learning rate seems not properly be set when training with "self.args.resume == True"

[DSonDH]

for example of SCINet/experiments/exp_ETTh.py,

I think

        if self.args.resume:
            self.model, lr, epoch_start = load_model(self.model, path, model_name=self.args.data, horizon=self.args.horizon)
        else:
            epoch_start = 0

should be above line 227,

model_optim = self._select_optimizer()

and

self.args.lr = lr 

should be added above line 227.

The load_model() function brings last learning rate from loaded model successfully. But optimizer cannot set that learning rate for optimization because optimizer is called first. It seems optimizer only takes self.args.lr and it is not the value from the loaded model.

Best Regards,