# 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 AlignProcessor @require_vision class AlignProcessorTest(ProcessorTesterMixin, unittest.TestCase): processor_class = AlignProcessor @classmethod def _setup_tokenizer(cls): tokenizer_class = cls._get_component_class_from_processor("tokenizer") vocab_tokens = [ "[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "want", "##want", "##ed", "wa", "un", "runn", "##ing", ",", "low", "lowest", ] vocab_file = f"{cls.tmpdirname}/vocab.txt" with open(vocab_file, "w", encoding="utf-8") as f: f.write("\n".join(vocab_tokens)) tokenizer = tokenizer_class(vocab_file) return tokenizer @classmethod def _setup_image_processor(cls): image_processor_class = cls._get_component_class_from_processor("image_processor") image_processor = image_processor_class( do_resize=True, size=20, do_normalize=True, image_mean=[0.48145466, 0.4578275, 0.40821073], image_std=[0.26862954, 0.26130258, 0.27577711], ) return image_processor