[性能优化]vali部分将criterion的计算放在GPU上

[giansha]

去掉.detach().cpu(),将criterion的计算放在GPU上：
原始：

 def vali(self, vali_data, vali_loader, criterion):

    total_loss = []
    self.model.eval()
    with torch.no_grad():
        for i, (batch_x, _) in enumerate(vali_loader):
            batch_x = batch_x.float().to(self.device)

            outputs = self.model(batch_x, None, None, None)

            f_dim = -1 if self.args.features == 'MS' else 0
            outputs = outputs[:, :, f_dim:]
            pred = outputs.detach().cpu()
            true = batch_x.detach().cpu()

            loss = criterion(pred, true)
            total_loss.append(loss)
    total_loss = np.average(total_loss)
    self.model.train()
    return total_loss

改为：

 def vali(self, vali_data, vali_loader, criterion):

           .....
            pred = outputs
            true = batch_x

            loss = criterion(pred, true)
            total_loss.append(loss.cpu())
    total_loss = np.average(total_loss)
    self.model.train()
    return total_loss

[wuhaixu2016]

感谢这个宝贵的建议，您可以提一个pull request，我们来merge～