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import torch |
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from mmdet3d.registry import MODELS |
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def test_dla_net(): |
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cfg = dict( |
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type='DLANet', |
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depth=34, |
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in_channels=3, |
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norm_cfg=dict(type='GN', num_groups=32)) |
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img = torch.randn((4, 3, 32, 32)) |
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self = MODELS.build(cfg) |
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self.init_weights() |
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results = self(img) |
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assert len(results) == 6 |
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assert results[0].shape == torch.Size([4, 16, 32, 32]) |
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assert results[1].shape == torch.Size([4, 32, 16, 16]) |
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assert results[2].shape == torch.Size([4, 64, 8, 8]) |
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assert results[3].shape == torch.Size([4, 128, 4, 4]) |
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assert results[4].shape == torch.Size([4, 256, 2, 2]) |
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assert results[5].shape == torch.Size([4, 512, 1, 1]) |
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