def test_connection_errors(self):
with self.assertRaises(NetworkConnectionError):
# Missed Input layer
GradientDescent(layers.Sigmoid(10) > layers.Sigmoid(1))
with self.assertRaises(NetworkConnectionError):
# Cannot use input layer inside the netowkr
GradientDescent([
layers.Input(1),
layers.Sigmoid(10),
layers.Input(1),
layers.Sigmoid(1),
])
def test_train_epoch_end(self):
global triggered_times
triggered_times = 0
epochs = 4
def print_message(network):
global triggered_times
triggered_times += 1
network = GradientDescent(
connection=(2, 2, 1),
epoch_end_signal=print_message,
)
network.train(xor_input_train, xor_target_train, epochs=epochs)
self.assertEqual(triggered_times, epochs)
def test_list_of_layers(self):
bpnet = GradientDescent([
layers.Input(2),
layers.Sigmoid(3),
layers.Sigmoid(1),
layers.Sigmoid(10),
])
self.assertEqual([layer.size for layer in bpnet.layers], [2, 3, 1, 10])
def test_layers_iteratinos(self):
network = GradientDescent((2, 2, 1))
layers = list(network.all_layers)
output_layer = layers.pop()
self.assertIsNone(output_layer.relate_to_layer)
for layer in layers:
self.assertIsNotNone(layer.relate_to_layer)
def test_recurrent_connections(self):
inp = Sigmoid(2)
hd = [Sigmoid(2), Sigmoid(2)]
out = Output(1)
GradientDescent(connection=(
inp > hd[0] > out,
hd[0] > hd[1],
hd[1] > hd[0],
))
def test_connection_initializations(self):
possible_connections = (
(2, 3, 1),
[Sigmoid(2), Tanh(3), Output(1)],
Relu(2) > Tanh(10) > Output(1),
)
for connection in possible_connections:
network = GradientDescent(connection)
self.assertEqual(len(network.all_layers), 3)
def test_list_of_layers(self):
bpnet = GradientDescent(
[Sigmoid(2), Sigmoid(3),
Sigmoid(1), Output(10)])
self.assertEqual([layer.size for layer in bpnet.all_layers],
[2, 3, 1, 10])
def test_without_output_layer(self):
with self.assertRaises(NetworkConnectionError):
GradientDescent(layers.Sigmoid(10) > layers.Sigmoid(1))
