def test_backprop_multisample_zero_is_zero(self):
lc = LinearCombination(4, 1)
in_error_buffers = [np.zeros_like(self.X)]
lc.backprop(self.theta, [self.X], self.T, np.zeros_like(self.T), in_error_buffers)
grad = np.zeros_like(self.theta)
lc.calculate_gradient(self.theta, grad, [self.X], self.T, in_error_buffers, np.zeros_like(self.T))
assert_allclose(in_error_buffers[0], np.zeros_like(self.X))
assert_allclose(grad, np.zeros_like(self.theta))
def test_backprop_multisample_zero_is_zero(self):
lc = LinearCombination(4, 1)
in_error_buffers = [np.zeros_like(self.X)]
lc.backprop(self.theta, [self.X], self.T, np.zeros_like(self.T),
in_error_buffers)
grad = np.zeros_like(self.theta)
lc.calculate_gradient(self.theta, grad, [self.X], self.T,
in_error_buffers, np.zeros_like(self.T))
assert_allclose(in_error_buffers[0], np.zeros_like(self.X))
assert_allclose(grad, np.zeros_like(self.theta))
