title: How to add scalar value into latent variables in auto-encoder with keras
body: <p>I've tried to input a specific scalar value(0 to 1; each image has) into a layer of latent variables.
  How to insert the value in CNN based auto-encoder sequential model?</p>
  <pre><code>def encoder():
      model = tf.keras.Sequential()
      model.add(Conv2D(12, (2,2), activation='relu', padding='same', input_shape=(32, 32, 1)))
      model.add(MaxPooling2D(pool_size=(2, 2), padding='same'))
      model.add(Flatten())
      model.add(Dense(64))
      return model
  
  # maybe some code here
  
  def decoder():
      model = tf.keras.Sequential()
      model.add(Dense(16*16*12, input_shape=(65,)))
      model.add(Reshape((16,16,12)))
      model.add(Conv2D(32, (2, 2), activation='relu', padding='same'))
      model.add(UpSampling2D((2, 2)))
      model.add(Dropout(0.5))
      model.add(Conv2D(1, (2, 2), padding='same'))
      return model
  </code></pre>
  <p>The number of latent variables is 64 in encoder, therefore, a scalar variable should make 65 latent variables in decoder.
  Concatenate layer could be applied?</p>