title: Learning rate of custom training loop for tensorflow 2.0
body: <p>Are there any functions or methods which can show the learning rate when I use the tensorflow 2.0 custom training loop? </p>
  
  <p>Here is an example of tensorflow guide: </p>
  
  <pre><code>def train_step(images, labels):
    with tf.GradientTape() as tape:
      predictions = model(images)
      loss = loss_object(labels, predictions)
    gradients = tape.gradient(loss, model.trainable_variables)
    optimizer.apply_gradients(zip(gradients, model.trainable_variables))
  
    train_loss(loss)
    train_accuracy(labels, predictions)
  </code></pre>
  
  <p>How can I retrieve the current learning rate from the optimizer when the model is training?</p>
  
  <p>I will be grateful for any help you can provide. :)</p>