From 8de6d3ff77e841a5fd9d5f1b16bdd22737c8d657 Mon Sep 17 00:00:00 2001 From: lambertae Date: Tue, 25 Jul 2023 22:35:43 -0400 Subject: fix progress bar & torchHijack --- modules/sd_samplers_kdiffusion.py | 19 +++++++++++++------ 1 file changed, 13 insertions(+), 6 deletions(-) (limited to 'modules/sd_samplers_kdiffusion.py') diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index ed60670c..7a2427b5 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -79,19 +79,26 @@ def restart_sampler(model, x, sigmas, extra_args=None, callback=None, disable=No for key, value in restart_list.items(): temp_list[int(torch.argmin(abs(sigmas - key), dim=0))] = value restart_list = temp_list - for i in trange(len(sigmas) - 1, disable=disable): - x = heun_step(x, sigmas[i], sigmas[i+1]) + step_list = [] + for i in range(len(sigmas) - 1): + step_list.append((sigmas[i], sigmas[i + 1])) if i + 1 in restart_list: restart_steps, restart_times, restart_max = restart_list[i + 1] min_idx = i + 1 max_idx = int(torch.argmin(abs(sigmas - restart_max), dim=0)) 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: restart_times -= 1 - x = x + torch.randn_like(x) * s_noise * (sigmas[max_idx] ** 2 - sigmas[min_idx] ** 2) ** 0.5 - for (old_sigma, new_sigma) in zip(sigma_restart[:-1], sigma_restart[1:]): - x = heun_step(x, old_sigma, new_sigma) + step_list.extend([(old_sigma, new_sigma) for (old_sigma, new_sigma) in zip(sigma_restart[:-1], sigma_restart[1:])]) + last_sigma = None + 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 samplers_data_k_diffusion = [ -- cgit v1.2.1