Ensure the cached weight will not be affected

        for module in model.modules():

            if isinstance(module, (torch.nn.Conv2d, torch.nn.Linear)):

                if shared.opts.cache_fp16_weight:

                    module.fp16_weight = module.weight.clone().half()

                    module.fp16_weight = module.weight.data.clone().cpu().half()

                    if module.bias is not None:

                        module.fp16_bias = module.bias.clone().half()

                        module.fp16_bias = module.bias.data.clone().cpu().half()

                module.to(torch.float8_e4m3fn)

        model.first_stage_model = first_stage

        timer.record("apply fp8")