From 1846ad36a3bd2a60bc9dc59a60e16d3ca7a559fe Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Tue, 23 May 2023 10:58:57 +0800 Subject: Use settings instead of main interface --- modules/generation_parameters_copypaste.py | 5 +++++ 1 file changed, 5 insertions(+) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index d5f0a49b..c92fb0fb 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -318,6 +318,11 @@ infotext_to_setting_name_mapping = [ ('Conditional mask weight', 'inpainting_mask_weight'), ('Model hash', 'sd_model_checkpoint'), ('ENSD', 'eta_noise_seed_delta'), + ('Enable Custom KDiffusion Schedule', 'custom_k_sched'), + ('KDiffusion Scheduler Type', 'k_sched_type'), + ('KDiffusion Scheduler sigma_max', 'sigma_max'), + ('KDiffusion Scheduler sigma_min', 'sigma_min'), + ('KDiffusion Scheduler rho', 'rho'), ('Noise multiplier', 'initial_noise_multiplier'), ('Eta', 'eta_ancestral'), ('Eta DDIM', 'eta_ddim'), -- cgit v1.2.3 From 72377b02518f96051a01a7e0ea30a6a14d8ec1de Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Tue, 23 May 2023 23:48:23 +0800 Subject: Use type to determine if it is enable --- modules/generation_parameters_copypaste.py | 1 - modules/sd_samplers_kdiffusion.py | 6 +++--- modules/shared.py | 3 +-- 3 files changed, 4 insertions(+), 6 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index c92fb0fb..e98866fc 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -318,7 +318,6 @@ infotext_to_setting_name_mapping = [ ('Conditional mask weight', 'inpainting_mask_weight'), ('Model hash', 'sd_model_checkpoint'), ('ENSD', 'eta_noise_seed_delta'), - ('Enable Custom KDiffusion Schedule', 'custom_k_sched'), ('KDiffusion Scheduler Type', 'k_sched_type'), ('KDiffusion Scheduler sigma_max', 'sigma_max'), ('KDiffusion Scheduler sigma_min', 'sigma_min'), diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 5fea08b0..eff2e32d 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -46,6 +46,7 @@ sampler_extra_params = { k_diffusion_samplers_map = {x.name: x for x in samplers_data_k_diffusion} k_diffusion_scheduler = { + 'None': None, 'karras': k_diffusion.sampling.get_sigmas_karras, 'exponential': k_diffusion.sampling.get_sigmas_exponential, 'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential @@ -295,8 +296,7 @@ class KDiffusionSampler: k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else []) - if opts.custom_k_sched: - p.extra_generation_params["Enable Custom KDiffusion Schedule"] = True + if opts.k_sched_type != "None": p.extra_generation_params["KDiffusion Scheduler Type"] = opts.k_sched_type p.extra_generation_params["KDiffusion Scheduler sigma_max"] = opts.sigma_max p.extra_generation_params["KDiffusion Scheduler sigma_min"] = opts.sigma_min @@ -325,7 +325,7 @@ class KDiffusionSampler: if p.sampler_noise_scheduler_override: sigmas = p.sampler_noise_scheduler_override(steps) - elif opts.custom_k_sched: + elif opts.k_sched_type != "None": sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item()) sigmas_func = k_diffusion_scheduler[opts.k_sched_type] sigmas_kwargs = { diff --git a/modules/shared.py b/modules/shared.py index a0e762d2..b24f52dd 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -517,8 +517,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - 'custom_k_sched': OptionInfo(False, "Enable Custom KDiffusion Scheduler"), - 'k_sched_type': OptionInfo("karras", "scheduler type", gr.Dropdown, {"choices": ["karras", "exponential", "polyexponential"]}), + 'k_sched_type': OptionInfo("default", "scheduler type", gr.Dropdown, {"choices": ["None", "karras", "exponential", "polyexponential"]}), 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number).info("the maximum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), 'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("the minimum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), 'rho': OptionInfo(7.0, "rho", gr.Number).info("higher will make a more steep noise scheduler (decrease faster). default for karras is 7.0, for polyexponential is 1.0"), -- cgit v1.2.3 From 4b88e24ebe776680b327e33fe96d7fcf38e2e5d2 Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Wed, 24 May 2023 20:35:58 +0800 Subject: improvements See: https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/10649#issuecomment-1561047723 --- modules/generation_parameters_copypaste.py | 20 ++++++++++++++++---- modules/sd_samplers_kdiffusion.py | 27 +++++++++++++++++---------- modules/shared.py | 4 ++-- scripts/xyz_grid.py | 8 ++++---- 4 files changed, 39 insertions(+), 20 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index e98866fc..4f827a6f 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -306,6 +306,18 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if "RNG" not in res: res["RNG"] = "GPU" + if "KDiff Sched Type" not in res: + res["KDiff Sched Type"] = "Automatic" + + if "KDiff Sched max sigma" not in res: + res["KDiff Sched max sigma"] = 14.6 + + if "KDiff Sched min sigma" not in res: + res["KDiff Sched min sigma"] = 0.3 + + if "KDiff Sched rho" not in res: + res["KDiff Sched rho"] = 7.0 + return res @@ -318,10 +330,10 @@ infotext_to_setting_name_mapping = [ ('Conditional mask weight', 'inpainting_mask_weight'), ('Model hash', 'sd_model_checkpoint'), ('ENSD', 'eta_noise_seed_delta'), - ('KDiffusion Scheduler Type', 'k_sched_type'), - ('KDiffusion Scheduler sigma_max', 'sigma_max'), - ('KDiffusion Scheduler sigma_min', 'sigma_min'), - ('KDiffusion Scheduler rho', 'rho'), + ('KDiff Sched Type', 'k_sched_type'), + ('KDiff Sched max sigma', 'sigma_max'), + ('KDiff Sched min sigma', 'sigma_min'), + ('KDiff Sched rho', 'rho'), ('Noise multiplier', 'initial_noise_multiplier'), ('Eta', 'eta_ancestral'), ('Eta DDIM', 'eta_ddim'), diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index a4c797c6..d2d172e4 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -296,12 +296,6 @@ class KDiffusionSampler: k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else []) - if opts.k_sched_type != "Automatic": - p.extra_generation_params["KDiffusion Scheduler Type"] = opts.k_sched_type - p.extra_generation_params["KDiffusion Scheduler sigma_max"] = opts.sigma_max - p.extra_generation_params["KDiffusion Scheduler sigma_min"] = opts.sigma_min - p.extra_generation_params["KDiffusion Scheduler rho"] = opts.rho - extra_params_kwargs = {} for param_name in self.extra_params: if hasattr(p, param_name) and param_name in inspect.signature(self.func).parameters: @@ -326,14 +320,27 @@ class KDiffusionSampler: if p.sampler_noise_scheduler_override: sigmas = p.sampler_noise_scheduler_override(steps) elif opts.k_sched_type != "Automatic": - sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item()) - sigmas_func = k_diffusion_scheduler[opts.k_sched_type] + m_sigma_min, m_sigma_max = (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item()) + sigma_min, sigma_max = (0.1, 10) sigmas_kwargs = { - 'sigma_min': opts.sigma_min or sigma_min, - 'sigma_max': opts.sigma_max or sigma_max + 'sigma_min': sigma_min if opts.use_old_karras_scheduler_sigmas else m_sigma_min, + 'sigma_max': sigma_max if opts.use_old_karras_scheduler_sigmas else m_sigma_max } + + sigmas_func = k_diffusion_scheduler[opts.k_sched_type] + p.extra_generation_params["KDiff Sched Type"] = opts.k_sched_type + + if opts.sigma_min != 0.3: + # take 0.0 as model default + sigmas_kwargs['sigma_min'] = opts.sigma_min or m_sigma_min + p.extra_generation_params["KDiff Sched min sigma"] = opts.sigma_min + if opts.sigma_max != 14.6: + sigmas_kwargs['sigma_max'] = opts.sigma_max or m_sigma_max + p.extra_generation_params["KDiff Sched max sigma"] = opts.sigma_max if opts.k_sched_type != 'exponential': sigmas_kwargs['rho'] = opts.rho + p.extra_generation_params["KDiff Sched rho"] = opts.rho + sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device) elif self.config is not None and self.config.options.get('scheduler', None) == 'karras': sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item()) diff --git a/modules/shared.py b/modules/shared.py index da7f7cfb..00fcced8 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -518,8 +518,8 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 'k_sched_type': OptionInfo("Automatic", "scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}), - 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number).info("the maximum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), - 'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("the minimum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), + 'sigma_max': OptionInfo(14.6, "sigma max", gr.Number).info("the maximum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), + 'sigma_min': OptionInfo(0.3, "sigma min", gr.Number).info("the minimum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), 'rho': OptionInfo(7.0, "rho", gr.Number).info("higher will make a more steep noise scheduler (decrease faster). default for karras is 7.0, for polyexponential is 1.0"), 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma").link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"), diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index a4126e78..41fc2107 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -220,10 +220,10 @@ axis_options = [ AxisOption("Sigma min", float, apply_field("s_tmin")), AxisOption("Sigma max", float, apply_field("s_tmax")), AxisOption("Sigma noise", float, apply_field("s_noise")), - AxisOption("KDiffusion Scheduler Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)), - AxisOption("KDiffusion Scheduler Sigma Min", float, apply_override("sigma_min")), - AxisOption("KDiffusion Scheduler Sigma Max", float, apply_override("sigma_max")), - AxisOption("KDiffusion Scheduler rho", float, apply_override("rho")), + AxisOption("KDiff Sched Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)), + AxisOption("KDiff Sched min sigma", float, apply_override("sigma_min")), + AxisOption("KDiff Sched max sigma", float, apply_override("sigma_max")), + AxisOption("KDiff Sched rho", float, apply_override("rho")), AxisOption("Eta", float, apply_field("eta")), AxisOption("Clip skip", int, apply_clip_skip), AxisOption("Denoising", float, apply_field("denoising_strength")), -- cgit v1.2.3 From a69b71a37f1fd32a60fbd87beed13f4f280400bd Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Wed, 24 May 2023 20:40:37 +0800 Subject: use Schedule instead of Sched --- modules/generation_parameters_copypaste.py | 24 ++++++++++++------------ modules/sd_samplers_kdiffusion.py | 8 ++++---- scripts/xyz_grid.py | 8 ++++---- 3 files changed, 20 insertions(+), 20 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 4f827a6f..1443c5cd 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -306,17 +306,17 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if "RNG" not in res: res["RNG"] = "GPU" - if "KDiff Sched Type" not in res: - res["KDiff Sched Type"] = "Automatic" + if "KDiff Schedule Type" not in res: + res["KDiff Schedule Type"] = "Automatic" - if "KDiff Sched max sigma" not in res: - res["KDiff Sched max sigma"] = 14.6 + if "KDiff Schedule max sigma" not in res: + res["KDiff Schedule max sigma"] = 14.6 - if "KDiff Sched min sigma" not in res: - res["KDiff Sched min sigma"] = 0.3 + if "KDiff Schedule min sigma" not in res: + res["KDiff Schedule min sigma"] = 0.3 - if "KDiff Sched rho" not in res: - res["KDiff Sched rho"] = 7.0 + if "KDiff Schedule rho" not in res: + res["KDiff Schedule rho"] = 7.0 return res @@ -330,10 +330,10 @@ infotext_to_setting_name_mapping = [ ('Conditional mask weight', 'inpainting_mask_weight'), ('Model hash', 'sd_model_checkpoint'), ('ENSD', 'eta_noise_seed_delta'), - ('KDiff Sched Type', 'k_sched_type'), - ('KDiff Sched max sigma', 'sigma_max'), - ('KDiff Sched min sigma', 'sigma_min'), - ('KDiff Sched rho', 'rho'), + ('KDiff Schedule Type', 'k_sched_type'), + ('KDiff Schedule max sigma', 'sigma_max'), + ('KDiff Schedule min sigma', 'sigma_min'), + ('KDiff Schedule rho', 'rho'), ('Noise multiplier', 'initial_noise_multiplier'), ('Eta', 'eta_ancestral'), ('Eta DDIM', 'eta_ddim'), diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index d2d172e4..9c9d9f17 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -328,18 +328,18 @@ class KDiffusionSampler: } sigmas_func = k_diffusion_scheduler[opts.k_sched_type] - p.extra_generation_params["KDiff Sched Type"] = opts.k_sched_type + p.extra_generation_params["KDiff Schedule Type"] = opts.k_sched_type if opts.sigma_min != 0.3: # take 0.0 as model default