Skip/freeze/omit learnable parameters

autograd
1

Hello community,

in order to freeze some parameter I could set the feature param.requires_grad to False. However my question is about optimizer, for example:

optimizer = torch.optim.Adam([
    {'params': model.feature_extractor.parameters()},
    {'params': model.covar_module.parameters()},
    {'params': model.mean_module.parameters()},
], lr=0.01)

If I leave out my model parameters in the optimizer definition and leaved out parameters are not set to param.requires_grad = False, will these parameters be changed?

Thank a lot!