TensorFlow Autodiff自动微分详解

如下所示： with tf.GradientTape(persistent=True) as tape: z1 = f(w1, w2 + 2.) z2 = f(w1, w2 + 5.) z3 = f(w1, w2 + 7.) z = [z1,z3,z3] [tape.gradient(z, [w1, w2]) for z in (z1, z2, z3)] 输出结果 [[<tf id=56906, shape=(), dtype=float32, numpy=40.0>, &lt;tf.Tensor: id=56898, shape=(), dtype=float32,