test_autodiff_cpu.py 文件源码

def test_sigmoid_activation():
    x2 = ad.Variable(name='x2')
    y = au.nn.sigmoid(x2)

    x2_val = np.array([-100, 0, 100])
    grad_x2, = ad.gradients(y, [x2])
    executor = ad.Executor([y, grad_x2])
    y_val, grad_x2_val = executor.run(feed_shapes={x2: x2_val})
    npt.assert_array_almost_equal(np.array([0.000, 0.500, 1.0]), y_val)
    npt.assert_array_almost_equal(np.array([0, 0.25, 0]), grad_x2_val)

    # testing with extreme values for numerical stability.
    x2_val = np.array([-9.9e10, 9.9e10]).astype(np.float32)
    y_val, grad_x2_val = executor.run(feed_shapes={x2: x2_val})
    npt.assert_array_almost_equal(np.array([0.0, 1.0]), y_val)
    npt.assert_array_almost_equal(np.array([0.0, 0.0]), grad_x2_val)