sigmas_kwargs['sigma_min'] = opts.sigma_min or m_sigma_min - p.extra_generation_params["KDiff Sched min sigma"] = opts.sigma_min + p.extra_generation_params["KDiff Schedule min sigma"] = opts.sigma_min if opts.sigma_max != 14.6: sigmas_kwargs['sigma_max'] = opts.sigma_max or m_sigma_max - p.extra_generation_params["KDiff Sched max sigma"] = opts.sigma_max + p.extra_generation_params["KDiff Schedule max sigma"] = opts.sigma_max if opts.k_sched_type != 'exponential': sigmas_kwargs['rho'] = opts.rho - p.extra_generation_params["KDiff Sched rho"] = opts.rho + p.extra_generation_params["KDiff Schedule rho"] = opts.rho sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device) elif self.config is not None and self.config.options.get('scheduler', None) == 'karras': diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 41fc2107..089d375e 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -220,10 +220,10 @@ axis_options = [ AxisOption("Sigma min", float, apply_field("s_tmin")), AxisOption("Sigma max", float, apply_field("s_tmax")), AxisOption("Sigma noise", float, apply_field("s_noise")), - AxisOption("KDiff Sched Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)), - AxisOption("KDiff Sched min sigma", float, apply_override("sigma_min")), - AxisOption("KDiff Sched max sigma", float, apply_override("sigma_max")), - AxisOption("KDiff Sched rho", float, apply_override("rho")), + AxisOption("KDiff Schedule Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)), + AxisOption("KDiff Schedule min sigma", float, apply_override("sigma_min")), + AxisOption("KDiff Schedule max sigma", float, apply_override("sigma_max")), + AxisOption("KDiff Schedule rho", float, apply_override("rho")), AxisOption("Eta", float, apply_field("eta")), AxisOption("Clip skip", int, apply_clip_skip), AxisOption("Denoising", float, apply_field("denoising_strength")), -- cgit v1.2.3 From e8e7fe11e903115a706187f8301df2e06fa018f8 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 27 May 2023 19:53:09 +0300 Subject: updates for the noise schedule settings --- modules/generation_parameters_copypaste.py | 24 ++++++++++++------------ modules/sd_samplers_kdiffusion.py | 30 ++++++++++++++++-------------- modules/shared.py | 8 ++++---- scripts/xyz_grid.py | 8 ++++---- 4 files changed, 36 insertions(+), 34 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 1443c5cd..81aef502 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -306,17 +306,17 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if "RNG" not in res: res["RNG"] = "GPU" - if "KDiff Schedule Type" not in res: - res["KDiff Schedule Type"] = "Automatic" + if "Schedule type" not in res: + res["Schedule type"] = "Automatic" - if "KDiff Schedule max sigma" not in res: - res["KDiff Schedule max sigma"] = 14.6 + if "Schedule max sigma" not in res: + res["Schedule max sigma"] = 0 - if "KDiff Schedule min sigma" not in res: - res["KDiff Schedule min sigma"] = 0.3 + if "Schedule min sigma" not in res: + res["Schedule min sigma"] = 0 - if "KDiff Schedule rho" not in res: - res["KDiff Schedule rho"] = 7.0 + if "Schedule rho" not in res: + res["Schedule rho"] = 0 return res @@ -330,10 +330,10 @@ infotext_to_setting_name_mapping = [ ('Conditional mask weight', 'inpainting_mask_weight'), ('Model hash', 'sd_model_checkpoint'), ('ENSD', 'eta_noise_seed_delta'), - ('KDiff Schedule Type', 'k_sched_type'), - ('KDiff Schedule max sigma', 'sigma_max'), - ('KDiff Schedule min sigma', 'sigma_min'), - ('KDiff Schedule rho', 'rho'), + ('Schedule type', 'k_sched_type'), + ('Schedule max sigma', 'sigma_max'), + ('Schedule min sigma', 'sigma_min'), + ('Schedule rho', 'rho'), ('Noise multiplier', 'initial_noise_multiplier'), ('Eta', 'eta_ancestral'), ('Eta DDIM', 'eta_ddim'), diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 9c9d9f17..e9ba2c61 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -321,25 +321,27 @@ class KDiffusionSampler: sigmas = p.sampler_noise_scheduler_override(steps) elif opts.k_sched_type != "Automatic": m_sigma_min, m_sigma_max = (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item()) - sigma_min, sigma_max = (0.1, 10) + sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (m_sigma_min, m_sigma_max) sigmas_kwargs = { - 'sigma_min': sigma_min if opts.use_old_karras_scheduler_sigmas else m_sigma_min, - 'sigma_max': sigma_max if opts.use_old_karras_scheduler_sigmas else m_sigma_max + 'sigma_min': sigma_min, + 'sigma_max': sigma_max, } sigmas_func = k_diffusion_scheduler[opts.k_sched_type] - p.extra_generation_params["KDiff Schedule Type"] = opts.k_sched_type - - if opts.sigma_min != 0.3: - # take 0.0 as model default - sigmas_kwargs['sigma_min'] = opts.sigma_min or m_sigma_min - p.extra_generation_params["KDiff Schedule min sigma"] = opts.sigma_min - if opts.sigma_max != 14.6: - sigmas_kwargs['sigma_max'] = opts.sigma_max or m_sigma_max - p.extra_generation_params["KDiff Schedule max sigma"] = opts.sigma_max - if opts.k_sched_type != 'exponential': + p.extra_generation_params["Schedule type"] = opts.k_sched_type + + if opts.sigma_min != m_sigma_min and opts.sigma_min != 0: + sigmas_kwargs['sigma_min'] = opts.sigma_min + p.extra_generation_params["Schedule min sigma"] = opts.sigma_min + if opts.sigma_max != m_sigma_max and opts.sigma_max != 0: + sigmas_kwargs['sigma_max'] = opts.sigma_max + p.extra_generation_params["Schedule max sigma"] = opts.sigma_max + + default_rho = 1. if opts.k_sched_type == "polyexponential" else 7. + + if opts.k_sched_type != 'exponential' and opts.rho != 0 and opts.rho != default_rho: sigmas_kwargs['rho'] = opts.rho - p.extra_generation_params["KDiff Schedule rho"] = opts.rho + p.extra_generation_params["Schedule rho"] = opts.rho sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device) elif self.config is not None and self.config.options.get('scheduler', None) == 'karras': diff --git a/modules/shared.py b/modules/shared.py index 364a5991..daab38dc 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -518,10 +518,10 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - 'k_sched_type': OptionInfo("Automatic", "scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}), - 'sigma_max': OptionInfo(14.6, "sigma max", gr.Number).info("the