def test_disassemble_params(self):
net = FeedforwardNetwork(ninput=3,
noutput=2,
nhidden=[2, 3],
activ_func=Logistic())
params = [
1111, 1112, 1113, 1121, 1122, 1123, 121, 122, 2111, 2112, 2121,
2122, 2131, 2132, 221, 222, 223, 3111, 3112, 3113, 3121, 3122,
3123, 321, 322
]
w, b = net.disassemble_params(params)
W0 = [[1111, 1112, 1113], [1121, 1122, 1123]]
W1 = [[2111, 2112], [2121, 2122], [2131, 2132]]
W2 = [[3111, 3112, 3113], [3121, 3122, 3123]]
B0 = [[121], [122]]
B1 = [[221], [222], [223]]
B2 = [[321], [322]]
assert_array_almost_equal(w[0], W0)
assert_array_almost_equal(w[1], W1)
assert_array_almost_equal(w[2], W2)
assert_array_almost_equal(b[0], B0)
assert_array_almost_equal(b[1], B1)
assert_array_almost_equal(b[2], B2)
def test_two_hiddenlayer_three_input_two_output(self):
l = Logistic()
i = Identity()
net = FeedforwardNetwork(ninput=3,
noutput=2,
nhidden=[2, 3],
activ_func=Logistic())
params = np.array([
1.111, 1.112, 11.13, 112.1, 0.1122, 1123, 12.1, 1.22, 0.2111,
0.2112, 2.121, 2.122, 0.2131, 0.2132, 2.21, 2.22, 0.223, 3.111,
0.3112, 3.113, 0.3121, 0.3122, 0.3123, 0.321, 3.22
])
w, b = net.disassemble_params(params)
innet = np.asarray([1, 2, 3]).reshape(3, 1)
expected = i(
np.dot(w[2], l(np.dot(w[1], l(np.dot(w[0], innet) + b[0])) +
b[1])) + b[2]).flatten()
assert_array_almost_equal(net(innet, params), expected, decimal=3)
innet = np.asarray([1.78, -2, 3]).reshape(3, 1)
expected = i(
np.dot(w[2], l(np.dot(w[1], l(np.dot(w[0], innet) + b[0])) +
b[1])) + b[2]).flatten()
assert_array_almost_equal(net(innet, params), expected, decimal=3)
innet = np.asarray([1, 25, 3]).reshape(3, 1)
expected = i(
np.dot(w[2], l(np.dot(w[1], l(np.dot(w[0], innet) + b[0])) +
b[1])) + b[2]).flatten()
assert_array_almost_equal(net(innet, params), expected, decimal=3)