Mirrors
/
stable-diffusion-webui
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #14978 from drhead/refiner_fix 

Make refiner switchover based on model timesteps instead of sampling steps
This commit is contained in:
AUTOMATIC1111 2024-03-02 07:24:44 +03:00 committed by GitHub
parent f4cb21bb8a bf348032bc
commit aabedcbcc7
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
3 changed files with 14 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
modules/sd_samplers_cfg_denoiser.py
View File

@ -152,7 +152,7 @@ class CFGDenoiser(torch.nn.Module):
if state.interrupted or state.skipped:
raise sd_samplers_common.InterruptedException
if sd_samplers_common.apply_refiner(self):
if sd_samplers_common.apply_refiner(self, sigma):
cond = self.sampler.sampler_extra_args['cond']
uncond = self.sampler.sampler_extra_args['uncond']

13
modules/sd_samplers_common.py
View File

@ -155,8 +155,17 @@ def replace_torchsde_browinan():
replace_torchsde_browinan()
def apply_refiner(cfg_denoiser):
completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
def apply_refiner(cfg_denoiser, sigma):
if opts.refiner_switch_by_sample_steps:
completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
else:
# torch.max(sigma) only to handle rare case where we might have different sigmas in the same batch
try:
timestep = torch.argmin(torch.abs(cfg_denoiser.inner_model.sigmas - torch.max(sigma)))
except AttributeError: # for samplers that dont use sigmas (DDIM) sigma is actually the timestep
timestep = torch.max(sigma).to(dtype=int)
completed_ratio = (999 - timestep) / 1000
refiner_switch_at = cfg_denoiser.p.refiner_switch_at
refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info

3
modules/shared_options.py
View File

@ -227,7 +227,8 @@ options_templates.update(options_section(('compatibility', "Compatibility", "sd"
"dont_fix_second_order_samplers_schedule": OptionInfo(False, "Do not fix prompt schedule for second order samplers."),
"hires_fix_use_firstpass_conds": OptionInfo(False, "For hires fix, calculate conds of second pass using extra networks of first pass."),
"use_old_scheduling": OptionInfo(False, "Use old prompt editing timelines.", infotext="Old prompt editing timelines").info("For [red:green:N]; old: If N < 1, it's a fraction of steps (and hires fix uses range from 0 to 1), if N >= 1, it's an absolute number of steps; new: If N has a decimal point in it, it's a fraction of steps (and hires fix uses range from 1 to 2), othewrwise it's an absolute number of steps"),
"use_downcasted_alpha_bar": OptionInfo(False, "Downcast model alphas_cumprod to fp16 before sampling. For reproducing old seeds.", infotext="Downcast alphas_cumprod")
"use_downcasted_alpha_bar": OptionInfo(False, "Downcast model alphas_cumprod to fp16 before sampling. For reproducing old seeds.", infotext="Downcast alphas_cumprod"),
"refiner_switch_by_sample_steps": OptionInfo(False, "Switch to refiner by sampling steps instead of model timesteps. Old behavior for refiner.", infotext="Refiner switch by sampling steps")
}))
options_templates.update(options_section(('interrogate', "Interrogate"), {