Hello,
I would like to add to an existing model, like AlexNet, additional layers.
My custom layer only changes the activation values, and does not affect any dimension.
My layer includes a 2D convolution but with constant weights (I set requires_grad=False).
The thing is that I’m having a hard time loading the pretrained values.
I’m looking at model.state_dict() and I can see that my layer affects the state_dict, in contrast to pooling or ReLU that doesn’t appear in it.
How do I force my layer to not change the original state_dict (like pooling or activation functions)?
Thanks.