From 125319988984987801dc4b4ab1e5ed36e9b211c5 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Fri, 10 Feb 2023 03:30:20 -0800 Subject: Working UniPC (for batch size 1) --- modules/sd_samplers_compvis.py | 35 ++++++++++++++++++++++++++++++----- 1 file changed, 30 insertions(+), 5 deletions(-) (limited to 'modules/sd_samplers_compvis.py') diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index d03131cd..86fa1c5b 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -7,19 +7,27 @@ import torch from modules.shared import state from modules import sd_samplers_common, prompt_parser, shared +import modules.models.diffusion.uni_pc samplers_data_compvis = [ sd_samplers_common.SamplerData('DDIM', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.ddim.DDIMSampler, model), [], {}), sd_samplers_common.SamplerData('PLMS', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.plms.PLMSSampler, model), [], {}), + sd_samplers_common.SamplerData('UniPC', lambda model: VanillaStableDiffusionSampler(modules.models.diffusion.uni_pc.UniPCSampler, model), [], {}), ] class VanillaStableDiffusionSampler: def __init__(self, constructor, sd_model): self.sampler = constructor(sd_model) + self.is_ddim = hasattr(self.sampler, 'p_sample_ddim') self.is_plms = hasattr(self.sampler, 'p_sample_plms') - self.orig_p_sample_ddim = self.sampler.p_sample_plms if self.is_plms else self.sampler.p_sample_ddim + self.is_unipc = isinstance(self.sampler, modules.models.diffusion.uni_pc.UniPCSampler) + self.orig_p_sample_ddim = None + if self.is_plms: + self.orig_p_sample_ddim = self.sampler.p_sample_plms + elif self.is_ddim: + self.orig_p_sample_ddim = self.sampler.p_sample_ddim self.mask = None self.nmask = None self.init_latent = None @@ -45,6 +53,15 @@ class VanillaStableDiffusionSampler: return self.last_latent def p_sample_ddim_hook(self, x_dec, cond, ts, unconditional_conditioning, *args, **kwargs): + x_dec, ts, cond, unconditional_conditioning = self.before_sample(x_dec, ts, cond, unconditional_conditioning) + + res = self.orig_p_sample_ddim(x_dec, cond, ts, unconditional_conditioning=unconditional_conditioning, *args, **kwargs) + + x_dec, ts, cond, unconditional_conditioning, res = self.after_sample(x_dec, ts, cond, unconditional_conditioning, res) + + return res + + def before_sample(self, x, ts, cond, unconditional_conditioning): if state.interrupted or state.skipped: raise sd_samplers_common.InterruptedException @@ -76,7 +93,7 @@ class VanillaStableDiffusionSampler: if self.mask is not None: img_orig = self.sampler.model.q_sample(self.init_latent, ts) - x_dec = img_orig * self.mask + self.nmask * x_dec + x = img_orig * self.mask + self.nmask * x # Wrap the image conditioning back up since the DDIM code can accept the dict directly. # Note that they need to be lists because it just concatenates them later. @@ -84,7 +101,13 @@ class VanillaStableDiffusionSampler: cond = {"c_concat": [image_conditioning], "c_crossattn": [cond]} unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]} - res = self.orig_p_sample_ddim(x_dec, cond, ts, unconditional_conditioning=unconditional_conditioning, *args, **kwargs) + return x, ts, cond, unconditional_conditioning + + def after_sample(self, x, ts, cond, uncond, res): + if self.is_unipc: + # unipc model_fn returns (pred_x0) + # p_sample_ddim returns (x_prev, pred_x0) + res = (None, res[0]) if self.mask is not None: self.last_latent = self.init_latent * self.mask + self.nmask * res[1] @@ -97,7 +120,7 @@ class VanillaStableDiffusionSampler: state.sampling_step = self.step shared.total_tqdm.update() - return res + return x, ts, cond, uncond, res def initialize(self, p): self.eta = p.eta if p.eta is not None else shared.opts.eta_ddim @@ -107,12 +130,14 @@ class VanillaStableDiffusionSampler: for fieldname in ['p_sample_ddim', 'p_sample_plms']: if