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experiment_mode=4 'rescale cfg' from that one paper

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Alex "mcmonkey" Goodwin
2023-05-22 07:20:30 -07:00
parent c9721ab01a
commit f02cacfc92
1 changed files with 13 additions and 0 deletions
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scripts/dynamic_thresholding.py
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@@ -154,6 +154,19 @@ class CustomCFGDenoiser(sd_samplers_kdiffusion.CFGDenoiser):
weights = torch.tensor(conds_list, device=uncond.device).select(2, 1) weights = torch.tensor(conds_list, device=uncond.device).select(2, 1)
weights = weights.reshape(*weights.shape, 1, 1, 1) weights = weights.reshape(*weights.shape, 1, 1, 1)
self.main_class.step = self.step self.main_class.step = self.step
if self.main_class.experiment_mode >= 4 and self.main_class.experiment_mode <= 5:
# https://arxiv.org/pdf/2305.08891.pdf "Rescale CFG". It's not good, but if you want to test it, just set experiment_mode = 4 + phi.
denoised = torch.clone(denoised_uncond)
fi = self.main_class.experiment_mode - 4.0
for i, conds in enumerate(conds_list):
for cond_index, weight in conds:
xcfg = (denoised_uncond[i] + (x_out[cond_index] - denoised_uncond[i]) * (cond_scale * weight))
xrescaled = xcfg * (torch.std(x_out[cond_index]) / torch.std(xcfg))
xfinal = fi * xrescaled + (1.0 - fi) * xcfg
denoised[i] = xfinal
return denoised
return self.main_class.dynthresh(x_out[:-uncond.shape[0]], denoised_uncond, cond_scale, weights) return self.main_class.dynthresh(x_out[:-uncond.shape[0]], denoised_uncond, cond_scale, weights)
######################### XYZ Plot Script Support logic ######################### ######################### XYZ Plot Script Support logic #########################