Hey i have notice that
If i do
            print(self.local_model.state_dict())
            print("total_loss.backward()",total_loss)
            total_loss.backward()
            opt_2 = torch.optim.SGD(self.local_model.parameters(),lr = 0.01)
            opt_2.step()
            self.opt.step()
            print(self.local_model.state_dict())

Then it show weight change.
But i want to update weights using loss of global_model.
I am using local_model to predict the result
then i want to apply grad to global model
A3C stuff
Do you know how to ?