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-rw-r--r--modules/sd_models.py20
1 files changed, 16 insertions, 4 deletions
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 08af128f..c5fe57bf 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -391,12 +391,24 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
devices.dtype_unet = torch.float16
timer.record("apply half()")
- if shared.cmd_opts.opt_unet_fp8_storage:
+
+ if shared.cmd_opts.opt_unet_fp8_storage:
+ enable_fp8 = True
+ elif model.is_sdxl and shared.cmd_opts.opt_unet_fp8_storage_xl:
+ enable_fp8 = True
+
+ if enable_fp8:
+ devices.fp8 = True
+ if devices.device == devices.cpu:
+ for module in model.model.diffusion_model.modules():
+ if isinstance(module, torch.nn.Conv2d):
+ module.to(torch.float8_e4m3fn)
+ elif isinstance(module, torch.nn.Linear):
+ module.to(torch.float8_e4m3fn)
+ timer.record("apply fp8 unet for cpu")
+ else:
model.model.diffusion_model = model.model.diffusion_model.to(torch.float8_e4m3fn)
timer.record("apply fp8 unet")
- elif model.is_sdxl and shared.cmd_opts.opt_unet_fp8_storage_xl:
- model.model.diffusion_model = model.model.diffusion_model.to(torch.float8_e4m3fn)
- timer.record("apply fp8 unet for sdxl")
devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16