def _test_back_propagate():
mynet = Network(4, 2, 3)
mynet.create_connections()
mynet.feed_forward([1, 1, 1, 1])
print(mynet.output_ouputs)
mynet.matrix_who = np.matrix([[0.11, 0.12, 0.13], [0.21, 0.22, 0.23]])
mynet.output_ouputs = np.matrix([[0.1, 0.2, 0.3]])
target = [0.9, 0.8, 0.7]
mynet.back_propagate(target)
def _test_ouput_deltas():
mynet = Network(4, 2, 3)
mynet.create_connections()
mynet.feed_forward([1, 1, 1, 1])
print(mynet.output_ouputs)
mynet.matrix_who = np.matrix([[0.11, 0.12, 0.13], [0.21, 0.22, 0.23]])
mynet.output_ouputs = np.matrix([[0.1, 0.2, 0.3]])
target = [0.9, 0.8, 0.7]
ods = mynet.get_output_deltas(target)
np.testing.assert_array_almost_equal(
np.matrix([(0.9 - 0.1) * mynet.gradient(0.1),
(0.8 - 0.2) * mynet.gradient(0.2),
(0.7 - 0.3) * mynet.gradient(0.3)]), ods)
def _test_hidden_deltas():
mynet = Network(4, 2, 3)
mynet.create_connections()
mynet.feed_forward([1, 1, 1, 1])
print(mynet.output_ouputs)
mynet.matrix_who = np.matrix([[0.11, 0.12, 0.13], [0.21, 0.22, 0.23]])
mynet.output_ouputs = np.matrix([[0.1, 0.2, 0.3]])
target = [0.9, 0.8, 0.7]
ods = mynet.get_output_deltas(target)
mynet.matrix_who = np.matrix([[1, 2, 3], [4, 5, 6]])
mynet.hidden_outputs = np.matrix([[0.5, 0.6]])
ods = np.matrix([[0.05, 0.06, 0.07]])
hds = mynet.get_hidden_deltas(ods)
np.testing.assert_array_almost_equal(
np.matrix([mynet.gradient(0.5) * 0.38,
mynet.gradient(0.6) * 0.92]), hds)