def test_gat_conv():
g = dgl.DGLGraph(sp.sparse.random(100, 100, density=0.1), readonly=True)
gat = nn.GATConv(5, 2, 4)
feat = F.randn((100, 5))
h = gat(g, feat)
assert h.shape == (100, 4, 2)
g = dgl.bipartite(sp.sparse.random(100, 200, density=0.1))
gat = nn.GATConv((5, 10), 2, 4)
feat = (F.randn((100, 5)), F.randn((200, 10)))
h = gat(g, feat)
def test_gat_conv(g, idtype, out_dim, num_heads):
g = g.astype(idtype).to(F.ctx())
ctx = F.ctx()
gat = nn.GATConv(5, out_dim, num_heads)
feat = F.randn((g.number_of_src_nodes(), 5))
h = gat(g, feat)
assert h.shape == (g.number_of_dst_nodes(), num_heads, out_dim)
_, a = gat(g, feat, get_attention=True)
assert a.shape == (g.number_of_edges(), num_heads, 1)
# test residual connection
gat = nn.GATConv(5, out_dim, num_heads, residual=True)
h = gat(g, feat)
def test_gat_conv(g, idtype):
g = g.astype(idtype).to(F.ctx())
ctx = F.ctx()
gat = nn.GATConv(5, 2, 4)
feat = F.randn((g.number_of_nodes(), 5))
h = gat(g, feat)
assert h.shape == (g.number_of_nodes(), 4, 2)
def test_gat_conv_bi(g, idtype):
g = g.astype(idtype).to(F.ctx())
ctx = F.ctx()
gat = nn.GATConv((5, 10), 2, 4)
feat = (F.randn(
(g.number_of_src_nodes(), 5)), F.randn((g.number_of_dst_nodes(), 10)))
h = gat(g, feat)
assert h.shape == (g.number_of_dst_nodes(), 4, 2)
def test_gat_conv(g, idtype):
g = g.astype(idtype).to(F.ctx())
ctx = F.ctx()
gat = nn.GATConv(5, 2, 4)
feat = F.randn((g.number_of_nodes(), 5))
h = gat(g, feat)
assert h.shape == (g.number_of_nodes(), 4, 2)
_, a = gat(g, feat, get_attention=True)
assert a.shape == (g.number_of_edges(), 4, 1)
def test_gat_conv():
g = dgl.DGLGraph(sp.sparse.random(100, 100, density=0.1), readonly=True)
gat = nn.GATConv(5, 2, 4)
feat = F.randn((100, 5))
h = gat(g, feat)
assert h.shape == (100, 4, 2)
g = dgl.bipartite(sp.sparse.random(100, 200, density=0.1))
gat = nn.GATConv((5, 10), 2, 4)
feat = (F.randn((100, 5)), F.randn((200, 10)))
h = gat(g, feat)
g = dgl.graph(sp.sparse.random(100, 100, density=0.001))
seed_nodes = np.unique(g.edges()[1].numpy())
block = dgl.to_block(g, seed_nodes)
gat = nn.GATConv(5, 2, 4)
feat = F.randn((block.number_of_src_nodes(), 5))
h = gat(block, feat)
assert h.shape == (block.number_of_dst_nodes(), 4, 2)
def test_gat_conv():
g = dgl.DGLGraph(sp.sparse.random(100, 100, density=0.1), readonly=True)
gat = nn.GATConv(5, 2, 4)
feat = F.randn((100, 5))
h = gat(g, feat)
assert h.shape[-1] == 2 and h.shape[-2] == 4
