def test_weights_is_correct_matrix(self):
layer = Layer(size=5,
prev_size=2,
activation=activation_functions.Sigmoid)
weights = layer.weights()
self.assertTupleEqual(weights.shape, (5, 2))
layer = Layer(size=2,
prev_size=3,
activation=activation_functions.Sigmoid)
weights = layer.weights()
self.assertTupleEqual(weights.shape, (2, 3))
def test_weights_is_of_correct_type(self):
layer = Layer(size=5,
prev_size=2,
activation=activation_functions.Sigmoid)
weights = layer.weights()
self.assertIsInstance(weights, np.ndarray)
self.assertIn(weights.dtype, [np.float32, np.float64])
def test_with_single_hidden_layer(self):
layer = Layer(size=3,
prev_size=2,
activation=activation_functions.Sigmoid)
weights = [[0, 10], [1, 1], [-1, 0.5]]
layer.set_weights(weights=np.array(weights, float))
self.assertEqual(layer.weights().tolist(),
[[0, 10], [1, 1], [-1, 0.5]])
def test_set_weight(self):
layer = Layer(size=2,
prev_size=3,
activation=activation_functions.Sigmoid)
layer.set_weight(row=0, col=1, new_value=2)
layer.set_weight(row=1, col=2, new_value=-0.5)
expected_w = np.array([[0, 2, 0], [0, 0, -0.5]], float)
self.assertEqual(layer.weights().tolist(), expected_w.tolist())