# coding=utf-8 # Copyright 2025 The HuggingFace Inc. 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 json import shutil import tempfile import unittest from transformers.testing_utils import require_av, require_vision from transformers.utils import is_vision_available from ...test_processing_common import ProcessorTesterMixin if is_vision_available(): from transformers import ( AutoProcessor, Ovis2ImageProcessor, Ovis2Processor, Qwen2TokenizerFast, ) @require_vision class Ovis2ProcessorTest(ProcessorTesterMixin, unittest.TestCase): processor_class = Ovis2Processor def setUp(self): self.tmpdirname = tempfile.mkdtemp() image_processor = Ovis2ImageProcessor() tokenizer = Qwen2TokenizerFast.from_pretrained("thisisiron/Ovis2-1B-hf") processor_kwargs = self.prepare_processor_dict() processor = Ovis2Processor(image_processor=image_processor, tokenizer=tokenizer, **processor_kwargs) processor.save_pretrained(self.tmpdirname) def get_tokenizer(self, **kwargs): return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).tokenizer def get_image_processor(self, **kwargs): return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).image_processor def prepare_processor_dict(self): return { "chat_template": "<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n'}}{% if message['content'] is string %}{{ message['content'] }}{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' %}{{ '\n' }}{% elif content['type'] == 'text' %}{{ content['text'] }}{% endif %}{% endfor %}{% endif %}{{'<|im_end|>\n'}}{% endfor %}{% if add_generation_prompt %}{{'<|im_start|>assistant\n' }}{% endif %}", } # fmt: skip def test_processor_to_json_string(self): processor = self.get_processor() obj = json.loads(processor.to_json_string()) for key, value in self.prepare_processor_dict().items(): # chat_tempalate are tested as a separate test because they are saved in separate files if key != "chat_template": self.assertEqual(obj[key], value) self.assertEqual(getattr(processor, key, None), value) def test_chat_template_is_saved(self): processor_loaded = self.processor_class.from_pretrained(self.tmpdirname) processor_dict_loaded = json.loads(processor_loaded.to_json_string()) # chat templates aren't serialized to json in processors self.assertFalse("chat_template" in processor_dict_loaded) # they have to be saved as separate file and loaded back from that file # so we check if the same template is loaded processor_dict = self.prepare_processor_dict() self.assertTrue(processor_loaded.chat_template == processor_dict.get("chat_template", None)) def tearDown(self): shutil.rmtree(self.tmpdirname) def test_chat_template(self): processor = AutoProcessor.from_pretrained("thisisiron/Ovis2-1B-hf") expected_prompt = "<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\n\nWhat is shown in this image?<|im_end|>\n<|im_start|>assistant\n" messages = [ { "role": "user", "content": [ {"type": "image"}, {"type": "text", "text": "What is shown in this image?"}, ], }, ] formatted_prompt = processor.apply_chat_template(messages, add_generation_prompt=True) self.assertEqual(expected_prompt, formatted_prompt) @require_av def test_chat_template_dict(self): processor = AutoProcessor.from_pretrained("thisisiron/Ovis2-1B-hf") messages = [ { "role": "user", "content": [ {"type": "image"}, {"type": "text", "text": "What is shown in this image?"}, ], }, ] formatted_prompt_tokenized = processor.apply_chat_template(messages, add_generation_prompt=True, tokenize=True) expected_output = [[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 27, 1805, 397, 3838, 374, 6839, 304, 419, 2168, 30, 151645, 198, 151644, 77091, 198]] # fmt: skip self.assertListEqual(expected_output, formatted_prompt_tokenized) out_dict = processor.apply_chat_template(messages, add_generation_prompt=True, tokenize=True, return_dict=True) self.assertListEqual(list(out_dict.keys()), ["input_ids", "attention_mask"])