Fix device issue in UperNetModelIntegrationTest (#21192)
fix device Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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@@ -272,7 +272,7 @@ def prepare_img():
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class UperNetModelIntegrationTest(unittest.TestCase):
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def test_inference_swin_backbone(self):
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processor = AutoImageProcessor.from_pretrained("openmmlab/upernet-swin-tiny")
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model = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-swin-tiny")
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model = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-swin-tiny").to(torch_device)
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image = prepare_img()
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inputs = processor(images=image, return_tensors="pt").to(torch_device)
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@@ -290,7 +290,7 @@ class UperNetModelIntegrationTest(unittest.TestCase):
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def test_inference_convnext_backbone(self):
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processor = AutoImageProcessor.from_pretrained("openmmlab/upernet-convnext-tiny")
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model = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-convnext-tiny")
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model = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-convnext-tiny").to(torch_device)
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image = prepare_img()
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inputs = processor(images=image, return_tensors="pt").to(torch_device)
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