title: How to set the input of a Keras layer with a Tensorflow tensor?
body: <p>In my <a href="https://stackoverflow.com/questions/41672114/add-tensorflow-pre-processing-to-existing-keras-model-for-use-in-tensorflow-ser">previous question</a>, I used Keras' <code>Layer.set_input()</code> to connect my Tensorflow pre-processing output tensor to my Keras model's input. However, <a href="https://github.com/fchollet/keras/commit/92e8a20761bedbde8fd56a02a165884e8132f045" rel="noreferrer">this method has been removed</a> after Keras version <code>1.1.1</code>.</p>
  
  <p>How can I achieve this in newer Keras versions?</p>
  
  <p><strong>Example:</strong></p>
  
  <pre><code># Tensorflow pre-processing
  raw_input = tf.placeholder(tf.string)
  ### some TF operations on raw_input ###
  tf_embedding_input = ...    # pre-processing output tensor
  
  # Keras model
  model = Sequential()
  e = Embedding(max_features, 128, input_length=maxlen)
  
  ### THIS DOESN'T WORK ANYMORE ###
  e.set_input(tf_embedding_input)
  ################################
  
  model.add(e)
  model.add(LSTM(128, activation='sigmoid'))
  model.add(Dense(num_classes, activation='softmax'))
  </code></pre>