A simple question, but what does Keras Concatenate actually do?. If I have two input layers with size 200 each and pass them through a concat layer what has actually happened? Does it just mean the output of the concatenated layer is treated as a single layer of size 400? When is concat useful?
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Just as you described, the layer is treated as a single layer of size 400. See here.
It's useful for a variety of different structures. Here is an example of it being used in a Keras implementation of BiGAN. (Line 105).
Related: You are more likely to see it in architectures that are not simple sequences of layers. Check out the Functional API Guide, which has many examples of concatenate in action.
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