Welcome and thanks for the question certainly a great one!
How come you are using tensor3d here? Maybe I am misunderstanding what you are trying to do, but if you just have a single post code and a single time of day as input to the model I would have expected it to be in the form of:
// 94701                        // evening
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0 ]

So the above would be a tensor1d which when sent as a batch to the model would be a tensor2d (can just call expandDims() to do that.
So as a batch you can do multiple predictions which would look like:
// Tensor2D
[
  [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0 ],
  [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0 ],
  [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0 ],
  [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0 ]
]

You do not need to normalize 1 hot encoded data here.
PS if you are just starting out you may be interested in my upcoming course for TensorFlow.js that covers some topics like this over on edX. Free to do if you do not need certification:

  
      

      edX
  

  
    

Google AI for JavaScript Developers with TensorFlow.js 1

  Get productive with TensorFlow.js - Google's Machine Learning library for JavaScript. From pre-made off the shelf models to writing or training your own, learn how to create next gen web apps.