Support arbitrary processor (#30875)

* Support arbitrary processor

* fix

* nit

* update

* nit

* nit

* fix and revert

* add a small test

* better check

* fixup

* bug so let's just use class for now

* oups

* .

src/transformers/models/llava/processing_llava.py

@@ -41,8 +41,8 @@ class LlavaProcessor(ProcessorMixin):
     """
 
     attributes = ["image_processor", "tokenizer"]
-    image_processor_class = "CLIPImageProcessor"
-    tokenizer_class = ("LlamaTokenizer", "LlamaTokenizerFast")
+    image_processor_class = "AutoImageProcessor"
+    tokenizer_class = "AutoTokenizer"
 
     def __init__(self, image_processor=None, tokenizer=None):
         super().__init__(image_processor, tokenizer)

tests/models/llava/test_processor_llava.py

@@ -0,0 +1,30 @@
+# Copyright 2021 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 transformers.testing_utils import require_vision
+from transformers.utils import is_vision_available
+
+
+if is_vision_available():
+    from transformers import AutoTokenizer, LlavaProcessor
+
+
+@require_vision
+class LlavaProcessorTest(unittest.TestCase):
+    def test_can_load_various_tokenizers(self):
+        for checkpoint in ["Intel/llava-gemma-2b", "llava-hf/llava-1.5-7b-hf"]:
+            processor = LlavaProcessor.from_pretrained(checkpoint)
+            tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+            self.assertEqual(processor.tokenizer.__class__, tokenizer.__class__)