af61e2fbb45c53df3ff2a91f81a2026a8f66d90d,tests/tensorflow/test_nn.py,,test_gat_conv,#,309

Before Change

    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

def test_sage_conv():
    for aggre_type in ["mean", "pool", "gcn", "lstm"]:
        ctx = F.ctx()

After Change

    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)

@pytest.mark.parametrize("aggre_type", ["mean", "pool", "gcn", "lstm"])
def test_sage_conv(aggre_type):
    ctx = F.ctx()

Instances