def test_set_and_get_weights():
input_dimensions = 4
number_of_nodes = 9
model = SingleLayerNN(input_dimensions=input_dimensions, number_of_nodes=number_of_nodes)
weights=model.get_weights()
assert weights.ndim == 2 and \
weights.shape[0] == number_of_nodes and \
weights.shape[1] == (input_dimensions + 1)
model.set_weights(np.ones((number_of_nodes, input_dimensions + 1)))
weights = model.get_weights()
assert weights.ndim == 2 and \
weights.shape[0] == number_of_nodes and \
weights.shape[1] == (input_dimensions + 1)
assert np.array_equal(model.get_weights(), np.ones((number_of_nodes, input_dimensions + 1)))
def test_weight_initialization():
input_dimensions = 2
number_of_nodes = 5
model = SingleLayerNN(input_dimensions=2, number_of_nodes=number_of_nodes)
model.initialize_weights(seed=1)
assert model.weights.ndim == 2 and model.weights.shape[0] == number_of_nodes and model.weights.shape[
1] == input_dimensions + 1
weights = np.array([[1.62434536, -0.61175641, -0.52817175],
[-1.07296862, 0.86540763, -2.3015387],
[1.74481176, -0.7612069, 0.3190391],
[-0.24937038, 1.46210794, -2.06014071],
[-0.3224172, -0.38405435, 1.13376944]])
np.testing.assert_allclose(model.get_weights(), weights, rtol=1e-3, atol=1e-3)