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fix progress bar & torchHijack

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lambertae 2023-07-25 22:35:43 -04:00
parent f873890298
commit 8de6d3ff77
1 changed files with 13 additions and 6 deletions
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19
modules/sd_samplers_kdiffusion.py
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@ -79,19 +79,26 @@ def restart_sampler(model, x, sigmas, extra_args=None, callback=None, disable=No
for key, value in restart_list.items(): for key, value in restart_list.items():
temp_list[int(torch.argmin(abs(sigmas - key), dim=0))] = value temp_list[int(torch.argmin(abs(sigmas - key), dim=0))] = value
restart_list = temp_list restart_list = temp_list
for i in trange(len(sigmas) - 1, disable=disable): step_list = []
x = heun_step(x, sigmas[i], sigmas[i+1]) for i in range(len(sigmas) - 1):
step_list.append((sigmas[i], sigmas[i + 1]))
if i + 1 in restart_list: if i + 1 in restart_list:
restart_steps, restart_times, restart_max = restart_list[i + 1] restart_steps, restart_times, restart_max = restart_list[i + 1]
min_idx = i + 1 min_idx = i + 1
max_idx = int(torch.argmin(abs(sigmas - restart_max), dim=0)) max_idx = int(torch.argmin(abs(sigmas - restart_max), dim=0))
if max_idx < min_idx: if max_idx < min_idx:
sigma_restart = get_sigmas_karras(restart_steps, sigmas[min_idx].item(), sigmas[max_idx].item(), device=sigmas.device)[:-1] # remove the zero at the end sigma_restart = get_sigmas_karras(restart_steps, sigmas[min_idx].item(), sigmas[max_idx].item(), device=sigmas.device)[:-1]
while restart_times > 0: while restart_times > 0:
restart_times -= 1 restart_times -= 1
x = x + torch.randn_like(x) * s_noise * (sigmas[max_idx] ** 2 - sigmas[min_idx] ** 2) ** 0.5 step_list.extend([(old_sigma, new_sigma) for (old_sigma, new_sigma) in zip(sigma_restart[:-1], sigma_restart[1:])])
for (old_sigma, new_sigma) in zip(sigma_restart[:-1], sigma_restart[1:]): last_sigma = None
x = heun_step(x, old_sigma, new_sigma) for i in trange(len(step_list), disable=disable):
if last_sigma is None:
last_sigma = step_list[i][0]
elif last_sigma < step_list[i][0]:
x = x + k_diffusion.sampling.torch.randn_like(x) * s_noise * (step_list[i][0] ** 2 - last_sigma ** 2) ** 0.5
x = heun_step(x, step_list[i][0], step_list[i][1])
last_sigma = step_list[i][1]
return x return x
samplers_data_k_diffusion = [ samplers_data_k_diffusion = [