hasattr(self.sampler, fieldname): setattr(self.sampler, fieldname, self.p_sample_ddim_hook) + if self.is_unipc: + self.sampler.set_hooks(lambda x, t, c, u: self.before_sample(x, t, c, u), lambda x, t, c, u, r: self.after_sample(x, t, c, u, r)) self.mask = p.mask if hasattr(p, 'mask') else None self.nmask = p.nmask if hasattr(p, 'nmask') else None def adjust_steps_if_invalid(self, p, num_steps): - if (self.config.name == 'DDIM' and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS'): + if ((self.config.name == 'DDIM' or self.config.name == "UniPC") and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS'): valid_step = 999 / (1000 // num_steps) if valid_step == math.floor(valid_step): return int(valid_step) + 1 -- cgit v1.2.3 From 21880eb9e57b884635a07d2360831b4186afddf4 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Fri, 10 Feb 2023 04:47:08 -0800 Subject: Fix logspam and live previews --- modules/models/diffusion/uni_pc/sampler.py | 20 ++++++++++++++----- modules/models/diffusion/uni_pc/uni_pc.py | 32 ++++++++++++++---------------- modules/sd_samplers_compvis.py | 20 ++++++++++--------- 3 files changed, 41 insertions(+), 31 deletions(-) (limited to 'modules/sd_samplers_compvis.py') diff --git a/modules/models/diffusion/uni_pc/sampler.py b/modules/models/diffusion/uni_pc/sampler.py index 7cccd8a2..219e9862 100644 --- a/modules/models/diffusion/uni_pc/sampler.py +++ b/modules/models/diffusion/uni_pc/sampler.py @@ -19,9 +19,10 @@ class UniPCSampler(object): attr = attr.to(torch.device("cuda")) setattr(self, name, attr) - def set_hooks(self, before, after): - self.before_sample = before - self.after_sample = after + def set_hooks(self, before_sample, after_sample, after_update): + self.before_sample = before_sample + self.after_sample = after_sample + self.after_update = after_update @torch.no_grad() def sample(self, @@ -50,9 +51,17 @@ class UniPCSampler(object): ): if conditioning is not None: if isinstance(conditioning, dict): - cbs = conditioning[list(conditioning.keys())[0]].shape[0] + ctmp = conditioning[list(conditioning.keys())[0]] + while isinstance(ctmp, list): ctmp = ctmp[0] + cbs = ctmp.shape[0] if cbs != batch_size: print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}") + + elif isinstance(conditioning, list): + for ctmp in conditioning: + if ctmp.shape[0] != batch_size: + print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}") + else: if conditioning.shape[0] != batch_size: print(f"Warning: Got {conditioning.shape[0]} conditionings but batch-size is {batch_size}") @@ -60,6 +69,7 @@ class UniPCSampler(object): # sampling C, H, W = shape size = (batch_size, C, H, W) + print(f'Data shape for UniPC sampling is {size}, eta {eta}') device = self.model.betas.device if x_T is None: @@ -79,7 +89,7 @@ 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) + 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) 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 ec6b37da..31ee81a6 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -378,7 +378,8 @@ class UniPC: condition=None, unconditional_condition=None, before_sample=None, - after_sample=None + after_sample=None, + after_update=None ): """Construct a UniPC. @@ -394,6 +395,7 @@ class UniPC: self.unconditional_condition = unconditional_condition self.before_sample = before_sample self.after_sample = after_sample + self.after_update = after_update def dynamic_thresholding_fn(self, x0, t=None): """ @@ -434,15 +436,6 @@ class UniPC: noise = self.noise_prediction_fn(x, t) dims = x.dim() alpha_t, sigma_t = self.noise_schedule.marginal_alpha(t), self.noise_schedule.marginal_std(t) - from pprint import pp - print("X:") - pp(x) - print("sigma_t:") - pp(sigma_t) - print("noise:") - pp(noise) - print("alpha_t:") - pp(alpha_t) x0 = (x - expand_dims(sigma_t, dims) * noise) / expand_dims(alpha_t, dims) if