lllyasviel/stable-diffusion-webui-forge
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link k-diffusion to backend

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layerdiffusion
2024-08-07 18:44:53 -07:00
parent 69b1827ed5
commit 5591b701c1
2 changed files with 38 additions and 8 deletions
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11
modules/sd_samplers_kdiffusion.py
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@@ -56,10 +56,7 @@ class CFGDenoiserKDiffusion(sd_samplers_cfg_denoiser.CFGDenoiser):
@property
def inner_model(self):
if self.model_wrap is None:
self.model_wrap = k_diffusion.external.DiscreteSchedule(
sigmas=shared.sd_model.forge_objects.unet.model.predictor.sigmas,
quantize=shared.opts.enable_quantization
)
self.model_wrap = k_diffusion.external.ForgeScheduleLinker(shared.sd_model.forge_objects.unet.model.predictor)
self.model_wrap.inner_model = shared.sd_model
return self.model_wrap
@@ -136,8 +133,7 @@ class KDiffusionSampler(sd_samplers_common.Sampler):
unet_patcher = self.model_wrap.inner_model.forge_objects.unet
sampling_prepare(self.model_wrap.inner_model.forge_objects.unet, x=x)
self.model_wrap.log_sigmas = self.model_wrap.log_sigmas.to(x.device)
self.model_wrap.sigmas = self.model_wrap.sigmas.to(x.device)
self.model_wrap.predictor.to(x.device)
steps, t_enc = sd_samplers_common.setup_img2img_steps(p, steps)
@@ -198,8 +194,7 @@ class KDiffusionSampler(sd_samplers_common.Sampler):
unet_patcher = self.model_wrap.inner_model.forge_objects.unet
sampling_prepare(self.model_wrap.inner_model.forge_objects.unet, x=x)
self.model_wrap.log_sigmas = self.model_wrap.log_sigmas.to(x.device)
self.model_wrap.sigmas = self.model_wrap.sigmas.to(x.device)
self.model_wrap.predictor.to(x.device)
steps = steps or p.steps