145170ca9bbd89aa01d8a40841e3c039d3683af8,tests/layer/test_graph_attention.py,Test_GAT,test_gat_node_model_l2norm,#Test_GAT#,370

Before Change

        model = keras.Model(inputs=x_in, outputs=x_out)

        X = gen.features
        A = gen.Aadj
        actual = model.predict([X, A])
        expected = np.ones((G.number_of_nodes(), self.layer_sizes[-1])) * (
            1.0 / G.number_of_nodes()
        )
        assert expected == pytest.approx(actual)

After Change

            1.0 / G.number_of_nodes()
        )

        assert np.allclose(expected, actual[0])

    def test_gat_node_model_no_norm(self):
        G = example_graph_1(feature_size=self.F_in)
        gen = FullBatchNodeGenerator(G, sparse=False)

Instances