def test_graph_propagate_forward(self):
layer_1 = layers.Input(1)
layer_2 = layers.Input(2)
graph = LayerGraph()
graph.add_layer(layer_1)
with self.assertRaises(ValueError):
graph.propagate_forward({layer_2: T.matrix()})
def test_graph_propagate_forward(self):
layer_1 = layers.Input(1)
layer_2 = layers.Input(2)
graph = LayerGraph()
graph.add_layer(layer_1)
with self.assertRaises(ValueError):
graph.propagate_forward({layer_2: T.matrix()})
def test_graph_propagate_forward(self):
layer_1 = layers.Input(1)
layer_2 = layers.Input(2)
graph = LayerGraph()
graph.add_layer(layer_1)
input_value_2 = np.random.random((10, 2))
with self.assertRaises(ValueError):
graph.propagate_forward({layer_2: input_value_2})
def test_subgraph_by_layer(self):
layer_1 = layers.Input(1)
layer_2 = layers.Input(2)
graph = LayerGraph()
graph.add_layer(layer_1)
subgraph = graph.subgraph_for_output(layer_1)
self.assertEqual(len(subgraph.forward_graph), 1)
subgraph = graph.subgraph_for_output(layer_2)
self.assertEqual(len(subgraph.forward_graph), 0)
def test_subgraph_by_layer(self):
layer_1 = layers.Input(1)
layer_2 = layers.Input(2)
graph = LayerGraph()
graph.add_layer(layer_1)
subgraph = graph.subgraph_for_output(layer_1)
self.assertEqual(len(subgraph.forward_graph), 1)
subgraph = graph.subgraph_for_output(layer_2)
self.assertEqual(len(subgraph.forward_graph), 0)
