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| import torch
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| import torchvision
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|
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| from mmaction.models import OmniResNet
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| from mmaction.testing import generate_backbone_demo_inputs
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|
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| def test_x3d_backbone():
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| """Test x3d backbone."""
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| _ = OmniResNet()
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|
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| resnet50 = torchvision.models.resnet50()
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| params = resnet50.state_dict()
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| torch.save(params, './r50.pth')
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| model = OmniResNet(pretrain_2d='./r50.pth')
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|
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| input_shape = (2, 3, 8, 64, 64)
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| videos = generate_backbone_demo_inputs(input_shape)
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| feat = model(videos)
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| assert feat.shape == torch.Size([2, 2048, 8, 2, 2])
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|
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| input_shape = (2, 3, 64, 64)
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| images = generate_backbone_demo_inputs(input_shape)
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| feat = model(images)
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| assert feat.shape == torch.Size([2, 2048, 2, 2])
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|
|
