Thank you for responding
In my set up I would like a set of linearities with a nonlinear but continuously differentiable activation function, so
layer 1: sigmoid(w_1^T x+b_1)
layer 2: softmax(w^T_2 y_1 +b_2)  etc. etc.
Am I doing this wrong in the code? Instead of nn.Linear should I use nn.sigmoid etc.?
And what should the F. function be in the forward pass for the linear part?
this is what I was going by, it is the only example of pytorch multilayer perceptron

  
    
    
    Getting started: Basic MLP example (my draft)? 
  
  
    Hi, I’ve gone through the PyTorch tutorials, and looked at a couple examples, and I’m still having trouble getting started – I’m just trying to make a basic MLP for now.   What I have below is my (existing) Keras version, and then an attempt at a PyTorch version, cobbled together from trying to read the docs and posts on this forum…still not finished because I’m not sure I’m doing this right. 
Can someone tell me if I’m on the right track? 
This MLP is intended to take, as input, a vector that’s…
  


thanks