self.thresholding: p = 0.995 # A hyperparameter in the paper of "Imagen" [1]. @@ -524,7 +517,7 @@ class UniPC: return self.multistep_uni_pc_vary_update(x, model_prev_list, t_prev_list, t, order, **kwargs) def multistep_uni_pc_vary_update(self, x, model_prev_list, t_prev_list, t, order, use_corrector=True): - print(f'using unified predictor-corrector with order {order} (solver type: vary coeff)') + #print(f'using unified predictor-corrector with order {order} (solver type: vary coeff)') ns = self.noise_schedule assert order <= len(model_prev_list) @@ -568,7 +561,7 @@ class UniPC: A_p = C_inv_p if use_corrector: - print('using corrector') + #print('using corrector') C_inv = torch.linalg.inv(C) A_c = C_inv @@ -627,7 +620,7 @@ class UniPC: return x_t, model_t def multistep_uni_pc_bh_update(self, x, model_prev_list, t_prev_list, t, order, x_t=None, use_corrector=True): - print(f'using unified predictor-corrector with order {order} (solver type: B(h))') + #print(f'using unified predictor-corrector with order {order} (solver type: B(h))') ns = self.noise_schedule assert order <= len(model_prev_list) dims = x.dim() @@ -695,7 +688,7 @@ class UniPC: D1s = None if use_corrector: - print('using corrector') + #print('using corrector') # for order 1, we use a simplified version if order == 1: rhos_c = torch.tensor([0.5], device=b.device) @@ -755,8 +748,9 @@ class UniPC: t_T = self.noise_schedule.T if t_start is None else t_start device = x.device if method == 'multistep': - assert steps >= order + 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") assert timesteps.shape[0] - 1 == steps with torch.no_grad(): vec_t = timesteps[0].expand((x.shape[0])) @@ -768,6 +762,8 @@ class UniPC: x, model_x = self.multistep_uni_pc_update(x, model_prev_list, t_prev_list, vec_t, init_order, use_corrector=True) if model_x is None: model_x = self.model_fn(x, vec_t) + if self.after_update is not None: + self.after_update(x, model_x) model_prev_list.append(model_x) t_prev_list.append(vec_t) for step in range(order, steps + 1): @@ -776,13 +772,15 @@ class UniPC: step_order = min(order, steps + 1 - step) else: step_order = order - print('this step order:', step_order) + #print('this step order:', step_order) if step == steps: - print('do not run corrector at the last step') + #print('do not run corrector at the last step') use_corrector = False else: use_corrector = True x, model_x = self.multistep_uni_pc_update(x, model_prev_list, t_prev_list, vec_t, step_order, use_corrector=use_corrector) + if self.after_update is not None: + self.after_update(x, model_x) for i in range(order - 1): t_prev_list[i] = t_prev_list[i + 1] model_prev_list[i] = model_prev_list[i + 1] diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index 86fa1c5b..946079ae 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -103,16 +103,11 @@ class VanillaStableDiffusionSampler: return x, ts, cond, unconditional_conditioning - def after_sample(self, x, ts, cond, uncond, res): - if self.is_unipc: - # unipc model_fn returns (pred_x0) - # p_sample_ddim returns (x_prev, pred_x0) - res = (None, res[0]) - + def update_step(self, last_latent): if self.mask is not None: - self.last_latent = self.init_latent * self.mask + self.nmask * res[1] + self.last_latent = self.init_latent * self.mask + self.nmask * last_latent else: - self.last_latent = res[1] + self.last_latent = last_latent sd_samplers_common.store_latent(self.last_latent) @@ -120,8 +115,15 @@ class VanillaStableDiffusionSampler: state.sampling_step = self.step shared.total_tqdm.update() + def after_sample(self, x, ts, cond, uncond, res): + if not self.is_unipc: + self.update_step(res[1]) + return x, ts, cond, uncond, res + def unipc_after_update(self, x, model_x): + self.update_step(x) + def initialize(self, p): self.eta = p.eta if p.eta is not None else shared.opts.eta_ddim if