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revise math

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This commit is contained in:
lllyasviel 2023-10-22 12:09:24 -07:00
parent 6f3fa4b670
commit 43bc2df328
3 changed files with 6 additions and 6 deletions
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2
fooocus_version.py
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@ -1 +1 @@
version = '2.1.730' version = '2.1.731'

6
modules/core.py
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@ -218,7 +218,7 @@ def get_previewer(model):
def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='dpmpp_2m_sde_gpu', def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='dpmpp_2m_sde_gpu',
scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None, scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
force_full_denoise=False, callback_function=None, refiner=None, refiner_switch=-1, force_full_denoise=False, callback_function=None, refiner=None, refiner_switch=-1,
previewer_start=None, previewer_end=None, sigmas=None, noise_offset=None): previewer_start=None, previewer_end=None, sigmas=None, noise_mean=None):
if sigmas is not None: if sigmas is not None:
sigmas = sigmas.clone().to(fcbh.model_management.get_torch_device()) sigmas = sigmas.clone().to(fcbh.model_management.get_torch_device())
@ -231,8 +231,8 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
batch_inds = latent["batch_index"] if "batch_index" in latent else None batch_inds = latent["batch_index"] if "batch_index" in latent else None
noise = fcbh.sample.prepare_noise(latent_image, seed, batch_inds) noise = fcbh.sample.prepare_noise(latent_image, seed, batch_inds)
if isinstance(noise_offset, torch.Tensor): if isinstance(noise_mean, torch.Tensor):
noise = noise + noise_offset noise = noise + noise_mean - torch.mean(noise, dim=1, keepdim=True)
noise_mask = None noise_mask = None
if "noise_mask" in latent: if "noise_mask" in latent:

4
modules/default_pipeline.py
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@ -468,7 +468,7 @@ def process_diffusion(positive_cond, negative_cond, steps, switch, width, height
denoise=denoise)[switch:] * k_sigmas denoise=denoise)[switch:] * k_sigmas
len_sigmas = len(sigmas) - 1 len_sigmas = len(sigmas) - 1
noise_offset = torch.mean(modules.patch.eps_record, dim=1, keepdim=True) * 0.9 noise_mean = torch.mean(modules.patch.eps_record, dim=1, keepdim=True)
if modules.inpaint_worker.current_task is not None: if modules.inpaint_worker.current_task is not None:
modules.inpaint_worker.current_task.swap() modules.inpaint_worker.current_task.swap()
@ -488,7 +488,7 @@ def process_diffusion(positive_cond, negative_cond, steps, switch, width, height
previewer_start=switch, previewer_start=switch,
previewer_end=steps, previewer_end=steps,
sigmas=sigmas, sigmas=sigmas,
noise_offset=noise_offset noise_mean=noise_mean
) )
target_model = final_refiner_vae target_model = final_refiner_vae