title: Visualizing NN classification results using Keras and TensorBoard
body: <p>I am trying to visualize classification results from neural network in Keras using TensorBoard Embeddings. If I understand correctly, the Embeddings can be used to visualize any tensor (when TB is being used directly with TensorFlow), not just embedding layer (weights / output).
  The Keras TensorBoard callback lets me specify a layer to watch. When I set it to watch the output layer, then the only tensor available in TB is "kernel" (meaning weights?).
  <a href="https://i.stack.imgur.com/WaAvJ.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/WaAvJ.png" alt="enter image description here"></a>
  So I thought I could use TB directly instead, without the Keras wrapper, but I found no way to obtain the output tensor of Keras layer. 
  The only workaround I can think of would be to build the tensor (using TF variable) manually. Is this the only way? Or am I missing / misunderstanding something?</p>