soaska/my-sd
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rework sigma device mapping

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This commit is contained in:
lllyasviel 2024-02-07 00:44:12 -08:00
parent d11c9d7506
commit 257ac2653a
3 changed files with 11 additions and 11 deletions
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12
modules/sd_samplers_kdiffusion.py
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@ -144,12 +144,12 @@ 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(unet_patcher.load_device)
self.model_wrap.sigmas = self.model_wrap.sigmas.to(unet_patcher.load_device)
self.model_wrap.log_sigmas = self.model_wrap.log_sigmas.to(x.device)
self.model_wrap.sigmas = self.model_wrap.sigmas.to(x.device)
steps, t_enc = sd_samplers_common.setup_img2img_steps(p, steps)
sigmas = self.get_sigmas(p, steps).to(shared.device)
sigmas = self.get_sigmas(p, steps).to(x.device)
sigma_sched = sigmas[steps - t_enc - 1:]
x = x.to(noise)
@ -206,12 +206,12 @@ 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(unet_patcher.load_device)
self.model_wrap.sigmas = self.model_wrap.sigmas.to(unet_patcher.load_device)
self.model_wrap.log_sigmas = self.model_wrap.log_sigmas.to(x.device)
self.model_wrap.sigmas = self.model_wrap.sigmas.to(x.device)
steps = steps or p.steps
sigmas = self.get_sigmas(p, steps).to(shared.device)
sigmas = self.get_sigmas(p, steps).to(x.device)
if opts.sgm_noise_multiplier:
p.extra_generation_params["SGM noise multiplier"] = True

2
modules/sd_samplers_lcm.py
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@ -27,7 +27,7 @@ class LCMCompVisDenoiser(DiscreteEpsDDPMDenoiser):
start = self.sigma_to_t(self.sigma_max)
end = self.sigma_to_t(self.sigma_min)
t = torch.linspace(start, end, n, device=shared.sd_model.forge_objects.unet.current_device)
t = torch.linspace(start, end, n, device=self.sigmas.device)
return sampling.append_zero(self.t_to_sigma(t))

8
modules/sd_samplers_timesteps.py
View File

@ -101,11 +101,11 @@ class CompVisSampler(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.inner_model.alphas_cumprod = self.model_wrap.inner_model.alphas_cumprod.to(unet_patcher.load_device)
self.model_wrap.inner_model.alphas_cumprod = self.model_wrap.inner_model.alphas_cumprod.to(x.device)
steps, t_enc = sd_samplers_common.setup_img2img_steps(p, steps)
timesteps = self.get_timesteps(p, steps).to(shared.device)
timesteps = self.get_timesteps(p, steps).to(x.device)
timesteps_sched = timesteps[:t_enc]
alphas_cumprod = shared.sd_model.alphas_cumprod
@ -151,10 +151,10 @@ class CompVisSampler(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.inner_model.alphas_cumprod = self.model_wrap.inner_model.alphas_cumprod.to(unet_patcher.load_device)
self.model_wrap.inner_model.alphas_cumprod = self.model_wrap.inner_model.alphas_cumprod.to(x.device)
steps = steps or p.steps
timesteps = self.get_timesteps(p, steps).to(shared.device)
timesteps = self.get_timesteps(p, steps).to(x.device)
extra_params_kwargs = self.initialize(p)
parameters = inspect.signature(self.func).parameters