Method optimizer_step

usr/task.py:78–84

(self, epoch, batch_idx, optimizer, optimizer_idx)

        return torch.optim.lr_scheduler.StepLR(optimizer, hparams['decay_steps'], gamma=0.5)

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