def build_graph(self, mg, src, dst, ntid, etid, ntypes, etypes):
# create h**o graph
print('Creating one whole graph ...')
g = dgl.graph((src, dst))
g.ndata[dgl.NTYPE] = F.tensor(ntid)
g.edata[dgl.ETYPE] = F.tensor(etid)
print('Total #nodes:', g.number_of_nodes())
print('Total #edges:', g.number_of_edges())
# rename names such as 'type' so that they an be used as keys
# to nn.ModuleDict
etypes = [RENAME_DICT.get(ty, ty) for ty in etypes]
mg_edges = mg.edges(keys=True)
mg = nx.MultiDiGraph()
for sty, dty, ety in mg_edges:
mg.add_edge(sty, dty, key=RENAME_DICT.get(ety, ety))
# convert to heterograph
print('Convert to heterograph ...')
hg = dgl.to_hetero(g,
ntypes,
etypes,
metagraph=mg)
print('#Node types:', len(hg.ntypes))
print('#Canonical edge types:', len(hg.etypes))
print('#Unique edge type names:', len(set(hg.etypes)))
self.graph = hg
def build_graph(self, mg, src, dst, ntid, etid, ntypes, etypes):
"""Build the graphs
Parameters
----------
mg: MultiDiGraph
Input graph
src: Numpy array
Source nodes
dst: Numpy array
Destination nodes
ntid: Numpy array
Node types for each node
etid: Numpy array
Edge types for each edge
ntypes: list
Node types
etypes: list
Edge types
Returns
-------
g: DGLGraph
"""
# create h**o graph
if self.verbose:
print('Creating one whole graph ...')
g = dgl.graph((src, dst))
g.ndata[dgl.NTYPE] = F.tensor(ntid)
g.edata[dgl.ETYPE] = F.tensor(etid)
if self.verbose:
print('Total #nodes:', g.number_of_nodes())
print('Total #edges:', g.number_of_edges())
# rename names such as 'type' so that they an be used as keys
# to nn.ModuleDict
etypes = [RENAME_DICT.get(ty, ty) for ty in etypes]
mg_edges = mg.edges(keys=True)
mg = nx.MultiDiGraph()
for sty, dty, ety in mg_edges:
mg.add_edge(sty, dty, key=RENAME_DICT.get(ety, ety))
# convert to heterograph
if self.verbose:
print('Convert to heterograph ...')
hg = dgl.to_hetero(g,
ntypes,
etypes,
metagraph=mg)
if self.verbose:
print('#Node types:', len(hg.ntypes))
print('#Canonical edge types:', len(hg.etypes))
print('#Unique edge type names:', len(set(hg.etypes)))
return hg
def create_test_heterograph1():
edges = []
edges.extend([(0,1), (1,2)]) # follows
edges.extend([(0,3), (1,3), (2,4), (1,4)]) # plays
edges.extend([(0,4), (2,3)]) # wishes
edges.extend([(5,3), (6,4)]) # develops
ntypes = F.tensor([0, 0, 0, 1, 1, 2, 2])
etypes = F.tensor([0, 0, 1, 1, 1, 1, 2, 2, 3, 3])
g0 = dgl.graph(edges)
g0.ndata[dgl.NTYPE] = ntypes
g0.edata[dgl.ETYPE] = etypes
return dgl.to_hetero(g0, ['user', 'game', 'developer'], ['follows', 'plays', 'wishes', 'develops'])
def build_graph(self, mg, src, dst, ntid, etid, ntypes, etypes):
# create h**o graph
print('Creating one whole graph ...')
g = dgl.graph((src, dst))
g.ndata[dgl.NTYPE] = F.tensor(ntid)
g.edata[dgl.ETYPE] = F.tensor(etid)
print('Total #nodes:', g.number_of_nodes())
print('Total #edges:', g.number_of_edges())
# convert to heterograph
print('Convert to heterograph ...')
