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enginex-mlu370-any2any/transformers/tests/models/ovis2/test_processor_ovis2.py
2025-10-09 16:47:16 +08:00

119 lines
5.2 KiB
Python

# 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' %}{{ '<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<image>\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"])