wehub-resource-sync
69 lines
3.2 KiB
Python
69 lines
3.2 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from paddlenlp.transformers import AutoImageProcessor, CLIPImageProcessor
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from paddlenlp.utils.log import logger
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from tests.testing_utils import slow
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@unittest.skip("skipping due to connection error!")
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class ImageProcessorLoadTester(unittest.TestCase):
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@slow
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def test_clip_load(self):
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logger.info("Download model from PaddleNLP BOS")
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clip_processor = CLIPImageProcessor.from_pretrained("openai/clip-vit-base-patch32", from_hf_hub=False)
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clip_processor = AutoImageProcessor.from_pretrained("openai/clip-vit-base-patch32", from_hf_hub=False)
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logger.info("Download model from local")
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clip_processor.save_pretrained("./paddlenlp-test-model/clip-vit-base-patch32")
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clip_processor = CLIPImageProcessor.from_pretrained("./paddlenlp-test-model/clip-vit-base-patch32")
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clip_processor = AutoImageProcessor.from_pretrained("./paddlenlp-test-model/clip-vit-base-patch32")
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logger.info("Download model from PaddleNLP BOS with subfolder")
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clip_processor = CLIPImageProcessor.from_pretrained(
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"./paddlenlp-test-model/", subfolder="clip-vit-base-patch32"
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)
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clip_processor = AutoImageProcessor.from_pretrained(
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"./paddlenlp-test-model/", subfolder="clip-vit-base-patch32"
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)
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logger.info("Download model from PaddleNLP BOS with subfolder")
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clip_processor = CLIPImageProcessor.from_pretrained(
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"baicai/paddlenlp-test-model", subfolder="clip-vit-base-patch32", from_hf_hub=False
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)
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clip_processor = AutoImageProcessor.from_pretrained(
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"baicai/paddlenlp-test-model", subfolder="clip-vit-base-patch32", from_hf_hub=False
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)
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logger.info("Download model from aistudio")
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clip_processor = CLIPImageProcessor.from_pretrained("aistudio/clip-vit-base-patch32", from_aistudio=True)
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clip_processor = AutoImageProcessor.from_pretrained("aistudio/clip-vit-base-patch32", from_aistudio=True)
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logger.info("Download model from aistudio with subfolder")
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clip_processor = CLIPImageProcessor.from_pretrained(
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"aistudio/paddlenlp-test-model", subfolder="clip-vit-base-patch32", from_aistudio=True
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)
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clip_processor = AutoImageProcessor.from_pretrained(
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"aistudio/paddlenlp-test-model", subfolder="clip-vit-base-patch32", from_aistudio=True
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)
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class ImageProcessorSubfolderLoadTester(unittest.TestCase):
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def test_clip_subfolder_load(self):
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logger.info("Download model with subfolder")
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clip_processor = CLIPImageProcessor.from_pretrained( # noqa: F841
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"runwayml/stable-diffusion-v1-5", subfolder="feature_extractor"
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)
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