hg = dgl.to_hetero(g, ntypes, etypes, metagraph=mg)
print('#Node types:', len(hg.ntypes))
print('#Canonical edge types:', len(hg.etypes))
print('#Unique edge type names:', len(set(hg.etypes)))
self.graph = hg
def test_convert():
hg = create_test_heterograph()
hs = []
for ntype in hg.ntypes:
h = F.randn((hg.number_of_nodes(ntype), 5))
hg.nodes[ntype].data['h'] = h
hs.append(h)
hg.nodes['user'].data['x'] = F.randn((3, 3))
ws = []
for etype in hg.canonical_etypes:
w = F.randn((hg.number_of_edges(etype), 5))
hg.edges[etype].data['w'] = w
ws.append(w)
hg.edges['plays'].data['x'] = F.randn((4, 3))
g = dgl.to_homo(hg)
assert F.array_equal(F.cat(hs, dim=0), g.ndata['h'])
assert 'x' not in g.ndata
assert F.array_equal(F.cat(ws, dim=0), g.edata['w'])
assert 'x' not in g.edata
src, dst = g.all_edges(order='eid')
src = F.asnumpy(src)
dst = F.asnumpy(dst)
etype_id, eid = F.asnumpy(g.edata[dgl.ETYPE]), F.asnumpy(g.edata[dgl.EID])
ntype_id, nid = F.asnumpy(g.ndata[dgl.NTYPE]), F.asnumpy(g.ndata[dgl.NID])
for i in range(g.number_of_edges()):
srctype = hg.ntypes[ntype_id[src[i]]]
dsttype = hg.ntypes[ntype_id[dst[i]]]
etype = hg.etypes[etype_id[i]]
src_i, dst_i = hg.find_edges([eid[i]], (srctype, etype, dsttype))
assert np.asscalar(F.asnumpy(src_i)) == nid[src[i]]
assert np.asscalar(F.asnumpy(dst_i)) == nid[dst[i]]
mg = nx.MultiDiGraph([('user', 'user', 'follows'),
('user', 'game', 'plays'),
('user', 'game', 'wishes'),
('developer', 'game', 'develops')])
for _mg in [None, mg]:
hg2 = dgl.to_hetero(g, ['user', 'game', 'developer'],
['follows', 'plays', 'wishes', 'develops'],
ntype_field=dgl.NTYPE,
etype_field=dgl.ETYPE,
metagraph=_mg)
assert set(hg.ntypes) == set(hg2.ntypes)
assert set(hg.canonical_etypes) == set(hg2.canonical_etypes)
for ntype in hg.ntypes:
assert hg.number_of_nodes(ntype) == hg2.number_of_nodes(ntype)
assert F.array_equal(hg.nodes[ntype].data['h'],
hg2.nodes[ntype].data['h'])
for canonical_etype in hg.canonical_etypes:
src, dst = hg.all_edges(etype=canonical_etype, order='eid')
src2, dst2 = hg2.all_edges(etype=canonical_etype, order='eid')
assert F.array_equal(src, src2)
assert F.array_equal(dst, dst2)
assert F.array_equal(hg.edges[canonical_etype].data['w'],
hg2.edges[canonical_etype].data['w'])
# hetero_from_homo test case 2
g = dgl.graph([(0, 2), (1, 2), (2, 3), (0, 3)])
g.ndata[dgl.NTYPE] = F.tensor([0, 0, 1, 2])
g.edata[dgl.ETYPE] = F.tensor([0, 0, 1, 2])
hg = dgl.to_hetero(g, ['l0', 'l1', 'l2'], ['e0', 'e1', 'e2'])
assert set(hg.canonical_etypes) == set([('l0', 'e0', 'l1'),
('l1', 'e1', 'l2'),
('l0', 'e2', 'l2')])
assert hg.number_of_nodes('l0') == 2
assert hg.number_of_nodes('l1') == 1
assert hg.number_of_nodes('l2') == 1
assert hg.number_of_edges('e0') == 2
assert hg.number_of_edges('e1') == 1
assert hg.number_of_edges('e2') == 1
# hetero_from_homo test case 3
mg = nx.MultiDiGraph([('user', 'movie', 'watches'),
('user', 'TV', 'watches')])
g = dgl.graph([(0, 1), (0, 2)])
g.ndata[dgl.NTYPE] = F.tensor([0, 1, 2])
g.edata[dgl.ETYPE] = F.tensor([0, 0])
for _mg in [None, mg]:
hg = dgl.to_hetero(g, ['user', 'TV', 'movie'], ['watches'],
metagraph=_mg)
assert set(hg.canonical_etypes) == set([('user', 'watches', 'movie'),
('user', 'watches', 'TV')])
assert hg.number_of_nodes('user') == 1
assert hg.number_of_nodes('TV') == 1
assert hg.number_of_nodes('movie') == 1
assert hg.number_of_edges(('user', 'watches', 'TV')) == 1
assert hg.number_of_edges(('user', 'watches', 'movie')) == 1
assert len(hg.etypes) == 2
# hetero_to_homo test case 2
hg = dgl.bipartite([(0, 0), (1, 1)], card=(2, 3))
g = dgl.to_homo(hg)
assert g.number_of_nodes() == 5
import dgl
if __name__ == "__main__":
follows_g = dgl.graph([(0, 1), (1, 2)], 'user', 'follows')
devs_g = dgl.bipartite([(0, 0), (1, 1)], 'developer', 'develops', 'game')
hetero_g = dgl.hetero_from_relations([follows_g, devs_g])
homo_g = dgl.to_homo(hetero_g)
hetero_g_2 = dgl.to_hetero(homo_g, hetero_g.ntypes, hetero_g.etypes)
print(hetero_g)
print(hetero_g_2)
print("here")
