| # Copyright 2023 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 | |
| from ...test_processing_common import ProcessorTesterMixin | |
| if is_vision_available(): | |
| from transformers import Blip2Processor | |
| class Blip2ProcessorTest(ProcessorTesterMixin, unittest.TestCase): | |
| processor_class = Blip2Processor | |
| def _setup_tokenizer(cls): | |
| tokenizer_class = cls._get_component_class_from_processor("tokenizer") | |
| return tokenizer_class.from_pretrained("hf-internal-testing/tiny-random-GPT2Model") | |
| def _setup_image_processor(cls): | |
| image_processor_class = cls._get_component_class_from_processor("image_processor") | |
| return image_processor_class.from_pretrained("hf-internal-testing/tiny-random-ViTModel") | |
| def prepare_processor_dict(): | |
| return {"num_query_tokens": 1} | |