From a10487986925ca8fd07ee7ae7fc5034752298551 Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Mon, 22 May 2023 21:52:46 +0800 Subject: Add custom karras scheduler --- scripts/xyz_grid.py | 3 +++ 1 file changed, 3 insertions(+) (limited to 'scripts/xyz_grid.py') diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index da820b39..6ea049ee 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -220,6 +220,9 @@ 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("Karras Scheduler Sigma Min", float, apply_field("sigma_min")), + AxisOption("Karras Scheduler Sigma Max", float, apply_field("sigma_max")), + AxisOption("Karras Scheduler rho", float, apply_field("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 e6269cba7fd84a76b2bd0012cb954f947a79b6a5 Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Mon, 22 May 2023 23:02:05 +0800 Subject: Add dropdown for scheduler type --- modules/img2img.py | 3 ++- modules/processing.py | 4 +++- modules/sd_samplers_kdiffusion.py | 19 +++++++++++++++---- modules/txt2img.py | 3 ++- modules/ui.py | 26 ++++++++++++++++---------- scripts/xyz_grid.py | 3 ++- 6 files changed, 40 insertions(+), 18 deletions(-) (limited to 'scripts/xyz_grid.py') diff --git a/modules/img2img.py b/modules/img2img.py index 898c3dc1..73af5acb 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -78,7 +78,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args): processed_image.save(os.path.join(output_dir, filename)) -def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, enable_k_sched, sigma_min, sigma_max, rho, *args): +def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, enable_k_sched, k_sched_type, sigma_min, sigma_max, rho, *args): override_settings = create_override_settings_dict(override_settings_texts) is_batch = mode == 5 @@ -156,6 +156,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s inpainting_mask_invert=inpainting_mask_invert, override_settings=override_settings, enable_karras=enable_k_sched, + k_sched_type=k_sched_type, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho diff --git a/modules/processing.py b/modules/processing.py index b26f7998..ad5d5960 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -106,7 +106,7 @@ class StableDiffusionProcessing: """ The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing """ - def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_karras: bool = False, sigma_min: float=0.1, sigma_max: float=10.0, rho: float=7.0): + def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_karras: bool = False, k_sched_type: str = "karras", sigma_min: float=0.1, sigma_max: float=10.0, rho: float=7.0): if sampler_index is not None: print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr) @@ -147,6 +147,7 @@ class StableDiffusionProcessing: self.s_tmax = s_tmax or float('inf') # not representable as a standard ui option self.s_noise = s_noise or opts.s_noise self.enable_karras = enable_karras + self.k_sched_type = k_sched_type self.sigma_max = sigma_max self.sigma_min = sigma_min self.rho = rho @@ -563,6 +564,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Steps": p.steps, "Sampler": p.sampler_name, "Enable Custom Karras Schedule": p.enable_karras, + "Karras Scheduler Type": p.k_sched_type, "Karras Scheduler sigma_max": p.sigma_max, "Karras Scheduler sigma_min": p.sigma_min, "Karras Scheduler rho": p.rho, diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index d428551d..441c040e 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -44,6 +44,12 @@ sampler_extra_params = { 'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'], } +k_diffusion_scheduler = { + 'karras': k_diffusion.sampling.get_sigmas_karras, + 'exponential': k_diffusion.sampling.get_sigmas_exponential, + 'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential +} + class CFGDenoiser(torch.nn.Module): """ @@ -305,10 +311,15 @@ class KDiffusionSampler: if p.sampler_noise_scheduler_override: sigmas = p.sampler_noise_scheduler_override(steps) elif p.enable_karras: - sigma_max = p.sigma_max - sigma_min = p.sigma_min - rho = p.rho - sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho, device=shared.device) + print(p.k_sched_type, p.sigma_min, p.sigma_max, p.rho) + sigmas_func = k_diffusion_scheduler[p.k_sched_type] + sigmas_kwargs = { + 'sigma_min': p.sigma_min, + 'sigma_max': p.sigma_max + } + if p.k_sched_type != 'exponential': + sigmas_kwargs['rho'] = p.