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)
