Exception on personalized

[burgalon]

Hey @catcathh Thank you for your great contribution!

When trying to run train_personalized.py - setup_optimizers() encounters an error params += list(models.train_lora.module.parameters()) needs to be fixed to params += list(models.train_lora.parameters())

Also if not running in DDP, need to fix backward_pass() and add:

    def backward_pass(self, update, loss_adjusted, models: Models, optimizers: TrainingCore.Optimizers, schedulers: Schedulers):

        if update:

            if self.config.use_ddp:
                torch.distributed.barrier()
            loss_adjusted.backward()

            grad_norm = nn.utils.clip_grad_norm_(models.train_lora.parameters(), 1.0)

Now it's failing on loading the lora... which I still didn't get around to fix

[catcathh]

Currently, the LoRA training code only supports multi-GPU setups. If you need to train on a single GPU, you might have to adjust parts of the code like model loading.