fix tiktoken convert to pass AddedToken to Tokenizer (#36566)

* pass AddedToken to Tokenizer

* ruff

* handle dict for special tokens

* option: test tokenizer from tiktoken same as fast

* ruff

* ruff

src/transformers/convert_slow_tokenizer.py

@@ -1580,7 +1580,9 @@ class TikTokenConverter:
         self.vocab_file = vocab_file
         self.pattern = pattern
         self.add_prefix_space = add_prefix_space
-        self.additional_special_tokens = additional_special_tokens
+        self.additional_special_tokens = (
+            additional_special_tokens.keys() if type(additional_special_tokens) is dict else additional_special_tokens
+        )
 
     def extract_vocab_merges_from_model(self, tiktoken_url: str):
         try:
@@ -1629,7 +1631,10 @@ class TikTokenConverter:
             ]
         )
         tokenizer.decoder = decoders.ByteLevel()
-        tokenizer.add_special_tokens(self.additional_special_tokens)
+
+        tokenizer.add_special_tokens(
+            [AddedToken(token, normalized=False, special=True) for token in self.additional_special_tokens]
+        )
 
         tokenizer.post_processor = processors.ByteLevel(trim_offsets=False)
 

tests/models/gpt2/test_tokenization_gpt2.py

@@ -20,7 +20,7 @@ import unittest
 
 from transformers import AutoTokenizer, GPT2Tokenizer, GPT2TokenizerFast
 from transformers.models.gpt2.tokenization_gpt2 import VOCAB_FILES_NAMES
-from transformers.testing_utils import require_jinja, require_tokenizers
+from transformers.testing_utils import require_jinja, require_tiktoken, require_tokenizers
 
 from ...test_tokenization_common import TokenizerTesterMixin
 
@@ -299,6 +299,23 @@ class GPT2TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
         for tokenized_chat, expected_tokens in zip(tokenized_chats, expected_tokens):
             self.assertListEqual(tokenized_chat, expected_tokens)
 
+    @require_tiktoken
+    def test_tokenization_tiktoken(self):
+        from tiktoken import encoding_name_for_model
+
+        from transformers.integrations.tiktoken import convert_tiktoken_to_fast
+
+        encoding = encoding_name_for_model("gpt2")
+        convert_tiktoken_to_fast(encoding, self.tmpdirname)
+
+        tiktoken_fast_tokenizer = GPT2TokenizerFast.from_pretrained(self.tmpdirname)
+        rust_tokenizer = GPT2TokenizerFast.from_pretrained("openai-community/gpt2")
+        sequence = "lower newer"
+        self.assertEqual(
+            rust_tokenizer.decode(rust_tokenizer.encode(sequence)),
+            tiktoken_fast_tokenizer.decode(rust_tokenizer.encode(sequence)),
+        )
+
 
 @require_tokenizers
 class OPTTokenizationTest(unittest.TestCase):