def _check_typed_subgraph1(g, sg): assert g.idtype == sg.idtype assert g.device == sg.device assert set(sg.ntypes) == {'user', 'game'} assert set(sg.etypes) == {'follows', 'plays', 'wishes'} for ntype in sg.ntypes: assert sg.number_of_nodes(ntype) == g.number_of_nodes(ntype) for etype in sg.etypes: src_sg, dst_sg = sg.all_edges(etype=etype, order='eid') src_g, dst_g = g.all_edges(etype=etype, order='eid') assert F.array_equal(src_sg, src_g) assert F.array_equal(dst_sg, dst_g) assert F.array_equal(sg.nodes['user'].data['h'], g.nodes['user'].data['h']) assert F.array_equal(sg.edges['follows'].data['h'], g.edges['follows'].data['h']) g.nodes['user'].data['h'] = F.scatter_row(g.nodes['user'].data['h'], F.tensor([2]), F.randn( (1, 5))) g.edges['follows'].data['h'] = F.scatter_row( g.edges['follows'].data['h'], F.tensor([1]), F.randn((1, 4))) assert F.array_equal(sg.nodes['user'].data['h'], g.nodes['user'].data['h']) assert F.array_equal(sg.edges['follows'].data['h'], g.edges['follows'].data['h'])
def test_reorder_nodes(): g = dgl.DGLGraph(create_large_graph_index(1000), readonly=True) new_nids = np.random.permutation(g.number_of_nodes()) # TODO(zhengda) we need to test both CSR and COO. new_g = dgl.transform.reorder_nodes(g, new_nids) new_in_deg = new_g.in_degrees() new_out_deg = new_g.out_degrees() in_deg = g.in_degrees() out_deg = g.out_degrees() new_in_deg1 = F.scatter_row(in_deg, F.tensor(new_nids), in_deg) new_out_deg1 = F.scatter_row(out_deg, F.tensor(new_nids), out_deg) assert np.all(F.asnumpy(new_in_deg == new_in_deg1)) assert np.all(F.asnumpy(new_out_deg == new_out_deg1)) orig_ids = F.asnumpy(new_g.ndata['orig_id']) for nid in range(g.number_of_nodes()): neighs = F.asnumpy(g.successors(nid)) new_neighs1 = new_nids[neighs] new_nid = new_nids[nid] new_neighs2 = new_g.successors(new_nid) assert np.all(np.sort(new_neighs1) == np.sort(F.asnumpy(new_neighs2))) for nid in range(new_g.number_of_nodes()): neighs = F.asnumpy(new_g.successors(nid)) old_neighs1 = orig_ids[neighs] old_nid = orig_ids[nid] old_neighs2 = g.successors(old_nid) assert np.all(np.sort(old_neighs1) == np.sort(F.asnumpy(old_neighs2))) neighs = F.asnumpy(new_g.predecessors(nid)) old_neighs1 = orig_ids[neighs] old_nid = orig_ids[nid] old_neighs2 = g.predecessors(old_nid) assert np.all(np.sort(old_neighs1) == np.sort(F.asnumpy(old_neighs2)))
def udf_push(target, name, id_tensor, data_tensor): target[name] = F.scatter_row(target[name], id_tensor, data_tensor * data_tensor)