title: Dictionary of tensors input for Keras Functional API TensorFlow 2.0
body: <p>I have a dataset of dictionary of tensors, and the following model defined using the  subclassing API:</p>
  
  <pre><code>class Model(tf.keras.Model):
  
    def __init__(self):
      super().__init__()
      self._movie_full_dense = tf.keras.layers.Dense(
          units=40, activation=tf.keras.layers.Activation("relu"))
      self._user_full_dense = tf.keras.layers.Dense(
          units=40, activation=tf.keras.layers.Activation("relu"))
      self._full_dense = tf.keras.layers.Dense(
          units=1, activation=tf.keras.layers.Activation("sigmoid"))
  
    def call(self, features):
      movie_embedding = self._movie_full_dense(features['movie'])
      user_embedding = self._user_full_dense(features['user'])
      combined = tf.concat([movie_embedding, user_embedding], 1)
      output = self._full_dense(combined)
      return output
  </code></pre>
  
  <p>I want to implement it using the functional API. but I do not know how to define the inputs? Namely, what is the functional equivalent for the following?</p>
  
  <pre><code>self._movie_full_dense(features['movie'])
  </code></pre>