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/txt2img.py b/modules/txt2img.py index 9f634007..28d30568 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -7,7 +7,7 @@ from modules.ui import plaintext_to_html -def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, enable_k_sched, sigma_min, sigma_max, rho, *args): +def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, enable_k_sched, k_sched_type, sigma_min, sigma_max, rho, *args): override_settings = create_override_settings_dict(override_settings_texts) p = processing.StableDiffusionProcessingTxt2Img( @@ -44,6 +44,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step hr_negative_prompt=hr_negative_prompt, override_settings=override_settings, enable_karras=enable_k_sched, + k_sched_type=k_sched_type, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho diff --git a/modules/ui.py b/modules/ui.py index a65f8d85..28d4f1d1 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -514,9 +514,10 @@ def create_ui(): elif category == "karras_scheduler": with FormGroup(visible=False, elem_id="txt2img_karras_scheduler") as t2i_k_sched_options: with FormRow(elem_id="txt2img_karras_scheduler_row1", variant="compact"): - t2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") - t2i_k_sched_sigma_min = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") - t2i_k_sched_rho = gr.Slider(minimum=3.0, maximum=10.0, step=0.5, label='rho', value=7.0, elem_id="txt2img_rho") + t2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras') + t2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") + t2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") + t2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho") elif category == "batch": if not opts.dimensions_and_batch_together: @@ -587,8 +588,9 @@ def create_ui(): hr_negative_prompt, override_settings, t2i_enable_k_sched, - t2i_k_sched_sigma_max, + t2i_k_sched_type, t2i_k_sched_sigma_min, + t2i_k_sched_sigma_max, t2i_k_sched_rho ] + custom_inputs, @@ -674,7 +676,8 @@ def create_ui(): (hr_prompt, "Hires prompt"), (hr_negative_prompt, "Hires negative prompt"), (hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()), - (t2i_enable_k_sched, "Enable CustomKarras Schedule"), + (t2i_enable_k_sched, "Enable Custom Karras Schedule"), + (t2i_k_sched_type, "Karras Scheduler Type"), (t2i_k_sched_sigma_max, "Karras Scheduler sigma_max"), (t2i_k_sched_sigma_min, "Karras Scheduler sigma_min"), (t2i_k_sched_rho, "Karras Scheduler rho"), @@ -874,9 +877,10 @@ def create_ui(): elif category == "karras_scheduler": with FormGroup(visible=False, elem_id="img2img_karras_scheduler") as i2i_k_sched_options: with FormRow(elem_id="img2img_karras_scheduler_row1", variant="compact"): - i2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") - i2i_k_sched_sigma_min = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") - i2i_k_sched_rho = gr.Slider(minimum=3.0, maximum=10.0, step=0.5, label='rho', value=7.0, elem_id="txt2img_rho") + i2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras') + i2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") + i2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") + i2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho") elif category == "batch": if not opts.dimensions_and_batch_together: @@ -981,8 +985,9 @@ def create_ui(): img2img_batch_inpaint_mask_dir, override_settings, i2i_enable_k_sched, - i2i_k_sched_sigma_max, + i2i_k_sched_type, i2i_k_sched_sigma_min, + i2i_k_sched_sigma_max, i2i_k_sched_rho ] + custom_inputs, outputs=[ @@ -1085,7 +1090,8 @@ def create_ui(): (steps, "Steps"), (sampler_index, "Sampler"), (restore_faces, "Face restoration"), - (i2i_enable_k_sched, "Enable Karras Schedule"), + (i2i_enable_k_sched, "Enable Custom Karras Schedule"), + (i2i_k_sched_type, "Karras Scheduler Type"), (i2i_k_sched_sigma_max, "Karras Scheduler sigma_max"), (i2i_k_sched_sigma_min, "Karras Scheduler sigma_min"), (i2i_k_sched_rho, "Karras Scheduler rho"), diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 6ea049ee..cea43c18 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -10,7 +10,7 @@ import numpy as np import modules.scripts as scripts import gradio as gr -from modules import images, sd_samplers, processing, sd_models, sd_vae +from modules import images, sd_samplers, processing, sd_models, sd_vae, sd_samplers_kdiffusion