def test_relu_1(self):
input = np.array([[2, 3, 5, 1, 7], [4, 3, 0, 5, 5], [-1, 2, 0, -3,
-4]])
output = np.array([[2, 3, 5, 1, 7], [4, 3, 0, 5, 5], [0, 2, 0, 0, 0]])
np.testing.assert_allclose(util_functions.relu(input),
output,
atol=0.0001)
def test_linear_with_relu_2(self):
x = np.array([[1, 2, 0, -1], [1, 2, 33, 15]])
w = np.array([[0., 1., 0., 0.], [0., 2., 2., 0.]])
b = np.array([-5., -1.])
expected_res = np.array([[0., 3.], [0., 69.]])
np.testing.assert_allclose(util_functions.relu(
util_functions.linear(x, w, b)),
expected_res,
atol=0.0001)
def test_linear_with_relu_1(self):
x = np.array([[1, 2, 33, 15], [1, 2, 33, 15]])
w = np.array([[0., 1., 0., 0.], [0., 2., 2., 0.]])
b = np.zeros(2)
expected_res = np.array([[2., 70.], [2., 70.]])
np.testing.assert_allclose(util_functions.relu(
util_functions.linear(x, w, b)),
expected_res,
atol=0.0001)
def __call__(self, z):
self.layer_input = z
self.layer_output = util_functions.relu(z)
return self.layer_output
def relu_function(x):
return np.sum(
util_functions.relu(x)), util_functions.relu_derivative(x)
def test_relu_3(self):
input = np.array([-2, -3, 5, 1, 7])
output = np.array([0, 0, 5, 1, 7])
np.testing.assert_allclose(util_functions.relu(input),
output,
atol=0.0001)