Q:

Torch, why is my neural network producing only one output instead of many?

I implemented a siamese neural network in Torch, but I have a problem on the dimensionality of the output.
In a simple script, that I developed just for testing, it reads N elements in input and correctly generates N elements in output.
But in my main software, the almost identical model reads N elements in input and wrongly generates 1 element in output.
The only difference between the two models are the number of neurons, that should not influence the output dimensionality
Why is this happening?
In this image you can see a comparison between the structures of the two Torch siamese neural networks.

What might the mistake be?
How to detect it?
Any ideas?

A:

I think we got it in the chat thread.
I assume that you're running Torch7 on CentOS.  Torch7 requires CentOS 7.0 or later.  It installs on CentOS 6, but doesn't work correctly; I think it's the back-propagation that has a subtle failure.

