,                            input.coords_key, None, input.coords_man)))          coords, feats, labels = data_loader(in_channels, batch_size=0)         feats = feats.double()         feats.requires_grad_()         input = SparseTensor(feats, coords=coords)         pool = MinkowskiGlobalPooling()         output = pool(input)         print(output)          # Check backward         fn = MinkowskiGlobalPoolingFunction()         self.assertTrue(             gradcheck(fn, (input.F, True, GlobalPoolingMode.