def test_activation_elu_infer(self): graph = build_graph(self.nodes_attributes, [ ('node_1', 'activation_node'), ('activation_node', 'node_3') ], { 'node_1': { 'value': np.array([6, -4, -2, -1]) }, 'activation_node': { 'operation': 'elu', 'alpha': 1.0, }, 'node_3': { 'value': None } }) graph.graph['layout'] = 'NCHW' activation_node = Node(graph, 'activation_node') Activation.infer(activation_node) exp_shape = np.array([227, 227, 227, 227]) res_shape = graph.node['node_3']['shape'] res_value = graph.node['node_3']['value'] exp_value = np.array([6., -0.98168436, -0.86466472, -0.63212056]) for i, value in enumerate(exp_shape): self.assertEqual(res_shape[i], value) for i, value in enumerate(exp_value): self.assertAlmostEqual(res_value[i], value)
def test_activation_infer(self): graph = build_graph(self.nodes_attributes, [ ('node_1', 'activation_node'), ('activation_node', 'node_3') ], { 'node_1': { 'value': np.array([0, 7, 3, -1]) }, 'activation_node': { 'operation': 'relu6' }, 'node_3': { 'value': None } }) graph.graph['layout'] = 'NCHW' activation_node = Node(graph, 'activation_node') Activation.infer(activation_node) exp_shape = np.array([227, 227, 227, 227]) res_shape = graph.node['node_3']['shape'] res_value = graph.node['node_3']['value'] exp_value = np.array([0, 6, 3, 0]) for i, value in enumerate(exp_shape): self.assertEqual(res_shape[i], value) for i, value in enumerate(exp_value): self.assertEqual(res_value[i], value)