self.eta != 0.0: @@ -131,7 +133,7 @@ class VanillaStableDiffusionSampler: if hasattr(self.sampler, fieldname): setattr(self.sampler, fieldname, self.p_sample_ddim_hook) if self.is_unipc: - self.sampler.set_hooks(lambda x, t, c, u: self.before_sample(x, t, c, u), lambda x, t, c, u, r: self.after_sample(x, t, c, u, r)) + self.sampler.set_hooks(lambda x, t, c, u: self.before_sample(x, t, c, u), lambda x, t, c, u, r: self.after_sample(x, t, c, u, r), lambda x, mx: self.unipc_after_update(x, mx)) self.mask = p.mask if hasattr(p, 'mask') else None self.nmask = p.nmask if hasattr(p, 'nmask') else None -- cgit v1.2.3 From c88dcc20d495dab4be2692bdff30277112dbe416 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Fri, 10 Feb 2023 05:00:09 -0800 Subject: UniPC does not support img2img (for now) --- modules/processing.py | 2 +- modules/sd_samplers.py | 2 +- modules/sd_samplers_compvis.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) (limited to 'modules/sd_samplers_compvis.py') diff --git a/modules/processing.py b/modules/processing.py index 11e726df..b7cf5357 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -884,7 +884,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): shared.state.nextjob() - img2img_sampler_name = 'DDIM' # PLMS does not support img2img so we just silently switch ot DDIM + img2img_sampler_name = 'DDIM' # PLMS/UniPC does not support img2img so we just silently switch ot DDIM self.sampler = sd_samplers.create_sampler(img2img_sampler_name, self.sd_model) samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2] diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 28c2136f..ff361f22 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -32,7 +32,7 @@ def set_samplers(): global samplers, samplers_for_img2img hidden = set(shared.opts.hide_samplers) - hidden_img2img = set(shared.opts.hide_samplers + ['PLMS']) + hidden_img2img = set(shared.opts.hide_samplers + ['PLMS', 'UniPC']) samplers = [x for x in all_samplers if x.name not in hidden] samplers_for_img2img = [x for x in all_samplers if x.name not in hidden_img2img] diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index 946079ae..ad39ab2b 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -139,7 +139,7 @@ class VanillaStableDiffusionSampler: self.nmask = p.nmask if hasattr(p, 'nmask') else None def adjust_steps_if_invalid(self, p, num_steps): - if ((self.config.name == 'DDIM' or self.config.name == "UniPC") and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS'): + if ((self.config.name == 'DDIM') and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS') or (self.config.name == 'UniPC'): valid_step = 999 / (1000 // num_steps) if valid_step == math.floor(valid_step): return int(valid_step) + 1 -- cgit v1.2.3 From 5fef67f6ee949a61826a3a043ea8610fd89fc371 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Fri, 10 Mar 2023 19:56:14 -0500 Subject: Requested changes --- modules/models/diffusion/uni_pc/sampler.py | 2 +- modules/sd_samplers_compvis.py | 4 +++- modules/shared.py | 3 +-- 3 files changed, 5 insertions(+), 4 deletions(-) (limited to 'modules/sd_samplers_compvis.py') diff --git a/modules/models/diffusion/uni_pc/sampler.py b/modules/models/diffusion/uni_pc/sampler.py index 708a9b2b..6bb3bb21 100644 --- a/modules/models/diffusion/uni_pc/sampler.py +++ b/modules/models/diffusion/uni_pc/sampler.py @@ -93,7 +93,7 @@ class UniPCSampler(object): guidance_scale=unconditional_guidance_scale, ) - 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) + uni_pc = UniPC(model_fn, ns, predict_x0=True, thresholding=False, 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/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index ad39ab2b..7d07c4a5 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -140,10 +140,12 @@ class VanillaStableDiffusionSampler: def adjust_steps_if_invalid(self, p, num_steps): if ((self.config.name == 'DDIM') and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS') or (self.config.name == 'UniPC'): + if self.config.name == 'UniPC' and num_steps < shared.opts.uni_pc_order: + num_steps = shared.opts.uni_pc_order valid_step = 999 / (1000 // num_steps) if valid_step == math.floor(valid_step): return int(valid_step) + 1 - + return num_steps def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning, steps=None, image_conditioning=None): diff --git a/modules/shared.py b/modules/shared.py index 7c559fa4..29f8dccb 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -485,10 +485,9 @@ 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_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "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": 50, "step": 1}), - 'uni_pc_thresholding': OptionInfo(False, "UniPC thresholding"), 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final"), })) -- cgit v1.2.3 From 58b5b7c2f1d3b843803c1fc7a0aae8b1d6be5763 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 11 Mar 2023 12:09:36 +0300 Subject: add UniPC options to infotext --- modules/generation_parameters_copypaste.py | 8 +++++++- modules/sd_samplers_compvis.py | 14 ++++++++++++++ modules/shared.py | 9 +++++++++ 3 files changed, 30 insertions(+), 1 deletion(-) (limited to 'modules/sd_samplers_compvis.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 89dc23bf..cb367655 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -288,6 +288,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model settings_map = {} + + infotext_to_setting_name_mapping = [ ('Clip skip', 'CLIP_stop_at_last_layers', ), ('Conditional mask weight', 'inpainting_mask_weight'), @@ -296,7 +298,11 @@ infotext_to_setting_name_mapping = [ ('Noise multiplier', 'initial_noise_multiplier'), ('Eta', 'eta_ancestral'), ('Eta DDIM', 'eta_ddim'), - ('Discard penultimate sigma', 'always_discard_next_to_last_sigma') + ('Discard penultimate sigma', 'always_discard_next_to_last_sigma'), + ('UniPC variant', 'uni_pc_variant'), + ('UniPC skip type', 'uni_pc_skip_type'), + ('UniPC order', 'uni_pc_order'), + ('UniPC lower order final', 'uni_pc_lower_order_final'), ] diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index 7d07c4a5..083da18c 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -129,6 +129,19 @@ class VanillaStableDiffusionSampler: if self.eta != 0.0: p.extra_generation_params["Eta DDIM"] = self.eta + if self.is_unipc: + keys = [ + ('UniPC variant', 'uni_pc_variant'), + ('UniPC skip type', 'uni_pc_skip_type'), + ('UniPC order', 'uni_pc_order'), + ('UniPC lower order final', 'uni_pc_lower_order_final'), + ] + + for name, key in keys: + v = getattr(shared.opts, key) + if v != shared.opts.get_default(key): + p.extra_generation_params[name] = v + for fieldname in ['p_sample_ddim', 'p_sample_plms']: if hasattr(self.sampler, fieldname): setattr(self.sampler, fieldname, self.p_sample_ddim_hook) @@ -138,6 +151,7 @@ class VanillaStableDiffusionSampler: self.mask = p.mask if hasattr(p, 'mask') else None self.nmask = p.nmask if hasattr(p, 'nmask') else None + def adjust_steps_if_invalid(self, p, num_steps): if ((self.config.name == 'DDIM') and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS') or (self.config.name == 'UniPC'): if self.config.name == 'UniPC' and num_steps < shared.opts.uni_pc_order: diff --git a/modules/shared.py b/modules/shared.py index 29f8dccb..d481c25b 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -563,6 +563,15 @@ class Options: return True + def get_default(self, key): + """returns the default value for the key""" + + data_label = self.data_labels.get(key) + if data_label is None: + return None + + return data_label.default + def save(self, filename): assert not cmd_opts.freeze_settings, "saving settings is disabled" -- cgit v1.2.3