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cba4e40bc1
明确受影响的模型(damo)： ONE-PEACE-4B ModuleNotFoundError: MyCustomPipeline: MyCustomModel: No module named 'one_peace'，缺少依赖。 cv_resnet50_face-reconstruction 不兼容tf2 nlp_automatic_post_editing_for_translation_en2de tf2.0兼容性问题，tf1.x需要 cv_resnet18_ocr-detection-word-level_damo tf2.x兼容性问题 cv_resnet18_ocr-detection-line-level_damo tf兼容性问题 cv_resnet101_detection_fewshot-defrcn 模型限制必须detection0.3+torch1.11.0" speech_dfsmn_ans_psm_48k_causal "librosa， numpy兼容性问题 cv_mdm_motion-generation "依赖numpy版本兼容性问题： File ""/opt/conda/lib/python3.8/site-packages/smplx/body_models.py"", cv_resnet50_ocr-detection-vlpt numpy兼容性问题 cv_clip-it_video-summarization_language-guided_en tf兼容性问题 Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/13744636 * numpy and pandas no version * modify compatible issue * fix numpy compatible issue * modify ci * fix lint issue * replace Image.ANTIALIAS to Image.Resampling.LANCZOS pillow compatible * skip uncompatible cases * fix numpy compatible issue, skip cases that can not compatbile numpy or tensorflow2.x * skip compatible cases * fix clip model issue * fix body 3d keypoints compatible issue
64 lines
2.5 KiB
Python
64 lines
2.5 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import subprocess
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import sys
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import unittest
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from modelscope.hub.snapshot_download import snapshot_download
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from modelscope.models import Model
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from modelscope.outputs import OutputKeys
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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from modelscope.utils.logger import get_logger
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from modelscope.utils.test_utils import test_level
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logger = get_logger()
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@unittest.skip('require detectron2-0.3 and torch 1.11.0')
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class ImageDefrcnFewShotTest(unittest.TestCase):
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def setUp(self) -> None:
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logger.info('start install detectron2-0.3')
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cmd = [
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sys.executable, '-m', 'pip', 'install', 'detectron2==0.3', '-f',
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'https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html'
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]
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subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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logger.info('install detectron2-0.3 finished')
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self.task = Tasks.image_fewshot_detection
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self.model_id = 'damo/cv_resnet101_detection_fewshot-defrcn'
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self.image = 'https://modelscope.oss-cn-beijing.aliyuncs.com/test/images/image_voc2007_000001.jpg'
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self.revision = 'v1.1.0'
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_with_model_from_modelhub(self):
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model = Model.from_pretrained(self.model_id, revision=self.revision)
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pipeline_defrcn = pipeline(
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task=self.task, model=model, model_revision=self.revision)
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print(pipeline_defrcn(input=self.image)[OutputKeys.LABELS])
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@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
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def test_run_with_model_name(self):
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pipeline_defrcn = pipeline(
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task=self.task, model=self.model_id, model_revision=self.revision)
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print(pipeline_defrcn(input=self.image)[OutputKeys.LABELS])
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run_with_default_model(self):
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pipeline_defrcn = pipeline(
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task=self.task, model_revision=self.revision)
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print(pipeline_defrcn(input=self.image)[OutputKeys.LABELS])
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run_by_direct_model_download(self):
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cache_path = snapshot_download(self.model_id, revision=self.revision)
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pipeline_defrcn = pipeline(
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self.task, model=cache_path, model_revision=self.revision)
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print(pipeline_defrcn(input=self.image)[OutputKeys.LABELS])
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if __name__ == '__main__':
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unittest.main()
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