title: Why do the outputs sum to 1 in the TensorFlow Get started with Eager tutorial?
body: <p>I did this tutorial: <a href="https://www.tensorflow.org/get_started/eager" rel="nofollow noreferrer">https://www.tensorflow.org/get_started/eager</a></p>
  
  <p>It was very helpful, but I didn't understand why the outputs always sum to 1. It is stated "For this example, the sum of the output predictions are 1.0", but not explained. I thought it might be a characteristic of the activation function, but I read ReLu can take any value >0 (<a href="https://medium.com/the-theory-of-everything/understanding-activation-functions-in-neural-networks-9491262884e0" rel="nofollow noreferrer">https://medium.com/the-theory-of-everything/understanding-activation-functions-in-neural-networks-9491262884e0</a>).</p>
  
  <p>I'd like to understand because I want to learn in which cases one should normalize the output variables and in which cases this is not necessary (I assume if they always sum up to 1, it's not necessary).</p>