Is it possible use FINN to make predictions without TopK as the last layer?

[bieelpaiao]

Hello everyone, I'm trying to build a CNN for classification with FINN which takes a 64x64x1 input image and returns an output with the probabilities of 4 classes. I saw the notebook examples for multi-class classification and all of them uses a TopK layer in the output but I really need the predictions for each class so TopK will not work for me.

I made a build without TopK and generated an stitched IP to use in Vivado, but now I am confused about what specifically the numbers in output represent.

The sample that I have simulated expects the following output considering streamlined model and execute.onnx function in Python:
[[30.37711 33.0512 81.76213 -8.510721]]

And the values outputed in Vivado are:
6157 6699 16572 -1725

Anyone knows the relation between these numbers? How can I verify if values in Vivado are close to the expected in Python?