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infotext support for #14978

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AUTOMATIC1111
2024-03-02 07:39:59 +03:00
parent aabedcbcc7
commit bb24c13ed7
3 changed files with 11 additions and 3 deletions
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8
modules/sd_samplers_common.py
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@@ -155,14 +155,16 @@ def replace_torchsde_browinan():
replace_torchsde_browinan()
def apply_refiner(cfg_denoiser, sigma):
if opts.refiner_switch_by_sample_steps:
def apply_refiner(cfg_denoiser, sigma=None):
if opts.refiner_switch_by_sample_steps or not sigma:
completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
cfg_denoiser.p.extra_generation_params["Refiner switch by sampling steps"] = True
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
except AttributeError: # for samplers that don't use sigmas (DDIM) sigma is actually the timestep
timestep = torch.max(sigma).to(dtype=int)
completed_ratio = (999 - timestep) / 1000