Non-trainable parameters?

[hovinen]

I would like to set up a network in which all of the parameters of one of the linear layers are hard-coded and do not change through training. In other libraries such as PyTorch, one can do this by clearing flag requires_grad on the parameters one wishes to hold fixed. I can't find any equivalent in the dfdx documentation, nor any mention of the terms "non-trainable" or similar.

Does dfdx support this at all? If so, how does one set this up?

[swfsql]

I'm not entirely sure, but I believe you can create a wrapper structure that defines how the forward_mut method behaves (assuming you want to implement a Module), and in that method when using the linear layers that you intend to not train, instead of calling their forward_mut methods you'd call the forward instead. But I'm not sure how you'd need to go about the Tapes on the inputs data, maybe it can be kept the same.