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test_batched_graph.py
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import dgl
from dgl import DGLGraph
import backend as F
def tree1():
"""Generate a tree
0
/ \
1 2
/ \
3 4
Edges are from leaves to root.
"""
g = dgl.DGLGraph()
g.add_nodes(5)
g.add_edge(3, 1)
g.add_edge(4, 1)
g.add_edge(1, 0)
g.add_edge(2, 0)
g.ndata['h'] = F.tensor([0, 1, 2, 3, 4])
g.edata['h'] = F.randn((4, 10))
return g
def tree2():
"""Generate a tree
1
/ \
4 3
/ \
2 0
Edges are from leaves to root.
"""
g = dgl.DGLGraph()
g.add_nodes(5)
g.add_edge(2, 4)
g.add_edge(0, 4)
g.add_edge(4, 1)
g.add_edge(3, 1)
g.ndata['h'] = F.tensor([0, 1, 2, 3, 4])
g.edata['h'] = F.randn((4, 10))
return g
def test_batch_unbatch():
t1 = tree1()
t2 = tree2()
bg = dgl.batch([t1, t2])
assert bg.number_of_nodes() == 10
assert bg.number_of_edges() == 8
assert bg.batch_size == 2
assert bg.batch_num_nodes == [5, 5]
assert bg.batch_num_edges == [4, 4]
tt1, tt2 = dgl.unbatch(bg)
assert F.allclose(t1.ndata['h'], tt1.ndata['h'])
assert F.allclose(t1.edata['h'], tt1.edata['h'])
assert F.allclose(t2.ndata['h'], tt2.ndata['h'])
assert F.allclose(t2.edata['h'], tt2.edata['h'])
def test_batch_unbatch1():
t1 = tree1()
t2 = tree2()
b1 = dgl.batch([t1, t2])
b2 = dgl.batch([t2, b1])
assert b2.number_of_nodes() == 15
assert b2.number_of_edges() == 12
assert b2.batch_size == 3
assert b2.batch_num_nodes == [5, 5, 5]
assert b2.batch_num_edges == [4, 4, 4]
s1, s2, s3 = dgl.unbatch(b2)
assert F.allclose(t2.ndata['h'], s1.ndata['h'])
assert F.allclose(t2.edata['h'], s1.edata['h'])
assert F.allclose(t1.ndata['h'], s2.ndata['h'])
assert F.allclose(t1.edata['h'], s2.edata['h'])
assert F.allclose(t2.ndata['h'], s3.ndata['h'])
assert F.allclose(t2.edata['h'], s3.edata['h'])
def test_batch_unbatch2():
# test setting/getting features after batch
a = dgl.DGLGraph()
a.add_nodes(4)
a.add_edges(0, [1, 2, 3])
b = dgl.DGLGraph()
b.add_nodes(3)
b.add_edges(0, [1, 2])
c = dgl.batch([a, b])
c.ndata['h'] = F.ones((7, 1))
c.edata['w'] = F.ones((5, 1))
assert F.allclose(c.ndata['h'], F.ones((7, 1)))
assert F.allclose(c.edata['w'], F.ones((5, 1)))
def test_batch_send_then_recv():
t1 = tree1()
t2 = tree2()
bg = dgl.batch([t1, t2])
bg.register_message_func(lambda edges: {'m' : edges.src['h']})
bg.register_reduce_func(lambda nodes: {'h' : F.sum(nodes.mailbox['m'], 1)})
u = [3, 4, 2 + 5, 0 + 5]
v = [1, 1, 4 + 5, 4 + 5]
bg.send((u, v))
bg.recv([1, 9]) # assuming recv takes in unique nodes
t1, t2 = dgl.unbatch(bg)
assert t1.ndata['h'][1] == 7
assert t2.ndata['h'][4] == 2
def test_batch_send_and_recv():
t1 = tree1()
t2 = tree2()
bg = dgl.batch([t1, t2])
bg.register_message_func(lambda edges: {'m' : edges.src['h']})
bg.register_reduce_func(lambda nodes: {'h' : F.sum(nodes.mailbox['m'], 1)})
u = [3, 4, 2 + 5, 0 + 5]
v = [1, 1, 4 + 5, 4 + 5]
bg.send_and_recv((u, v))
t1, t2 = dgl.unbatch(bg)
assert t1.ndata['h'][1] == 7
assert t2.ndata['h'][4] == 2
def test_batch_propagate():
t1 = tree1()
t2 = tree2()
bg = dgl.batch([t1, t2])
bg.register_message_func(lambda edges: {'m' : edges.src['h']})
bg.register_reduce_func(lambda nodes: {'h' : F.sum(nodes.mailbox['m'], 1)})
# get leaves.
order = []
# step 1
u = [3, 4, 2 + 5, 0 + 5]
v = [1, 1, 4 + 5, 4 + 5]
order.append((u, v))
# step 2
u = [1, 2, 4 + 5, 3 + 5]
v = [0, 0, 1 + 5, 1 + 5]
order.append((u, v))
bg.prop_edges(order)
t1, t2 = dgl.unbatch(bg)
assert t1.ndata['h'][0] == 9
assert t2.ndata['h'][1] == 5
def test_batched_edge_ordering():
g1 = dgl.DGLGraph()
g1.add_nodes(6)
g1.add_edges([4, 4, 2, 2, 0], [5, 3, 3, 1, 1])
e1 = F.randn((5, 10))
g1.edata['h'] = e1
g2 = dgl.DGLGraph()
g2.add_nodes(6)
g2.add_edges([0, 1 ,2 ,5, 4 ,5], [1, 2, 3, 4, 3, 0])
e2 = F.randn((6, 10))
g2.edata['h'] = e2
g = dgl.batch([g1, g2])
r1 = g.edata['h'][g.edge_id(4, 5)]
r2 = g1.edata['h'][g1.edge_id(4, 5)]
assert F.array_equal(r1, r2)
def test_batch_no_edge():
g1 = dgl.DGLGraph()
g1.add_nodes(6)
g1.add_edges([4, 4, 2, 2, 0], [5, 3, 3, 1, 1])
g2 = dgl.DGLGraph()
g2.add_nodes(6)
g2.add_edges([0, 1, 2, 5, 4, 5], [1 ,2 ,3, 4, 3, 0])
g3 = dgl.DGLGraph()
g3.add_nodes(1) # no edges
g = dgl.batch([g1, g3, g2]) # should not throw an error
if __name__ == '__main__':
test_batch_unbatch()
test_batch_unbatch1()
test_batch_unbatch2()
test_batched_edge_ordering()
test_batch_send_then_recv()
test_batch_send_and_recv()
test_batch_propagate()
test_batch_no_edge()