Method on_after_optimization

utils/commons/base_task.py:169–171

(self, epoch, batch_idx, optimizer, optimizer_idx)

            torch.nn.utils.clip_grad_value_(self.parameters(), self.gradient_clip_val)

    def on_after_optimization(self, epoch, batch_idx, optimizer, optimizer_idx):
        if self.scheduler is not None:
            self.scheduler.step(self.global_step // hparams['accumulate_grad_batches'])

    ######################
    # validation