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How I can implement a custom hidden and a regression output layer with 2 inputs?

Asked by Markus Wagner on 2 Jan 2019
Latest activity Commented on by Markus Wagner on 2 Jan 2019
I want bulid up with the deep learning toolbox (CNN, deppNrworkDesigner, layerGraph) a variational autoencoder for a sequence data input.
For this I need one custom layer with 2 inputs and a custom regression output layer in my networtk. But the documentation page "Define Custome Deep Learning Layers" just explain templates for layers with one input.
Howe i can adapt this templates for layers with more than one input and how i can use this layer in functions and apps (deepNetworkDesigner, trainNetwork, layerGraph-Functions etc.)?
i have Adapt the class of the Addition Layer, but it doesnt work well.

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1 Answer

Answer by Greg Heath
on 2 Jan 2019

Is that one input a scalar or a vector?
Hope this helps
**Thank you for formally accepting my answer**
Greg

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The input of the network is a vector. The inputs of the layer are vectors.

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