maximum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), - 'sigma_min': OptionInfo(0.3, "sigma min", gr.Number).info("the minimum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), - 'rho': OptionInfo(7.0, "rho", gr.Number).info("higher will make a more steep noise scheduler (decrease faster). default for karras is 7.0, for polyexponential is 1.0"), + 'k_sched_type': OptionInfo("Automatic", "scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}).info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"), + 'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"), + 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number).info("0 = default (~14.6); maximum noise strength for k-diffusion noise schedule"), + 'rho': OptionInfo(0.0, "rho", gr.Number).info("0 = default (7 for karras, 1 for polyexponential); higher values result in a more steep noise schedule (decreases faster)"), 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma").link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"), 'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "vary_coeff"]}), diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 089d375e..7821cc65 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -220,10 +220,10 @@ axis_options = [ AxisOption("Sigma min", float, apply_field("s_tmin")), AxisOption("Sigma max", float, apply_field("s_tmax")), AxisOption("Sigma noise", float, apply_field("s_noise")), - AxisOption("KDiff Schedule Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)), - AxisOption("KDiff Schedule min sigma", float, apply_override("sigma_min")), - AxisOption("KDiff Schedule max sigma", float, apply_override("sigma_max")), - AxisOption("KDiff Schedule rho", float, apply_override("rho")), + AxisOption("Schedule type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)), + AxisOption("Schedule min sigma", float, apply_override("sigma_min")), + AxisOption("Schedule max sigma", float, apply_override("sigma_max")), + AxisOption("Schedule rho", float, apply_override("rho")), AxisOption("Eta", float, apply_field("eta")), AxisOption("Clip skip", int, apply_clip_skip), AxisOption("Denoising", float, apply_field("denoising_strength")), -- cgit v1.2.3 From b957dcfece29c84ac0cfcd5a69475ff8684c531f Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 28 May 2023 10:39:57 +0300 Subject: add quoting for infotext values that have a colon in them --- modules/generation_parameters_copypaste.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 81aef502..071bd9ea 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -35,7 +35,7 @@ def reset(): def quote(text): - if ',' not in str(text) and '\n' not in str(text): + if ',' not in str(text) and '\n' not in str(text) and ':' not in str(text): return text return json.dumps(text, ensure_ascii=False) -- cgit v1.2.3 From 51864790fd72386fbbbb015d24a43ce501ecaa4b Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Fri, 2 Jun 2023 14:58:10 +0300 Subject: Simplify a bunch of `len(x) > 0`/`len(x) == 0` style expressions --- extensions-builtin/LDSR/sd_hijack_autoencoder.py | 3 ++- extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 4 ++-- extensions-builtin/Lora/extra_networks_lora.py | 4 ++-- extensions-builtin/Lora/lora.py | 4 ++-- .../extra-options-section/scripts/extra_options_section.py | 2 +- modules/api/api.py | 2 +- modules/call_queue.py | 2 +- modules/extra_networks_hypernet.py | 4 ++-- modules/generation_parameters_copypaste.py | 6 ++---- modules/images.py | 6 +++--- modules/img2img.py | 3 +-- modules/models/diffusion/ddpm_edit.py | 4 ++-- modules/processing.py | 3 ++- modules/prompt_parser.py | 6 +++--- modules/script_callbacks.py | 4 ++-- modules/sd_hijack_clip.py | 2 +- modules/sd_hijack_clip_old.py | 2 +- modules/textual_inversion/autocrop.py | 14 +++++++------- modules/textual_inversion/dataset.py | 2 +- modules/textual_inversion/preprocess.py | 4 ++-- modules/textual_inversion/textual_inversion.py | 2 +- modules/ui.py | 2 +- modules/ui_extensions.py | 5 +++-- modules/ui_settings.py | 2 +- scripts/prompts_from_file.py | 3 +-- 25 files changed, 47 insertions(+), 48 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py index 27a86e13..c29d274d 100644 --- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py +++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py @@ -91,8 +91,9 @@ class VQModel(pl.LightningModule): del sd[k] missing, unexpected = self.load_state_dict(sd, strict=False) print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys") - if len(missing) > 0: + if missing: print(f"Missing Keys: {missing}") + if unexpected: print(f"Unexpected Keys: {unexpected}") def on_train_batch_end(self, *args, **kwargs): diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py index 631a08ef..04adc5eb 100644 --- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py +++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py @@ -195,9 +195,9 @@ class DDPMV1(pl.LightningModule): missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict( sd, strict=False) print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys") - if len(missing) > 0: + if missing: print(f"Missing Keys: {missing}") - if len(unexpected) > 0: + if unexpected: print(f"Unexpected Keys: {unexpected}") def q_mean_variance(self, x_start, t): diff --git a/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py index b5fea4d2..66ee9c85 100644 --- a/extensions-builtin/Lora/extra_networks_lora.py +++ b/extensions-builtin/Lora/extra_networks_lora.py @@ -9,14 +9,14 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork): def activate(self, p, params_list): additional = shared.opts.sd_lora - if additional != "None" and additional in lora.available_loras and len([x for x in params_list if x.items[0] == additional]) == 0: + if additional != "None" and additional in lora.available_loras and not any(x for x in params_list if x.items[0] == additional): p.all_prompts = [x + f"" for x in p.all_prompts] params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier])) names = [] multipliers = [] for params in params_list: - assert len(params.items) > 0 + assert params.items names.append(params.items[0]) multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0) diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index eec14712..af93991c 