title: Sequentialmodels without `input_shape` passed to the 1st layer cannot reload optimizer state
body: <p>WARNING:tensorflow:Sequential models without an <code>input_shape</code> passed to the first layer cannot reload their optimizer state. As a result, your model is starting with a freshly initialized optimizer.</p>
  
  <p>while trying to load a saved model i encountered this warning from tensorflow</p>
  
  <pre><code>import tensorflow.keras as keras
  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)
  
  model.save('epic_num_reader.model')
  new_model = tf.keras.models.load_model('epic_num_reader.model')
  predictions = new_model.predict(x_test)
  </code></pre>