utils/box_ops3d.py [274:317]:
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        assert len(corners1.shape) == 4
        assert len(corners2.shape)== 4
        assert corners1.shape[2] == 8
        assert corners1.shape[3] == 3
        assert corners1.shape[0] == corners2.shape[0]
        assert corners1.shape[2] == corners2.shape[2]
        assert corners1.shape[3] == corners2.shape[3]

        B, K1 = corners1.shape[0], corners1.shape[1]
        _, K2 = corners2.shape[0], corners2.shape[1]

        # # box height. Y is negative, so max is torch.min
        ymax = torch.min(corners1[:, :, 0,1][:, :, None], corners2[:, :, 0,1][:, None, :])
        ymin = torch.max(corners1[:, :, 4,1][:, :, None], corners2[:, :, 4,1][:, None, :])
        height = (ymax - ymin).clamp(min=0)
        EPS = 1e-8
        
        idx = torch.arange(start=3, end=-1, step=-1, device=corners1.device)
        idx2 = torch.tensor([0,2], dtype=torch.int64, device=corners1.device)
        rect1 = corners1[:, :, idx, :]
        rect2 = corners2[:, :, idx, :]
        rect1 = rect1[:, :, :, idx2]
        rect2 = rect2[:, :, :, idx2]

        lt = torch.max(rect1[:, :, 1][:, :, None, :], rect2[:, :, 1][:, None, : ,:])
        rb = torch.min(rect1[:, :, 3][:, :, None, :], rect2[:, :, 3][:, None, : ,:])
        wh = (rb - lt).clamp(min=0)
        non_rot_inter_areas = wh[:, :, :, 0] * wh[:, :, :, 1]
        non_rot_inter_areas = non_rot_inter_areas.view(B, K1, K2)
        if nums_k2 is not None:
            for b in range(B):
                non_rot_inter_areas[b, :, nums_k2[b]:] = 0

        enclosing_vols = enclosing_box3d_vol(corners1, corners2)
        
        # vols of boxes
        vols1 = box3d_vol_tensor(corners1).clamp(min=EPS)
        vols2 = box3d_vol_tensor(corners2).clamp(min=EPS)
        
        sum_vols = vols1[:, :, None] + vols2[:, None, :]

        # filter malformed boxes
        good_boxes = (enclosing_vols > 2*EPS) * (sum_vols > 4*EPS)
        if rotated_boxes:
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utils/box_ops3d.py [359:403]:
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    assert len(corners1.shape) == 4
    assert len(corners2.shape)== 4
    assert corners1.shape[2] == 8
    assert corners1.shape[3] == 3
    assert corners1.shape[0] == corners2.shape[0]
    assert corners1.shape[2] == corners2.shape[2]
    assert corners1.shape[3] == corners2.shape[3]

    B, K1 = corners1.shape[0], corners1.shape[1]
    _, K2 = corners2.shape[0], corners2.shape[1]

    # # box height. Y is negative, so max is torch.min
    ymax = torch.min(corners1[:, :, 0,1][:, :, None], corners2[:, :, 0,1][:, None, :])
    ymin = torch.max(corners1[:, :, 4,1][:, :, None], corners2[:, :, 4,1][:, None, :])
    height = (ymax - ymin).clamp(min=0)
    EPS = 1e-8
    
    idx = torch.arange(start=3, end=-1, step=-1, device=corners1.device)
    idx2 = torch.tensor([0,2], dtype=torch.int64, device=corners1.device)
    rect1 = corners1[:, :, idx, :]
    rect2 = corners2[:, :, idx, :]
    rect1 = rect1[:, :, :, idx2]
    rect2 = rect2[:, :, :, idx2]

    lt = torch.max(rect1[:, :, 1][:, :, None, :], rect2[:, :, 1][:, None, : ,:])
    rb = torch.min(rect1[:, :, 3][:, :, None, :], rect2[:, :, 3][:, None, : ,:])
    wh = (rb - lt).clamp(min=0)
    non_rot_inter_areas = wh[:, :, :, 0] * wh[:, :, :, 1]
    non_rot_inter_areas = non_rot_inter_areas.view(B, K1, K2)
    if nums_k2 is not None:
        for b in range(B):
            non_rot_inter_areas[b, :, nums_k2[b]:] = 0

    enclosing_vols = enclosing_box3d_vol(corners1, corners2)
    
    # vols of boxes
    vols1 = box3d_vol_tensor(corners1).clamp(min=EPS)
    vols2 = box3d_vol_tensor(corners2).clamp(min=EPS)
    
    sum_vols = vols1[:, :, None] + vols2[:, None, :]

    # filter malformed boxes
    good_boxes = (enclosing_vols > 2*EPS) * (sum_vols > 4*EPS)

    if rotated_boxes:
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