Method optimize_normal

improved_diffusion/train_util.py:244–249

(self)

        self.lg_loss_scale += self.fp16_scale_growth

    def optimize_normal(self):
        self._log_grad_norm()
        self._anneal_lr()
        self.opt.step()
        for rate, params in zip(self.ema_rate, self.ema_params):
            update_ema(params, self.master_params, rate=rate)

    def _log_grad_norm(self):
        sqsum = 0.0