes, do_phonemize=False).input_ids)
+
+    def test_decode_with_del(self):
+        tokenizer = self.tokenizer_class.from_pretrained(
+            "facebook/wav2vec2-lv-60-espeak-cv-ft", word_delimiter_token="|"
+        )
+        tokenizer.add_tokens("|")
+
+        # fmt: off
+        sample_ids = [
+            [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
+        tokens = tokenizer.decode(sample_ids[0])
+        batch_tokens = tokenizer.batch_decode(sample_ids)
+        self.assertEqual(tokens, batch_tokens[0])
+        self.assertEqual(batch_tokens, ["k s ɾ ɾ l ɭʲ", "j ð s j ð s oːɹ"])
+
+        # decode with no word_del_token filter
+        tokens = tokenizer.decode(sample_ids[0], filter_word_delimiter_token=False)
+        batch_tokens = tokenizer.batch_decode(sample_ids, filter_word_delimiter_token=False)
+        self.assertEqual(tokens, batch_tokens[0])
+        self.assertEqual(batch_tokens, ["k s ɾ | ɾ l | ɭʲ", "| j ð | s j ð s oːɹ"])
+
+    def test_encode_decode_with_del(self):
+        tokenizer = self.tokenizer_class.from_pretrained(
+            "facebook/wav2vec2-lv-60-espeak-cv-ft", word_delimiter_token="|"
+        )
+        tokenizer.add_tokens("|")
+
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+
+        phonemes_enc_dec = tokenizer.decode(tokenizer(input_text).input_ids, filter_word_delimiter_token=False)
+
+        self.assertEqual(phonemes, phonemes_enc_dec)
+
+    def test_encode_decode_with_del_filter(self):
+        tokenizer = self.tokenizer_class.from_pretrained(
+            "facebook/wav2vec2-lv-60-espeak-cv-ft", word_delimiter_token="|"
+        )
+        tokenizer.add_tokens("|")
+
+        input_text = "Hello how are you"
+        phonemes = tokenizer.phonemize(input_text, phonemizer_lang="en-us")
+
+        phonemes_enc_dec = tokenizer.decode(tokenizer(input_text).input_ids, filter_word_delimiter_token=True)
+
+        self.assertEqual(" ".join([p.strip() for p in phonemes.split(" |")]).strip(), phonemes_enc_dec)
+
+    def test_change_phonemizer_lang(self):
+        tokenizer = self.tokenizer_class.from_pretrained(
+            "facebook/wav2vec2-lv-60-espeak-cv-ft", word_delimiter_token=None
+        )
+        input_text = "Hello how are you"
+
+        input_ids_en = tokenizer(input_text, phonemizer_lang="en-us").input_ids
+        input_ids_fr = tokenizer(input_text, phonemizer_lang="fr-fr").input_ids
+
+        self.assertNotEqual(input_ids_en, input_ids_fr)
+
+        text_en = tokenizer.decode(input_ids_en)
+        text_fr = tokenizer.decode(input_ids_fr)
+
+        self.assertEqual(text_en, "h ə l oʊ h aʊ ɑːɹ j uː")
+        self.assertEqual(text_fr, "ɛ l o h aʊ a ʁ j u")
+
+    def test_case_insensitive(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+        input_text_up = "Hello how Are you"
+        input_text_low = "hello how are you"
+
+        input_ids_up = tokenizer(input_text_up).input_ids
+        input_ids_low = tokenizer(input_text_low).input_ids
+
+        self.assertEqual(input_ids_up, input_ids_low)
+
+    def test_tokenizer_decode_added_tokens(self):
+        tokenizer = self.tokenizer_class.from_pretrained("facebook/wav2vec2-lv-60-espeak-cv-ft")
+        tokenizer.add_tokens(["!", "?"])
