def test_model_forward():
np.random.seed(6)
x = np.random.randn(5, 4)
w1 = np.random.randn(4, 5)
b1 = np.random.randn(4, 1)
w2 = np.random.randn(3, 4)
b2 = np.random.randn(3, 1)
w3 = np.random.randn(1, 3)
b3 = np.random.randn(1, 1)
nn = NeuralNetwork(w=[w1, w2, w3], b=[b1, b2, b3], params_ok=True)
al = nn.model_forward(x)
nt.eq_(len(nn.cache), 3)
assert_eq(al, [[0.03921668, 0.70498921, 0.19734387, 0.04728177]])
def test_forward_propagation_dropout():
np.random.seed(1)
x = np.random.randn(3, 5)
w1 = np.random.randn(2, 3)
b1 = np.random.randn(2, 1)
w2 = np.random.randn(3, 2)
b2 = np.random.randn(3, 1)
w3 = np.random.randn(1, 3)
b3 = np.random.randn(1, 1)
np.random.seed(1)
nn = NeuralNetwork(w=[w1, w2, w3], b=[b1, b2, b3], params_ok=True)
a3 = nn.model_forward(x, keep_prop=0.7)
assert_eq(a3,
[[0.36974721, 0.00305176, 0.04565099, 0.49683389, 0.36974721]],
rtol=1e-5)