Method test_empty

tests/python/pruning.py:82–109

(self)

        print(output)

    def test_empty(self):
        in_channels = 2
        coords, feats, labels = data_loader(in_channels, batch_size=1)
        feats = feats.double()
        feats.requires_grad_()
        input = SparseTensor(feats, coords)
        use_feat = torch.BoolTensor(len(input))
        use_feat.zero_()
        pruning = MinkowskiPruning()
        output = pruning(input, use_feat)
        print(input)
        print(use_feat)
        print(output)

        # Check backward
        fn = MinkowskiPruningFunction()
        self.assertTrue(
            gradcheck(
                fn,
                (
                    input.F,
                    use_feat,
                    input.coordinate_map_key,
                    output.coordinate_map_key,
                    input.coordinate_manager,
                ),
            )
        )

    def test_pruning(self):
        in_channels, D = 2, 2