title: TensorFlow Keras guide: custom layer get_config method not updating the layer's configuration?
body: <p>Under the <a href="https://www.tensorflow.org/guide/keras#custom_layers" rel="nofollow noreferrer">custom layers</a> section of the TensorFlow Keras guide there is an optional implementation of the <code>get_config</code> method:</p>
  
  <pre><code>  def get_config(self):
      base_config = super(MyLayer, self).get_config()
      base_config['output_dim'] = self.output_dim
  </code></pre>
  
  <p>Running the full code with some dummy data, then looking at the configuration produced by calling <code>model.get_config()</code> after <code>model.fit(...</code> yields the following output:</p>
  
  <pre><code>[{'class_name': 'MyLayer', 'config': None},
   {'class_name': 'Activation',
   'config': {'name': 'activation_38',
    'trainable': True,
    'dtype': 'float32',
    'activation': 'softmax'}}]
  </code></pre>
  
  <p>My question is: should the config for the custom layer 'MyLayer' not contain the <code>output_dim</code> field as as a result of the final assignment in the <code>get_config</code> method? Many thanks.</p>