Add missing lang tokens in M2M100Tokenizer.get_vocab (#18416)

src/transformers/models/m2m_100/tokenization_m2m_100.py

@@ -280,7 +280,7 @@ class M2M100Tokenizer(PreTrainedTokenizer):
         return self.prefix_tokens + token_ids_0 + token_ids_1 + self.suffix_tokens
 
     def get_vocab(self) -> Dict:
-        vocab = self.encoder.copy()
+        vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)}
         vocab.update(self.added_tokens_encoder)
         return vocab
 

tests/models/m2m_100/test_tokenization_m2m_100.py

@@ -89,7 +89,7 @@ class M2M100TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
         self.assertEqual(vocab_keys[0], "</s>")
         self.assertEqual(vocab_keys[1], "<unk>")
         self.assertEqual(vocab_keys[-1], "<s>")
-        self.assertEqual(len(vocab_keys), 10)
+        self.assertEqual(len(vocab_keys), 110)
 
     def test_vocab_size(self):
         self.assertEqual(self.get_tokenizer().vocab_size, 117)
@@ -160,6 +160,9 @@ class M2M100TokenizerIntegrationTest(unittest.TestCase):
         self.assertEqual(self.tokenizer.get_lang_id("ro"), 128076)
         self.assertEqual(self.tokenizer.get_lang_id("mr"), 128063)
 
+    def test_get_vocab(self):
+        self.assertIn(self.tokenizer.get_lang_token("en"), self.tokenizer.get_vocab())
+
     def test_tokenizer_batch_encode_plus(self):
         self.tokenizer.src_lang = "en"
         ids = self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]