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -219,7 +219,7 @@ def load_lora(name, lora_on_disk): else: raise AssertionError(f"Bad Lora layer name: {key_diffusers} - must end in lora_up.weight, lora_down.weight or alpha") - if len(keys_failed_to_match) > 0: + if keys_failed_to_match: print(f"Failed to match keys when loading Lora {lora_on_disk.filename}: {keys_failed_to_match}") return lora @@ -267,7 +267,7 @@ def load_loras(names, multipliers=None): lora.multiplier = multipliers[i] if multipliers else 1.0 loaded_loras.append(lora) - if len(failed_to_load_loras) > 0: + if failed_to_load_loras: sd_hijack.model_hijack.comments.append("Failed to find Loras: " + ", ".join(failed_to_load_loras)) diff --git a/extensions-builtin/extra-options-section/scripts/extra_options_section.py b/extensions-builtin/extra-options-section/scripts/extra_options_section.py index 17f84184..a05e10d8 100644 --- a/extensions-builtin/extra-options-section/scripts/extra_options_section.py +++ b/extensions-builtin/extra-options-section/scripts/extra_options_section.py @@ -21,7 +21,7 @@ class ExtraOptionsSection(scripts.Script): self.setting_names = [] with gr.Blocks() as interface: - with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and len(shared.opts.extra_options) > 0 else gr.Group(), gr.Row(): + with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and shared.opts.extra_options else gr.Group(), gr.Row(): for setting_name in shared.opts.extra_options: with FormColumn(): comp = ui_settings.create_setting_component(setting_name) diff --git a/modules/api/api.py b/modules/api/api.py index d34ab422..555eefdb 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -280,7 +280,7 @@ class Api: script_args[0] = selectable_idx + 1 # Now check for always on scripts - if request.alwayson_scripts and (len(request.alwayson_scripts) > 0): + if request.alwayson_scripts: for alwayson_script_name in request.alwayson_scripts.keys(): alwayson_script = self.get_script(alwayson_script_name, script_runner) if alwayson_script is None: diff --git a/modules/call_queue.py b/modules/call_queue.py index 53af6d70..1b5e5273 100644 --- a/modules/call_queue.py +++ b/modules/call_queue.py @@ -21,7 +21,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): def f(*args, **kwargs): # if the first argument is a string that says "task(...)", it is treated as a job id - if len(args) > 0 and type(args[0]) == str and args[0][0:5] == "task(" and args[0][-1] == ")": + if args and type(args[0]) == str and args[0].startswith("task(") and args[0].endswith(")"): id_task = args[0] progress.add_task_to_queue(id_task) else: diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py index aa2a14ef..b6a6dc0e 100644 --- a/modules/extra_networks_hypernet.py +++ b/modules/extra_networks_hypernet.py @@ -9,7 +9,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork): def activate(self, p, params_list): additional = shared.opts.sd_hypernetwork - if additional != "None" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0: + if additional != "None" and additional in shared.hypernetworks and not any(x for x in params_list if x.items[0] == additional): hypernet_prompt_text = f"" p.all_prompts = [f"{prompt}{hypernet_prompt_text}" for prompt in p.all_prompts] params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier])) @@ -17,7 +17,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork): names = [] multipliers = [] for params in params_list: - assert len(params.items) > 0 + assert params.items names.append(params.items[0]) multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0) diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 071bd9ea..237401a1 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -55,7 +55,7 @@ def image_from_url_text(filedata): if filedata is None: return None - if type(filedata) == list and len(filedata) > 0 and type(filedata[0]) == dict and filedata[0].get("is_file", False): + if type(filedata) == list and filedata and type(filedata[0]) == dict and filedata[0].get("is_file", False): filedata = filedata[0] if type(filedata) == dict and filedata.get("is_file", False): @@ -437,7 +437,7 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, vals_pairs = [f"{k}: {v}" for k, v in vals.items()] - return gr.Dropdown.update(value=vals_pairs, choices=vals_pairs, visible=len(vals_pairs) > 0) + return gr.Dropdown.update(value=vals_pairs, choices=vals_pairs, visible=bool(vals_pairs)) paste_fields = paste_fields + [(override_settings_component, paste_settings)] @@ -454,5 +454,3 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, outputs=[], show_progress=False, ) - - diff --git a/modules/images.py b/modules/images.py index a12d252b..7bbfc3e0 100644 --- a/modules/images.py +++ b/modules/images.py @@ -406,7 +406,7 @@ class FilenameGenerator: prompt_no_style = self.prompt for style in shared.prompt_styles.get_style_prompts(self.p.styles): - if len(style) > 0: + if style: for part in style.split("{prompt}"): prompt_no_style = prompt_no_style.replace(part, "").replace(", ,", ",").strip().strip(',') @@ -415,7 +415,7 @@ class FilenameGenerator: return sanitize_filename_part(prompt_no_style, replace_spaces=False) def prompt_words(self): - words = [x for x in re_nonletters.split(self.prompt or "") if len(x) > 0] + words = [x for x in re_nonletters.split(self.prompt or "") if x] if len(words) == 0: words = ["empty"] return sanitize_filename_part(" ".join(words[0:opts.directories_max_prompt_words]), replace_spaces=False) @@ -423,7 +423,7 @@ class FilenameGenerator: def datetime(self, *args): time_datetime = datetime.datetime.now() - time_format = args[0] if len(args) > 0 and args[0] != "" else self.default_time_format + time_format = args[0] if (args and args[0] != "") else self.default_time_format try: time_zone = pytz.timezone(args[1]) if len(args) > 1 else None except pytz.exceptions.UnknownTimeZoneError: diff --git a/modules/img2img.py b/modules/img2img.py index 4c12c2c5..35c4facc 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -21,8 +21,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args): is_inpaint_batch = False if inpaint_mask_dir: inpaint_masks = shared.listfiles(inpaint_mask_dir) - is_inpaint_batch = len(inpaint_masks) > 0 - if is_inpaint_batch: + is_inpaint_batch = bool(inpaint_masks) print(f"\nInpaint batch is enabled. {len(inpaint_masks)} masks found.") print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.") diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index 3fb76b65..b892d5fc 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -230,9 +230,9 @@ class DDPM(pl.LightningModule): missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict( sd, strict=False) print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys") - if len(missing) > 0: + if missing: print(f"Missing Keys: {missing}") - if len(unexpected) > 0: + if unexpected: print(f"Unexpected Keys: {unexpected}") def q_mean_variance(self, x_start, t): diff --git a/modules/processing.py b/modules/processing.py index 362ab4c2..9ebdb549 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -975,7 +975,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest") if self.enable_hr and latent_scale_mode is None: - assert len([x for x in shared.sd_upscalers if x.name == self.hr_upscaler]) > 0, f"could not find upscaler named {self.hr_upscaler}" + if not any(x.name == self.hr_upscaler for x in shared.sd_upscalers): + raise Exception(f"could not find upscaler named {self.hr_upscaler}") x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x)) diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index b4aff704..0069d8b0 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -336,11 +336,11 @@ def parse_prompt_attention(text): round_brackets.append(len(res)) elif text == '[': square_brackets.append(len(res)) - elif weight is not None and len(round_brackets) > 0: + elif weight is not None and round_brackets: multiply_range(round_brackets.pop(), float(weight)) - elif text == ')' and len(round_brackets) > 0: + elif text == ')' and round_brackets: multiply_range(round_brackets.pop(), round_bracket_multiplier) - elif text == ']' and len(square_brackets) > 0: + elif text == ']' and square_brackets: multiply_range(square_brackets.pop(), square_bracket_multiplier) else: parts = re.split(re_break, text) diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index f755283c..77ee55ee 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -287,14 +287,14 @@ def list_unets_callback(): def add_callback(callbacks, fun): stack = [x for x in inspect.stack() if x.filename != __file__] - filename = stack[0].filename if len(stack) > 0 else 'unknown file' + filename = stack[0].filename if stack else 'unknown file' callbacks.append(ScriptCallback(filename, fun)) def remove_current_script_callbacks(): stack = [x for x in inspect.stack() if x.filename != __file__] - filename = stack[0].filename if len(stack) > 0 else 'unknown file' + filename = stack[0].filename if stack else 'unknown file' if filename == 'unknown file': return for callback_list in callback_map.values(): diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py index cc6e8c21..3b5a7666 100644 --- a/modules/sd_hijack_clip.py +++ b/modules/sd_hijack_clip.py @@ -167,7 +167,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): chunk.multipliers += [weight] * emb_len position += embedding_length_in_tokens - if len(chunk.tokens) > 0 or len(chunks) == 0: + if chunk.tokens or not chunks: next_chunk(is_last=True) return chunks, token_count diff --git a/modules/sd_hijack_clip_old.py b/modules/sd_hijack_clip_old.py index a3476e95..c5c6270b 100644 --- a/modules/sd_hijack_clip_old.py +++ b/modules/sd_hijack_clip_old.py @@ -74,7 +74,7 @@ def forward_old(self: sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase, text self.hijack.comments += hijack_comments - if len(used_custom_terms) > 0: + if used_custom_terms: embedding_names = ", ".join(f"{word} [{checksum}]" for word, checksum in used_custom_terms) self.hijack.comments.append(f"Used embeddings: {embedding_names}") diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 8e667a4d..75705459 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -77,27 +77,27 @@ def focal_point(im, settings): pois = [] weight_pref_total = 0 - if len(corner_points) > 0: + if corner_points: weight_pref_total += settings.corner_points_weight - if len(entropy_points) > 0: + if entropy_points: weight_pref_total += settings.entropy_points_weight - if len(face_points) > 0: + if face_points: weight_pref_total += settings.face_points_weight corner_centroid = None - if len(corner_points) > 0: + if corner_points: corner_centroid = centroid(corner_points) corner_centroid.weight = settings.corner_points_weight / weight_pref_total pois.append(corner_centroid) entropy_centroid = None - if len(entropy_points) > 0: + if entropy_points: entropy_centroid = centroid(entropy_points) entropy_centroid.weight = settings.entropy_points_weight / weight_pref_total pois.append(entropy_centroid) face_centroid = None - if len(face_points) > 0: + if face_points: face_centroid = centroid(face_points) face_centroid.weight = settings.face_points_weight / weight_pref_total pois.append(face_centroid) @@ -187,7 +187,7 @@ def image_face_points(im, settings): except Exception: continue - if len(faces) > 0: + if faces: rects = [[f[0], f[1], f[0] + f[2], f[1] + f[3]] for f in faces] return [PointOfInterest((r[0] +r[2]) // 2, (r[1] + r[3]) // 2, size=abs(r[0]-r[2]), weight=1/len(rects)) for r in rects] return [] diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index b9621fc9..7ee05061 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -32,7 +32,7 @@ class DatasetEntry: class PersonalizedBase(Dataset): def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, cond_model=None, device=None, template_file=None, include_cond=False, batch_size=1, gradient_step=1, shuffle_tags=False, tag_drop_out=0, latent_sampling_method='once', varsize=False, use_weight=False): - re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex) > 0 else None + re_word = re.compile(shared.opts.dataset_filename_word_regex) if shared.opts.dataset_filename_word_regex else None self.placeholder_token = placeholder_token diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index a009d8e8..0d4c3f84 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -47,7 +47,7 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti caption += shared.interrogator.generate_caption(image) if params.process_caption_deepbooru: - if len(caption) > 0: + if caption: caption += ", " caption += deepbooru.model.tag_multi(image) @@ -67,7 +67,7 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti caption = caption.strip() - if len(caption) > 0: + if caption: with open(os.path.join(params.dstdir, f"{basename}.txt"), "w", encoding="utf8") as file: file.write(caption) diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 8da050ca..bb6f211c 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -251,7 +251,7 @@ class EmbeddingDatabase: if self.previously_displayed_embeddings != displayed_embeddings: self.previously_displayed_embeddings = displayed_embeddings print(f"Textual inversion embeddings loaded({len(self.word_embeddings)}): {', '.join(self.word_embeddings.keys())}") - if len(self.skipped_embeddings) > 0: + if self.skipped_embeddings: print(f"Textual inversion embeddings skipped({len(self.skipped_embeddings)}): {', '.join(self.skipped_embeddings.keys())}") def find_embedding_at_position(self, tokens, offset): diff --git a/modules/ui.py b/modules/ui.py index b7459f08..9a025cca 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -398,7 +398,7 @@ def create_override_settings_dropdown(tabname, row): dropdown = gr.Dropdown([], label="Override settings", visible=False, elem_id=f"{tabname}_override_settings", multiselect=True) dropdown.change( - fn=lambda x: gr.Dropdown.update(visible=len(x) > 0), + fn=lambda x: gr.Dropdown.update(visible=bool(x)), inputs=[dropdown], outputs=[dropdown], ) diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 3140ed64..65173e06 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -333,7 +333,8 @@ def install_extension_from_url(dirname, url, branch_name=None): assert not os.path.exists(target_dir), f'Extension directory already exists: {target_dir}' normalized_url = normalize_git_url(url) - assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed' + if any(x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url): + raise Exception(f'Extension with this URL is already installed: {url}') tmpdir = os.path.join(paths.data_path, "tmp", dirname) @@ -449,7 +450,7 @@ def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text=" existing = installed_extension_urls.get(normalize_git_url(url), None) extension_tags = extension_tags + ["installed"] if existing else extension_tags - if len([x for x in extension_tags if x in tags_to_hide]) > 0: + if any(x for x in extension_tags if x in tags_to_hide): hidden += 1 continue diff --git a/modules/ui_settings.py b/modules/ui_settings.py index 7874298e..2688d8c2 100644 --- a/modules/ui_settings.py +++ b/modules/ui_settings.py @@ -81,7 +81,7 @@ class UiSettings: opts.save(shared.config_filename) except RuntimeError: return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.' - return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.' + return opts.dumpjson(), f'{len(changed)} settings changed{": " if changed else ""}{", ".join(changed)}.' def run_settings_single(self, value, key): if not opts.same_type(value, opts.data_labels[key].default): diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 83a2f220..50320d55 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -121,8 +121,7 @@ class Script(scripts.Script): return [checkbox_iterate, checkbox_iterate_batch, prompt_txt] def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_txt: str): - lines = [x.strip() for x in prompt_txt.splitlines()] - lines = [x for x in lines if len(x) > 0] + lines = [x for x in (x.strip() for x in prompt_txt.splitlines()) if x] p.do_not_save_grid = True -- cgit v1.2.3 From f98f4f73aa4898c754681f411608df5f248619f6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 4 Jun 2023 10:56:48 +0300 Subject: infer styles from prompts, and an option to control the behavior --- modules/generation_parameters_copypaste.py | 8 ++++ modules/shared.py | 13 +++++- modules/styles.py | 67 +++++++++++++++++++++++++++++- modules/ui.py | 2 + 4 files changed, 87 insertions(+), 3 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 071bd9ea..4c420e5f 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -265,6 +265,14 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model else: prompt += ("" if prompt == "" else "\n") + line + if shared.opts.infotext_styles != "Ignore": + found_styles, prompt, negative_prompt = shared.prompt_styles.extract_styles_from_prompt(prompt, negative_prompt) + + if shared.opts.infotext_styles == "Apply": + res["Styles array"] = found_styles + elif shared.opts.infotext_styles == "Apply if any" and found_styles: + res["Styles array"] = found_styles + res["Prompt"] = prompt res["Negative prompt"] = negative_prompt diff --git a/modules/shared.py b/modules/shared.py index 7025a754..53e3d5da 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -260,6 +260,10 @@ class OptionInfo: self.comment_after += f"({info})" return self + def html(self, html): + self.comment_after += html + return self + def needs_restart(self): self.comment_after += " (requires restart)" return self @@ -488,7 +492,14 @@ options_templates.update(options_section(('infotext', "Infotext"), { "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"), "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"), "add_version_to_infotext": OptionInfo(True, "Add program version to generation information"), - "disable_weights_auto_swap": OptionInfo(True, "When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint."), + "disable_weights_auto_swap": OptionInfo(True, "Disregard checkpoint information from pasted infotext").info("when reading generation parameters from text into UI"), + "infotext_styles": OptionInfo("Apply if any", "Infer styles from prompts of pasted infotext", gr.Radio, {"choices": ["Ignore", "Apply", "Discard", "Apply if any"]}).info("when reading generation parameters from text into UI)").html("""
    +
  • Ignore: keep prompt and styles dropdown as it is.
    • +
  • Apply: remove style text from prompt, always replace styles dropdown value with found styles (even if none are found).
    • +
  • Discard: remove style text from prompt, keep styles dropdown as it is.
    • +
  • Apply if any: remove style text from prompt; if any styles are found in prompt, put them into styles dropdown, otherwise keep it as it is.
