Method update_fixed_params

models/base_model.py:161–167

(self)

        self.old_lr = lr

    def update_fixed_params(self): # finetune all scales instead of just finest scale
        params = []
        for s in range(self.n_scales):
            params += list(getattr(self, 'netG'+str(s)).parameters())
        self.optimizer_G = torch.optim.Adam(params, lr=self.old_lr, betas=(self.opt.beta1, 0.999))
        self.finetune_all = True
        print('------------ Now finetuning all scales -----------')

    def update_training_batch(self, ratio): # increase number of backpropagated frames and number of frames in each GPU
        nfb = self.n_frames_bp