class TestForMultipleHiddenLayers(unittest.TestCase):
def setUp(self):
self.patcher = patch('builtins.print')
self.mock_object = self.patcher.start()
self.x_test = np.array([[1], [0]])
self.y_test = np.array([[1], [0]])
self.hidden_node_biases = [0.10399593413625441, 0.9477095968224993]
self.output_node_biases = [0.1683069001902736]
self.weights = [
0.08946817286422626, 0.10066428298027419, 0.8768683269443115
]
self.net = NeuralNet(1,
4,
1,
1,
self.hidden_node_biases,
self.output_node_biases,
self.weights,
learning_rate=0.01)
def tearDown(self):
self.patcher.stop()
def test_weights(self):
self.assertEqual(self.net.get_weights(), self.weights)
def test_biases(self):
self.assertEqual(
self.net.get_biases(),
[0.10399593413625441, 0.9477095968224993, 0.1683069001902736])
def test_partial_derivatives_for_biases(self):
self.net.train(self.x_test, self.y_test, 1)
self.assertEqual(
self.net.get_biases(),
[0.10397901969529151, 0.9470426291307198, 0.16445586456466701])
def test_partial_derivatives_for_weights(self):
self.net.train(self.x_test, self.y_test, 1)
self.assertEqual(
self.net.get_weights(),
[0.08948139076478426, 0.10032526109304217, 0.8740529208576437])
class TestForMultipleOutputs(unittest.TestCase):
def setUp(self):
self.patcher = patch('builtins.print')
self.mock_object = self.patcher.start()
self.x_test = np.array([[1, 0], [0, 1], [0, 0], [1, 1]])
self.y_test = np.array([[0, 1], [0, 1], [1, 0], [1, 0]])
self.hidden_node_biases = [2, 2]
self.output_node_biases = [3, 3]
self.weights = [5, 5, 5, 5, 5, 5, 5, 5]
self.net = NeuralNet(2,
3,
2,
2,
self.hidden_node_biases,
self.output_node_biases,
self.weights,
activation_function=ActivationFunction.LOG,
learning_rate=0.01)
def tearDown(self):
self.patcher.stop()
def test_weights(self):
self.assertEqual(self.net.get_weights(), self.weights)
def test_biases(self):
self.assertEqual(self.net.get_biases(), [2, 2, 3, 3])
def test_partial_derivatives_for_biases(self):
self.net.train(self.x_test, self.y_test, 1)
self.assertEqual(self.net.get_biases(), [
2.000000000000002, 2.000000000000002, 3.0000000257168224,
2.99999997428318
])
def test_partial_derivatives_for_weights(self):
self.net.train(self.x_test, self.y_test, 1)
self.assertEqual(self.net.get_weights(), [
5.0, 5.0, 5.0, 5.0, 5.000000021300251, 4.999999978699751,
5.000000021300251, 4.999999978699751
])
