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 train the variable that it should train. Will this happen? Or what is the result when you combine a trainable param with and non trainable param (and then set that where the param is not trainable)?


  
      stackoverflow.com
  
  
      
    
  

  If we combine one trainable parameters with a non-trainable parameter, is the original trainable param trainable? 6



  python, machine-learning, neural-network, conv-neural-network



  asked by
  
  
    Charlie Parker
  
  on 10:44PM - 02 May 18