x_data = tf.random.normal(shape=(1000,), dtype=tf.float32)
y_data = 3*x_data - 1
w = tf.Variable(-1.)
b = tf.Variable(-1.)
learning_rate = 0.01
w_trace, b_trace = [], []
for x, y in zip(x_data, y_data):
with tf.GradientTape() as tape:
prediction = w*x + b
loss = (prediction - y)**2
gradients = tape.gradient(loss, [w, b])
w_trace.append(w.numpy())
b_trace.append(b.numpy())
w = tf.Variable(w - learning_rate=gradients[0])
b = tf.Variable(b - learning_rate=gradients[1])
flg, ax = plt.subplots(figsize=(20, 10))
ax.plot(w_trace,
label='weight')
ax.plot(b_trace,
label='bias')
ax.tick_params(labelsize=20)
ax.legend(fontsize=30)
구글 코랩으로 진행하고 있다가 이런 오류가 났습니다, 어떻게 해결해야 하나요?