    • +
"""), + })) options_templates.update(options_section(('ui', "Live previews"), { diff --git a/modules/styles.py b/modules/styles.py index 34e1b5e1..ec0e1bc5 100644 --- a/modules/styles.py +++ b/modules/styles.py @@ -1,6 +1,7 @@ import csv import os import os.path +import re import typing import shutil @@ -28,6 +29,44 @@ def apply_styles_to_prompt(prompt, styles): return prompt +re_spaces = re.compile(" +") + + +def extract_style_text_from_prompt(style_text, prompt): + stripped_prompt = re.sub(re_spaces, " ", prompt.strip()) + stripped_style_text = re.sub(re_spaces, " ", style_text.strip()) + if "{prompt}" in stripped_style_text: + left, right = stripped_style_text.split("{prompt}", 2) + if stripped_prompt.startswith(left) and stripped_prompt.endswith(right): + prompt = stripped_prompt[len(left):len(stripped_prompt)-len(right)] + return True, prompt + else: + if stripped_prompt.endswith(stripped_style_text): + prompt = stripped_prompt[:len(stripped_prompt)-len(stripped_style_text)] + + if prompt.endswith(', '): + prompt = prompt[:-2] + + return True, prompt + + return False, prompt + + +def extract_style_from_prompts(style: PromptStyle, prompt, negative_prompt): + if not style.prompt and not style.negative_prompt: + return False, prompt, negative_prompt + + match_positive, extracted_positive = extract_style_text_from_prompt(style.prompt, prompt) + if not match_positive: + return False, prompt, negative_prompt + + match_negative, extracted_negative = extract_style_text_from_prompt(style.negative_prompt, negative_prompt) + if not match_negative: + return False, prompt, negative_prompt + + return True, extracted_positive, extracted_negative + + class StyleDatabase: def __init__(self, path: str): self.no_style = PromptStyle("None", "", "") @@ -67,10 +106,34 @@ class StyleDatabase: if os.path.exists(path): shutil.copy(path, f"{path}.bak") - fd = os.open(path, os.O_RDWR|os.O_CREAT) + fd = os.open(path, os.O_RDWR | os.O_CREAT) with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file: # _fields is actually part of the public API: typing.NamedTuple is a replacement for collections.NamedTuple, # and collections.NamedTuple has explicit documentation for accessing _fields. Same goes for _asdict() writer = csv.DictWriter(file, fieldnames=PromptStyle._fields) writer.writeheader() - writer.writerows(style._asdict() for k, style in self.styles.items()) + writer.writerows(style._asdict() for k, style in self.styles.items()) + + def extract_styles_from_prompt(self, prompt, negative_prompt): + extracted = [] + + applicable_styles = list(self.styles.values()) + + while True: + found_style = None + + for style in applicable_styles: + is_match, new_prompt, new_neg_prompt = extract_style_from_prompts(style, prompt, negative_prompt) + if is_match: + found_style = style + prompt = new_prompt + negative_prompt = new_neg_prompt + break + + if not found_style: + break + + applicable_styles.remove(found_style) + extracted.append(found_style.name) + + return list(reversed(extracted)), prompt, negative_prompt diff --git a/modules/ui.py b/modules/ui.py index 988b2003..7ae33ab1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -621,6 +621,7 @@ def create_ui(): (subseed_strength, "Variation seed strength"), (seed_resize_from_w, "Seed resize from-1"), (seed_resize_from_h, "Seed resize from-2"), + (txt2img_prompt_styles, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()), (denoising_strength, "Denoising strength"), (enable_hr, lambda d: "Denoising strength" in d), (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), @@ -1036,6 +1037,7 @@ def create_ui(): (subseed_strength, "Variation seed strength"), (seed_resize_from_w, "Seed resize from-1"), (seed_resize_from_h, "Seed resize from-2"), + (img2img_prompt_styles, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()), (denoising_strength, "Denoising strength"), (mask_blur, "Mask blur"), *modules.scripts.scripts_img2img.infotext_fields -- cgit v1.2.3 From 851bf43520226da6cfe5f6546d9aaf035a121182 Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Tue, 6 Jun 2023 05:40:00 +0900 Subject: print error and continue print error and continue --- modules/generation_parameters_copypaste.py | 21 ++++++++++++--------- 1 file changed, 12 insertions(+), 9 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 1d02ffae..a638f912 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -277,15 +277,18 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res["Negative prompt"] = negative_prompt for k, v in re_param.findall(lastline): - if v[0] == '"' and v[-1] == '"': - v = unquote(v) - - m = re_imagesize.match(v) - if m is not None: - res[f"{k}-1"] = m.group(1) - res[f"{k}-2"] = m.group(2) - else: - res[k] = v + try: + if v[0] == '"' and v[-1] == '"': + v = unquote(v) + + m = re_imagesize.match(v) + if m is not None: + res[f"{k}-1"] = m.group(1) + res[f"{k}-2"] = m.group(2) + else: + res[k] = v + except Exception: + print(f"Error parsing \"{k}: {v}\"") # Missing CLIP skip means it was set to 1 (the default) if "Clip skip" not in res: -- cgit v1.2.3 From 4bd490c28dd8f17b7df943eb3963c34d725084fc Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 27 Jun 2023 06:18:43 +0300 Subject: add missing infotext entry for the pad cond/uncond option --- modules/generation_parameters_copypaste.py | 1 + modules/sd_samplers_kdiffusion.py | 11 ++++++++++- 2 files changed, 11 insertions(+), 1 deletion(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a638f912..dd30a1b5 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -357,6 +357,7 @@ infotext_to_setting_name_mapping = [ ('Token merging ratio hr', 'token_merging_ratio_hr'), ('RNG', 'randn_source'), ('NGMS', 's_min_uncond'), + ('Pad conds', 'pad_cond_uncond'), ] diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index f8a0c7ba..71581b76 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -69,6 +69,7 @@ class CFGDenoiser(torch.nn.Module): self.init_latent = None self.step = 0 self.image_cfg_scale = None + self.padded_cond_uncond = False def combine_denoised(self, x_out, conds_list, uncond, cond_scale): denoised_uncond = x_out[-uncond.shape[0]:] @@ -133,15 +134,17 @@ class CFGDenoiser(torch.nn.Module): x_in = x_in[:-batch_size] sigma_in = sigma_in[:-batch_size] - # TODO add infotext entry + self.padded_cond_uncond = False if shared.opts.pad_cond_uncond and tensor.shape[1] != uncond.shape[1]: empty = shared.sd_model.cond_stage_model_empty_prompt num_repeats = (tensor.shape[1] - uncond.shape[1]) // empty.shape[1] if num_repeats < 0: tensor = torch.cat([tensor, empty.repeat((tensor.shape[0], -num_repeats, 1))], axis=1) + self.padded_cond_uncond = True elif num_repeats > 0: uncond = torch.cat([uncond, empty.repeat((uncond.shape[0], num_repeats, 1))], axis=1) + self.padded_cond_uncond = True if tensor.shape[1] == uncond.shape[1] or skip_uncond: if is_edit_model: @@ -405,6 +408,9 @@ class KDiffusionSampler: samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs)) + if self.model_wrap_cfg.padded_cond_uncond: + p.extra_generation_params["Pad conds"] = True + return samples def sample(self, p, x, conditioning, unconditional_conditioning, steps=None, image_conditioning=None): @@ -438,5 +444,8 @@ class KDiffusionSampler: 's_min_uncond': self.s_min_uncond }, disable=False, callback=self.callback_state, **extra_params_kwargs)) + if self.model_wrap_cfg.padded_cond_uncond: + p.extra_generation_params["Pad conds"] = True + return samples -- cgit v1.2.3