title: Tensorflow——keras model.save() raise NotImplementedError
body: <pre class="lang-py prettyprint-override"><code>import tensorflow as tf 
  
  mnist = tf.keras.datasets.mnist 
  
  (x_train, y_train), (x_test, y_test) = mnist.load_data()
  
  x_train = tf.keras.utils.normalize(x_train, axis=1)
  x_test = tf.keras.utils.normalize(x_test, axis=1)
  
  model = tf.keras.models.Sequential()
  
  model.add(tf.keras.layers.Flatten())
  model.add(tf.keras.layers.Dense(128,activation=tf.nn.relu))
  model.add(tf.keras.layers.Dense(128,activation=tf.nn.relu))
  model.add(tf.keras.layers.Dense(10,activation=tf.nn.softmax))
  
  model.compile(optimizer ='adam',
              loss='sparse_categorical_crossentropy',
               metrics=['accuracy'])
  model.fit(x_train, y_train, epochs=3)
  </code></pre>
  
  <p>When I tried to save the model</p>
  
  <pre class="lang-py prettyprint-override"><code>model.save('epic_num_reader.model')
  </code></pre>
  
  <p>I get a NotImplementedError:  </p>
  
  <pre><code>NotImplementedError                       Traceback (most recent call last)
  &lt;ipython-input-4-99efa4bdc06e&gt; in &lt;module&gt;()
        1 
  ----&gt; 2 model.save('epic_num_reader.model')
  
  NotImplementedError: Currently `save` requires model to be a graph network. Consider using `save_weights`, in order to save the weights of the model.
  </code></pre>
  
  <p>So how can I save the model defined in the code?</p>