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import pytest |
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import torch |
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def test_chamfer_disrance(): |
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from mmdet3d.models.losses import ChamferDistance, chamfer_distance |
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with pytest.raises(AssertionError): |
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ChamferDistance(mode='smoothl1') |
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ChamferDistance(mode='l2', reduction=None) |
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self = ChamferDistance( |
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mode='l2', reduction='sum', loss_src_weight=1.0, loss_dst_weight=1.0) |
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source = torch.tensor([[[-0.9888, 0.9683, -0.8494], |
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[-6.4536, 4.5146, |
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1.6861], [2.0482, 5.6936, -1.4701], |
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[-0.5173, 5.6472, 2.1748], |
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[-2.8010, 5.4423, -1.2158], |
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[2.4018, 2.4389, -0.2403], |
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[-2.8811, 3.8486, 1.4750], |
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[-0.2031, 3.8969, |
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-1.5245], [1.3827, 4.9295, 1.1537], |
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[-2.6961, 2.2621, -1.0976]], |
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[[0.3692, 1.8409, |
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-1.4983], [1.9995, 6.3602, 0.1798], |
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[-2.1317, 4.6011, |
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-0.7028], [2.4158, 3.1482, 0.3169], |
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[-0.5836, 3.6250, -1.2650], |
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[-1.9862, 1.6182, -1.4901], |
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[2.5992, 1.2847, -0.8471], |
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[-0.3467, 5.3681, -1.4755], |
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[-0.8576, 3.3400, -1.7399], |
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[2.7447, 4.6349, 0.1994]]]) |
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target = torch.tensor([[[-0.4758, 1.0094, -0.8645], |
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[-0.3130, 0.8564, -0.9061], |
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[-0.1560, 2.0394, -0.8936], |
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[-0.3685, 1.6467, -0.8271], |
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[-0.2740, 2.2212, -0.7980]], |
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[[1.4856, 2.5299, |
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-1.0047], [2.3262, 3.3065, -0.9475], |
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[2.4593, 2.5870, |
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-0.9423], [0.0000, 0.0000, 0.0000], |
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[0.0000, 0.0000, 0.0000]]]) |
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loss_source, loss_target, indices1, indices2 = self( |
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source, target, return_indices=True) |
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assert torch.allclose(loss_source, torch.tensor(219.5936)) |
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assert torch.allclose(loss_target, torch.tensor(22.3705)) |
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expected_inds1 = [[0, 4, 4, 4, 4, 2, 4, 4, 4, 3], |
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[0, 1, 0, 1, 0, 4, 2, 0, 0, 1]] |
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expected_inds2 = [[0, 4, 4, 4, 4, 2, 4, 4, 4, 3], |
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[0, 1, 0, 1, 0, 3, 2, 0, 0, 1]] |
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assert (torch.equal(indices1, indices1.new_tensor(expected_inds1)) |
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or torch.equal(indices1, indices1.new_tensor(expected_inds2))) |
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assert torch.equal(indices2, |
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indices2.new_tensor([[0, 0, 0, 0, 0], [0, 3, 6, 0, 0]])) |
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loss_source, loss_target, indices1, indices2 = chamfer_distance( |
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source, target, reduction='sum') |
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assert torch.allclose(loss_source, torch.tensor(219.5936)) |
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assert torch.allclose(loss_target, torch.tensor(22.3705)) |
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assert (torch.equal(indices1, indices1.new_tensor(expected_inds1)) |
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or torch.equal(indices1, indices1.new_tensor(expected_inds2))) |
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assert (indices2 == indices2.new_tensor([[0, 0, 0, 0, 0], [0, 3, 6, 0, |
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0]])).all() |
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