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Implement zero terminal SNR schedule option

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drhead 2023-11-29 17:42:07 -05:00 committed by GitHub
parent 588a52891d
commit 6d0a8dcd89
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1 changed files with 28 additions and 0 deletions
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modules/processing.py
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@ -864,6 +864,34 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.n_iter > 1: if p.n_iter > 1:
shared.state.job = f"Batch {n+1} out of {p.n_iter}" shared.state.job = f"Batch {n+1} out of {p.n_iter}"
def rescale_zero_terminal_snr_abar(alphas_cumprod):
alphas_bar_sqrt = alphas_cumprod.sqrt()
# Store old values.
alphas_bar_sqrt_0 = alphas_bar_sqrt[0].clone()
alphas_bar_sqrt_T = alphas_bar_sqrt[-1].clone()
# Shift so the last timestep is zero.
alphas_bar_sqrt -= (alphas_bar_sqrt_T)
# Scale so the first timestep is back to the old value.
alphas_bar_sqrt *= alphas_bar_sqrt_0 / (alphas_bar_sqrt_0 - alphas_bar_sqrt_T)
# Convert alphas_bar_sqrt to betas
alphas_bar = alphas_bar_sqrt**2 # Revert sqrt
alphas_bar[-1] = 4.8973451890853435e-08
return alphas_bar
p.sd_model.alphas_cumprod = p.sd_model.alphas_cumprod_original.to(shared.device)
if opts.use_downcasted_alpha_bar:
p.extra_generation_params['Downcast alphas_cumprod'] = opts.use_downcasted_alpha_bar
p.sd_model.alphas_cumprod = p.sd_model.alphas_cumprod.half().to(shared.device)
if opts.sd_noise_schedule == "Zero Terminal SNR":
p.extra_generation_params['Noise Schedule'] = opts.sd_noise_schedule
print("rescaling noise schedule for zero snr")
p.sd_model.alphas_cumprod = rescale_zero_terminal_snr_abar(p.sd_model.alphas_cumprod).to(shared.device)
with devices.without_autocast() if devices.unet_needs_upcast else devices.autocast(): with devices.without_autocast() if devices.unet_needs_upcast else devices.autocast():
samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts) samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)