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-rw-r--r--modules/sd_models.py3
-rw-r--r--modules/sd_models_xl.py2
2 files changed, 3 insertions, 2 deletions
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 23660454..7ed89a9c 100644
--- a/modules/sd_models.py
+++ b/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
diff --git a/modules/sd_models_xl.py b/modules/sd_models_xl.py
index 01123321..11259a36 100644
--- a/modules/sd_models_xl.py
+++ b/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()