자동 미분

import tensorflow as tf

x = tf.Variable(3.0)

<tf.Variable 'Variable:0' shape=() dtype=float32, numpy=3.0>

with tf.GradientTape() as tape:
    y = x ** 2

<tf.Tensor: shape=(), dtype=float32, numpy=9.0>

grad = tape.gradient(y, x)

grad

<tf.Tensor: shape=(), dtype=float32, numpy=6.0>

optimizer = tf.keras.optimizers.Adam(learning_rate=0.1)

optimizer.apply_gradients([(grad, x)])

<tf.Variable 'UnreadVariable' shape=() dtype=int64, numpy=1>

<tf.Variable 'Variable:0' shape=() dtype=float32, numpy=2.9>

with tf.GradientTape() as tape:
    y = x ** 2

<tf.Tensor: shape=(), dtype=float32, numpy=8.410001>

for i in range(30):
    with tf.GradientTape() as tape:
        y = x ** 2
    grad = tape.gradient(y, x)
    optimizer.apply_gradients([(grad, x)])
    print(x.numpy(), y.numpy())