+        tokenizer.add_special_tokens({"cls_token": "$$$"})
+
+        # fmt: off
+        sample_ids = [
+            [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98, 392, 392, 393, 392, 392, 393, 394, 394],
+            [24, 22, 5, 24, 22, 5, 77, tokenizer.pad_token_id, 394, 394],
+        ]
+        # fmt: on
+
+        batch_tokens = tokenizer.batch_decode(sample_ids)
+        self.assertEqual(batch_tokens, ["k s ɾ ɾ l ɭʲ!?!? $$$", "j ð s j ð s oːɹ $$$"])
+
+    @staticmethod
+    def get_from_offsets(offsets, key):
+        retrieved_list = [d[key] for d in offsets]
+        return retrieved_list
+
+    def test_offsets(self):
+        tokenizer = 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"
+        sample_ids = [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
+
+        outputs = tokenizer.decode(sample_ids, output_char_offsets=True, filter_word_delimiter_token=False)
+        # 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(outputs, Wav2Vec2PhonemeCTCTokenizerOutput))
+
+        # 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 test_offsets_batch(self):
+        tokenizer = self.get_tokenizer(word_delimiter_token="|")
+
+        def check_list_tuples_equal(outputs_batch, outputs_list):
+            self.assertTrue(isinstance(outputs_batch, Wav2Vec2PhonemeCTCTokenizerOutput))
+            self.assertTrue(isinstance(outputs_list[0], Wav2Vec2PhonemeCTCTokenizerOutput))
+
+            # transform list to ModelOutput
+            outputs_batch_2 = Wav2Vec2PhonemeCTCTokenizerOutput(
+                {k: [d[k] for d in outputs_list] for k in outputs_list[0]}
+            )
+
+            self.assertListEqual(outputs_batch["text"], outputs_batch_2["text"])
+
+            def recursive_check(list_or_dict_1, list_or_dict_2):
+                if isinstance(list_or_dict_1, list):
+                    [recursive_check(l1, l2) for l1, l2 in zip(list_or_dict_1, list_or_dict_2)]
+                self.assertEqual(list_or_dict_1, list_or_dict_2)
+
+            if "char_offsets" in outputs_batch:
+                recursive_check(outputs_batch["char_offsets"], outputs_batch_2["char_offsets"])
+
+        # fmt: off
+        sample_ids = [
+            [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
+        outputs_char_batch = tokenizer.batch_decode(sample_ids, output_char_offsets=True)
+        outputs_char = [tokenizer.decode(ids, output_char_offsets=True) for ids in sample_ids]
+        check_list_tuples_equal(outputs_char_batch, outputs_char)
+
+    @unittest.skip("Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes")
+    def test_added_tokens_do_lower_case(self):
+        pass
+
+    @unittest.skip("Wav2Vec2PhonemeTokenizer always puts spaces between phonemes")
+    def test_encode_decode_with_spaces(self):
+        pass
+
+    @unittest.skip("encodes to text to ids, but decodes ids to phonemes -> not possible to have internal consistency")
+    def test_internal_consistency(self):
+        pass
+
+    @unittest.skip("Wav2Vec2PhonemeModel has no max model length => no testing")
+    def test_add_tokens_tokenizer(self):
+        tokenizers = self.get_tokenizers(do_lower_case=False)
+        for tokenizer in tokenizers:
+            with self.subTest(f"{tokenizer.__class__.__name__}"):
+                vocab_size = tokenizer.vocab_size
+                all_size = len(tokenizer)
+
+                self.assertNotEqual(vocab_size, 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)
+
+                new_toks = ["aaaaa bbbbbb", "cccccccccdddddddd"]
+                added_toks = tokenizer.add_tokens(new_toks)
+                vocab_size_2 = tokenizer.vocab_size
+                all_size_2 = len(tokenizer)
+
+                self.assertNotEqual(vocab_size_2, 0)
+                self.assertEqual(vocab_size, vocab_size_2)
+                self.assertEqual(added_toks, len(new_toks))
+                self.assertEqual(all_size_2, all_size + len(new_toks))
+
+                tokens = tokenizer.encode("aaaaa bbbbbb low cccccccccdddddddd l", add_special_tokens=False)
+
+                self.assertGreaterEqual(len(tokens), 4)
+                self.assertGreater(tokens[0], tokenizer.vocab_size - 1)
+                self.assertGreater(tokens[-3], tokenizer.vocab_size - 1)
+
+                new_toks_2 = {"eos_token": ">>>>|||<||<<|<<", "pad_token": "<<<<<|||>|>>>>|>"}
+                added_toks_2 = tokenizer.add_special_tokens(new_toks_2)
+                vocab_size_3 = tokenizer.vocab_size
+                all_size_3 = len(tokenizer)
+
+                self.assertNotEqual(vocab_size_3, 0)
+                self.assertEqual(vocab_size, vocab_size_3)
+                self.assertEqual(added_toks_2, len(new_toks_2))
+                self.assertEqual(all_size_3, all_size_2 + len(new_toks_2))
+
+                tokens = tokenizer.encode(
+                    ">>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l", add_special_tokens=False
+                )
+
+                self.assertGreaterEqual(len(tokens), 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 test_tf_encode_plus_sent_to_model(self):
+        pass
+
+    @unittest.skip("The tokenizer shouldn't be used to encode input IDs (except for labels), only to decode.")
+    def test_torch_encode_plus_sent_to_model(self):
+        pass
+
+    def test_convert_tokens_to_string_format(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.
+        tokenizers = self.get_tokenizers(fast=True, do_lower_case=True)
+        for tokenizer in tokenizers:
+            with self.subTest(f"{tokenizer.__class__.__name__}"):
+                tokens = ["ð", "ɪ", "s", "ɪ", "z", "ɐ", "t", "ɛ", "k", "s", "t"]
+                output = tokenizer.convert_tokens_to_string(tokens)
+
+                self.assertIsInstance(output["text"], str)