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)
