I want to replace the parameters of a net with new parameters. e.g.
del net3.conv0.weight
net3.conv0.weight = net.conv0.weight + net2.conv0.weight

but I have the string name of the layer. Is that possible to be done?
I looked into self.convs = nn.ModuleList() but wasn’t sure if that was good or what was the best option…

Context:

  
    
    
    If we combine one trainable parameters with a non-trainable parameter, is the original trainable param trainable? 
  
  
    Say I have two nets and I combine their parameters in some fancy way using only pytorch operations. I store the result in a third net which has its parameters set to non-trainable. Then I proceed and pass data through this new net. The new net is just a place holder for 
placeholder_net.W = Op( not_trainable_net.W, trainable_net.W )

Then I pass data: 
output = placeholder_net(input)

I am concerned that since the params of the placeholder net are set to not trainable that it won’t actually trai…