Fix alphas cumprod

modules/sd_models.py

@@ -396,6 +396,8 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
         enable_fp8 = True
     elif model.is_sdxl and shared.cmd_opts.opt_unet_fp8_storage_xl:
         enable_fp8 = True
+    else:
+        enable_fp8 = False
 
     if enable_fp8:
         devices.fp8 = True
@@ -416,7 +418,6 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
                     module.to(torch.float8_e4m3fn)
             model.model.diffusion_model = model.model.diffusion_model.to(torch.float8_e4m3fn)
             timer.record("apply fp8 unet")
-        model.alphas_cumprod = model.alphas_cumprod.to(torch.float32)
 
     devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16
 

modules/sd_models_xl.py

@@ -93,7 +93,7 @@ def extend_sdxl(model):
     model.parameterization = "v" if isinstance(model.denoiser.scaling, sgm.modules.diffusionmodules.denoiser_scaling.VScaling) else "eps"
 
     discretization = sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization()
-    model.alphas_cumprod = torch.asarray(discretization.alphas_cumprod, device=devices.device, dtype=dtype)
+    model.alphas_cumprod = torch.asarray(discretization.alphas_cumprod, device=devices.device, dtype=torch.float32)
 
     model.conditioner.wrapped = torch.nn.Module()