From 79ffb9453f8eddbdd4e316b9d9c75812b0eea4e1 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Fri, 10 Feb 2023 05:27:05 -0800 Subject: [PATCH] Add UniPC sampler settings --- modules/models/diffusion/uni_pc/sampler.py | 5 +++-- modules/models/diffusion/uni_pc/uni_pc.py | 2 +- modules/shared.py | 5 +++++ scripts/xyz_grid.py | 7 +++++++ 4 files changed, 16 insertions(+), 3 deletions(-) diff --git a/modules/models/diffusion/uni_pc/sampler.py b/modules/models/diffusion/uni_pc/sampler.py index 219e9862c..e66a21e3b 100644 --- a/modules/models/diffusion/uni_pc/sampler.py +++ b/modules/models/diffusion/uni_pc/sampler.py @@ -3,6 +3,7 @@ import torch from .uni_pc import NoiseScheduleVP, model_wrapper, UniPC +from modules import shared class UniPCSampler(object): def __init__(self, model, **kwargs): @@ -89,7 +90,7 @@ class UniPCSampler(object): guidance_scale=unconditional_guidance_scale, ) - uni_pc = UniPC(model_fn, ns, predict_x0=True, thresholding=False, condition=conditioning, unconditional_condition=unconditional_conditioning, before_sample=self.before_sample, after_sample=self.after_sample, after_update=self.after_update) - x = uni_pc.sample(img, steps=S, skip_type="time_uniform", method="multistep", order=3, lower_order_final=True) + uni_pc = UniPC(model_fn, ns, predict_x0=True, thresholding=shared.opts.uni_pc_thresholding, variant=shared.opts.uni_pc_variant, condition=conditioning, unconditional_condition=unconditional_conditioning, before_sample=self.before_sample, after_sample=self.after_sample, after_update=self.after_update) + x = uni_pc.sample(img, steps=S, skip_type=shared.opts.uni_pc_skip_type, method="multistep", order=shared.opts.uni_pc_order, lower_order_final=shared.opts.uni_pc_lower_order_final) return x.to(device), None diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index 31ee81a65..df63d1bcf 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -750,7 +750,7 @@ class UniPC: if method == 'multistep': assert steps >= order, "UniPC order must be < sampling steps" timesteps = self.get_time_steps(skip_type=skip_type, t_T=t_T, t_0=t_0, N=steps, device=device) - print(f"Running UniPC Sampling with {timesteps.shape[0]} timesteps") + print(f"Running UniPC Sampling with {timesteps.shape[0]} timesteps, order {order}") assert timesteps.shape[0] - 1 == steps with torch.no_grad(): vec_t = timesteps[0].expand((x.shape[0])) diff --git a/modules/shared.py b/modules/shared.py index 79fbf7249..342420739 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -480,6 +480,11 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"), + 'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "vary_coeff"]}), + 'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}), + 'uni_pc_order': OptionInfo(3, "UniPC order (must be < sampling steps)", gr.Slider, {"minimum": 1, "maximum": 150 - 1, "step": 1}), + 'uni_pc_thresholding': OptionInfo(False, "UniPC thresholding"), + 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final"), })) options_templates.update(options_section(('postprocessing', "Postprocessing"), { diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 5982cfbaa..72421e0ca 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -126,6 +126,10 @@ def apply_styles(p: StableDiffusionProcessingTxt2Img, x: str, _): p.styles.extend(x.split(',')) +def apply_uni_pc_order(p, x, xs): + opts.data["uni_pc_order"] = min(x, p.steps - 1) + + def format_value_add_label(p, opt, x): if type(x) == float: x = round(x, 8) @@ -202,6 +206,7 @@ axis_options = [ AxisOptionImg2Img("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight")), AxisOption("VAE", str, apply_vae, cost=0.7, choices=lambda: list(sd_vae.vae_dict)), AxisOption("Styles", str, apply_styles, choices=lambda: list(shared.prompt_styles.styles)), + AxisOption("UniPC Order", int, apply_uni_pc_order, cost=0.5), ] @@ -310,9 +315,11 @@ class SharedSettingsStackHelper(object): def __enter__(self): self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers self.vae = opts.sd_vae + self.uni_pc_order = opts.uni_pc_order def __exit__(self, exc_type, exc_value, tb): opts.data["sd_vae"] = self.vae + opts.data["uni_pc_order"] = self.uni_pc_order modules.sd_models.reload_model_weights() modules.sd_vae.reload_vae_weights()