[Tokenizer] Support adding special tokens to Qwen tokenizer (#9344)

* update qwen tokenizer

* add test case

paddlenlp/transformers/qwen/tokenizer.py

@@ -125,14 +125,41 @@ def convert_tokens_to_ids(self, tokens: Union[bytes, str, List[Union[bytes, str]
                 ids.append(self.mergeable_ranks.get(token))
         return ids
 
+    def _update_tiktoken(self, tokens: List[str], special_tokens: bool = False) -> int:
+        if special_tokens:
+            added_tokens = []
+            for token in tokens:
+                if token in self.special_tokens:
+                    continue
+
+                token_id = len(self.mergeable_ranks) + len(self.special_tokens)
+                self.special_tokens[token] = token_id
+                self.decoder[token_id] = token
+
+                added_tokens.append(token)
+
+            import tiktoken
+
+            self.tokenizer = tiktoken.Encoding(
+                "Qwen",
+                pat_str=PAT_STR,
+                mergeable_ranks=self.mergeable_ranks,
+                special_tokens=self.special_tokens,
+            )
+
+            return len(added_tokens)
+        else:
+            raise ValueError("Adding regular tokens is not supported")
+
     def _add_tokens(self, new_tokens: Union[List[str], List[AddedToken]], special_tokens: bool = False) -> int:
         if not special_tokens and new_tokens:
             raise ValueError("Adding regular tokens is not supported")
+        new_tokens_str = []
         for token in new_tokens:
             surface_form = token.content if isinstance(token, AddedToken) else token
-            if surface_form not in SPECIAL_TOKENS:
-                raise ValueError("Adding unknown special tokens is not supported")
-        return 0
+            new_tokens_str.append(surface_form)
+
+        return self._update_tiktoken(new_tokens_str, special_tokens)
 
     def save_vocabulary(self, save_directory: str, **kwargs) -> Tuple[str]:
         """

paddlenlp/utils/import_utils.py

@@ -52,7 +52,6 @@ def _is_package_available(pkg_name: str, return_version: bool = False) -> Union[
             else:
                 # For packages other than "torch", don't attempt the fallback and set as not available
                 package_exists = False
-        logger.debug(f"Detected {pkg_name} version: {package_version}")
     if return_version:
         return package_exists, package_version
     else:
@@ -96,7 +95,6 @@ def _is_package_available(pkg_name: str, return_version: bool = False) -> Union[
             else:
                 # For packages other than "torch", don't attempt the fallback and set as not available
                 package_exists = False
-        logger.debug(f"Detected {pkg_name} version: {package_version}")
     if return_version:
         return package_exists, package_version
     else:

tests/transformers/qwen/test_tokenizer.py

@@ -0,0 +1,46 @@
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
+# Copyright 2024 The Qwen team, Alibaba Group and the HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import unittest
+
+from paddlenlp.transformers import QWenTokenizer
+
+
+class Qwen2TokenizationTest(unittest.TestCase):
+    from_pretrained_id = "qwen/qwen-7b"
+    tokenizer_class = QWenTokenizer
+    test_slow_tokenizer = True
+    space_between_special_tokens = False
+    from_pretrained_kwargs = None
+    test_seq2seq = False
+
+    def setUp(self):
+        super().setUp()
+
+    def get_tokenizer(self, **kwargs):
+        return QWenTokenizer.from_pretrained(self.from_pretrained_id, **kwargs)
+
+    def test_add_special_tokens(self):
+        tokenizer = self.get_tokenizer()
+        origin_tokens_len = len(tokenizer)
+
+        add_tokens_num = tokenizer.add_special_tokens({"additional_special_tokens": ["<img>"]})
+        assert add_tokens_num == 1
+        assert len(tokenizer) == origin_tokens_len + 1
+
+        add_tokens_num = tokenizer.add_special_tokens({"unk_token": "<unk>"})
+        assert add_tokens_num == 1
+        assert len(tokenizer) == origin_tokens_len + 2