from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img from modules.shared import opts, state import modules.shared as shared @@ -220,6 +220,7 @@ 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("Karras Scheduler Type", str, apply_field("k_sched_type"), choices=lambda: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]), AxisOption("Karras Scheduler Sigma Min", float, apply_field("sigma_min")), AxisOption("Karras Scheduler Sigma Max", float, apply_field("sigma_max")), AxisOption("Karras Scheduler rho", float, apply_field("rho")), -- cgit v1.2.3 From f82105144319fef7e973339062e972b6688fae11 Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Mon, 22 May 2023 23:09:03 +0800 Subject: Change karras to kdiffusion --- modules/processing.py | 8 ++++---- modules/shared.py | 2 +- modules/ui.py | 32 ++++++++++++++++---------------- scripts/xyz_grid.py | 8 ++++---- 4 files changed, 25 insertions(+), 25 deletions(-) (limited to 'scripts/xyz_grid.py') diff --git a/modules/processing.py b/modules/processing.py index ad5d5960..3fb05d79 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -564,10 +564,10 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Steps": p.steps, "Sampler": p.sampler_name, "Enable Custom Karras Schedule": p.enable_karras, - "Karras Scheduler Type": p.k_sched_type, - "Karras Scheduler sigma_max": p.sigma_max, - "Karras Scheduler sigma_min": p.sigma_min, - "Karras Scheduler rho": p.rho, + "kdiffusion Scheduler Type": p.k_sched_type, + "kdiffusion Scheduler sigma_max": p.sigma_max, + "kdiffusion Scheduler sigma_min": p.sigma_min, + "kdiffusion Scheduler rho": p.rho, "CFG scale": p.cfg_scale, "Image CFG scale": getattr(p, 'image_cfg_scale', None), "Seed": all_seeds[index], diff --git a/modules/shared.py b/modules/shared.py index dbba0824..069b37d8 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -47,7 +47,7 @@ ui_reorder_categories = [ "inpaint", "sampler", "checkboxes", - "karras_scheduler", + "kdiffusion_scheduler", "hires_fix", "dimensions", "cfg", diff --git a/modules/ui.py b/modules/ui.py index 28d4f1d1..fd5c0799 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -484,7 +484,7 @@ def create_ui(): with FormRow(elem_classes="checkboxes-row", variant="compact"): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces") tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling") - t2i_enable_k_sched = gr.Checkbox(label='Custom Karras Scheduler', value=False, elem_id="txt2img_enable_k_sched") + t2i_enable_k_sched = gr.Checkbox(label='Custom KDiffusion Scheduler', value=False, elem_id="txt2img_enable_k_sched") enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr") hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False) @@ -511,9 +511,9 @@ def create_ui(): with gr.Row(): hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"]) - elif category == "karras_scheduler": - with FormGroup(visible=False, elem_id="txt2img_karras_scheduler") as t2i_k_sched_options: - with FormRow(elem_id="txt2img_karras_scheduler_row1", variant="compact"): + elif category == "kdiffusion_scheduler": + with FormGroup(visible=False, elem_id="txt2img_kdiffusion_scheduler") as t2i_k_sched_options: + with FormRow(elem_id="txt2img_kdiffusion_scheduler_row1", variant="compact"): t2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras') t2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") t2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") @@ -677,10 +677,10 @@ def create_ui(): (hr_negative_prompt, "Hires negative prompt"), (hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()), (t2i_enable_k_sched, "Enable Custom Karras Schedule"), - (t2i_k_sched_type, "Karras Scheduler Type"), - (t2i_k_sched_sigma_max, "Karras Scheduler sigma_max"), - (t2i_k_sched_sigma_min, "Karras Scheduler sigma_min"), - (t2i_k_sched_rho, "Karras Scheduler rho"), + (t2i_k_sched_type, "KDiffusion Scheduler Type"), + (t2i_k_sched_sigma_max, "KDiffusion Scheduler sigma_max"), + (t2i_k_sched_sigma_min, "KDiffusion Scheduler sigma_min"), + (t2i_k_sched_rho, "KDiffusion Scheduler rho"), *modules.scripts.scripts_txt2img.infotext_fields ] parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields, override_settings) @@ -872,11 +872,11 @@ def create_ui(): with FormRow(elem_classes="checkboxes-row", variant="compact"): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces") tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling") - i2i_enable_k_sched = gr.Checkbox(label='Custom Karras Scheduler', value=False, elem_id="txt2img_enable_k_sched") + i2i_enable_k_sched = gr.Checkbox(label='Custom KDiffusion Scheduler', value=False, elem_id="txt2img_enable_k_sched") - elif category == "karras_scheduler": - with FormGroup(visible=False, elem_id="img2img_karras_scheduler") as i2i_k_sched_options: - with FormRow(elem_id="img2img_karras_scheduler_row1", variant="compact"): + elif category == "kdiffusion_scheduler": + with FormGroup(visible=False, elem_id="img2img_kdiffusion_scheduler") as i2i_k_sched_options: + with FormRow(elem_id="img2img_kdiffusion_scheduler_row1", variant="compact"): i2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras') i2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") i2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") @@ -1091,10 +1091,10 @@ def create_ui(): (sampler_index, "Sampler"), (restore_faces, "Face restoration"), (i2i_enable_k_sched, "Enable Custom Karras Schedule"), - (i2i_k_sched_type, "Karras Scheduler Type"), - (i2i_k_sched_sigma_max, "Karras Scheduler sigma_max"), - (i2i_k_sched_sigma_min, "Karras Scheduler sigma_min"), - (i2i_k_sched_rho, "Karras Scheduler rho"), + (i2i_k_sched_type, "KDiffusion Scheduler Type"), + (i2i_k_sched_sigma_max, "KDiffusion Scheduler sigma_max"), + (i2i_k_sched_sigma_min, "KDiffusion Scheduler sigma_min"), + (i2i_k_sched_rho, "KDiffusion Scheduler rho"), (cfg_scale, "CFG scale"), (image_cfg_scale, "Image CFG scale"), (seed, "Seed"), diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index cea43c18..74ece252 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("Karras Scheduler Type", str, apply_field("k_sched_type"), choices=lambda: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]), - AxisOption("Karras Scheduler Sigma Min", float, apply_field("sigma_min")), - AxisOption("Karras Scheduler Sigma Max", float, apply_field("sigma_max")), - AxisOption("Karras Scheduler rho", float, apply_field("rho")), + AxisOption("KDiffusion Scheduler Type", str, apply_field("k_sched_type"), choices=lambda: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]), + AxisOption("KDiffusion Scheduler Sigma Min", float, apply_field("sigma_min")), + AxisOption("KDiffusion Scheduler Sigma Max", float, apply_field("sigma_max")), + AxisOption("KDiffusion Scheduler rho", float, apply_field("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 78aed1fa4a984b2714ad11f33cbb20007aec2a34 Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Tue, 23 May 2023 11:47:32 +0800 Subject: Fix xyz --- scripts/xyz_grid.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'scripts/xyz_grid.py') diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 74ece252..cb618e18 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_field("k_sched_type"), choices=lambda: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]), - AxisOption("KDiffusion Scheduler Sigma Min", float, apply_field("sigma_min")), - AxisOption("KDiffusion Scheduler Sigma Max", float, apply_field("sigma_max")), - AxisOption("KDiffusion Scheduler rho", float, apply_field("rho")), + AxisOption("KDiffusion Scheduler Type", str, apply_override("k_sched_type"), choices=lambda: [x for x in 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("Eta", float, apply_field("eta")), AxisOption("Clip skip", int, apply_clip_skip), AxisOption("Denoising", float, apply_field("denoising_strength")), -- cgit v1.2.3 From 27962ded4a5303548559d14fe2cae373d7a5e5ac Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Tue, 23 May 2023 23:50:19 +0800 Subject: Fix ruff error --- scripts/xyz_grid.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'scripts/xyz_grid.py') diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index cb618e18..a4126e78 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -220,7 +220,7 @@ 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: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]), + 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")), -- 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 'scripts/xyz_grid.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 'scripts/xyz_grid.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 'scripts/xyz_grid.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