title: BatchNormalization for some inputs only in Keras
body: <p>I have LSTM network that has 5 input. The 1st input typical values are from 1000 to 3000. Rest of inputs have values from -1 to 1.</p>
  
  <p>I'd like to insert BatchNormalization as the 1st layer. But inputs 2-5 are already between -1 and 1 and the 1st input is much greater than the 1st input. That's I'd like to apply batch normalization for the 1st input only and leave inputs 2-5 as is. Then 1st (normalized) input and  2-5 inputs should be passed to LSTM layer.</p>
  
  <pre><code>      +----+   +---+
   1 --&gt;| BN |--&gt;|   |
        +----+   | L |
   2 -----------&gt;| S |
   3 -----------&gt;| T |
   4 -----------&gt;| M | 
   5 -----------&gt;|   |
                 +---+
  </code></pre>
  
  <p>How can it be done in Keras?</p>
  
  <p>I think that I can create the model with BatchNormalization bare layer for the 1st input and then concatenate it with rest of layers. But I'm not sure and don't know how exactly do this.</p>