hi, nihao.
i have the same issues too. i trained the model a few step and torch.save the model to compare the parameters, and find the one not be updated(unused).
for example:
import torch
sd1 = torch.load("./work_dir/step_1.pth")["state_dict"]
sd4 = torch.load("./work_dir/step_5.pth")["state_dict"]
for k in sd1:
    v1 = sd1[k]
    v4 = sd4[k]
    if (v1==v4).all():
        print(k)