title: Mixed one_hot and float input
body: <p>I am trying to train model of LSTM layers data of timeseries of categorical (one_hot) action(call/fold/raise) and time. 
  So example time series of 3 rounds where player 2x called and then folded.</p>
  
  <pre><code>  #Call  #0.5s    # Call    #0.3s   #Fold, 1.5s
  
  [[[1,0,0], 0.5], [[1,0,0], 0.3], [[0,1,0], 1.5]]
  </code></pre>
  
  <p>The categorical array of call/fold/raise cannot be processed by the first layer (LSTM) and I cannot use simple Embedding layer because of the non-categorical time. </p>
  
  <p>First layer - 
  model.add(LSTM(500, return_sequences=True, input_shape=(3, 2)))  </p>
  
  <p>I have tried to change the input_shape, but nothing worked for me. 
  Any ideas how to represent one_hot and float in once input?</p>