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

---
 modules/shared.py | 1 +
 1 file changed, 1 insertion(+)

(limited to 'modules/shared.py')

diff --git a/modules/shared.py b/modules/shared.py
index 0897f937..dbba0824 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -47,6 +47,7 @@ ui_reorder_categories = [
     "inpaint",
     "sampler",
     "checkboxes",
+    "karras_scheduler",
     "hires_fix",
     "dimensions",
     "cfg",
-- 
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 'modules/shared.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 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

---
 javascript/hints.js                        |  7 +---
 modules/generation_parameters_copypaste.py |  5 +++
 modules/img2img.py                         |  7 +---
 modules/processing.py                      | 12 +++----
 modules/shared.py                          |  6 +++-
 modules/txt2img.py                         |  7 +---
 modules/ui.py                              | 52 ------------------------------
 7 files changed, 19 insertions(+), 77 deletions(-)

(limited to 'modules/shared.py')

diff --git a/javascript/hints.js b/javascript/hints.js
index 9583c7dc..46f342cb 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -113,12 +113,7 @@ var titles = {
     "Multiplier for extra networks": "When adding extra network such as Hypernetwork or Lora to prompt, use this multiplier for it.",
     "Discard weights with matching name": "Regular expression; if weights's name matches it, the weights is not written to the resulting checkpoint. Use ^model_ema to discard EMA weights.",
     "Extra networks tab order": "Comma-separated list of tab names; tabs listed here will appear in the extra networks UI first and in order lsited.",
-    "Negative Guidance minimum sigma": "Skip negative prompt for steps where image is already mostly denoised; the higher this value, the more skips there will be; provides increased performance in exchange for minor quality reduction.",
-
-    "Custom KDiffusion Scheduler": "Custom noise scheduler to use for KDiffusion. See https://arxiv.org/abs/2206.00364",
-    "sigma min": "the minimum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use.",
-    "sigma max": "the maximum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use.",
-    "rho": "higher will make a more steep noise scheduler (decrease faster). default for karras is 7.0, for polyexponential is 1.0"
+    "Negative Guidance minimum sigma": "Skip negative prompt for steps where image is already mostly denoised; the higher this value, the more skips there will be; provides increased performance in exchange for minor quality reduction."
 };
 
 function updateTooltipForSpan(span) {
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'),
diff --git a/modules/img2img.py b/modules/img2img.py
index bec4354f..d704bf90 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, k_sched_type, 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, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     is_batch = mode == 5
@@ -155,11 +155,6 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
         inpaint_full_res_padding=inpaint_full_res_padding,
         inpainting_mask_invert=inpainting_mask_invert,
         override_settings=override_settings,
-        enable_custom_k_sched=enable_k_sched,
-        k_sched_type=k_sched_type,
-        sigma_min=sigma_min,
-        sigma_max=sigma_max,
-        rho=rho
     )
 
     p.scripts = modules.scripts.scripts_img2img
diff --git a/modules/processing.py b/modules/processing.py
index 68f7f168..0a0181de 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_custom_k_sched: bool = False, k_sched_type: str = "karras", 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_custom_k_sched: bool = False, k_sched_type: str = "", sigma_min: float=0.0, sigma_max: float=0.0, rho: float=0.0):
         if sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
@@ -146,11 +146,11 @@ class StableDiffusionProcessing:
         self.s_tmin = s_tmin or opts.s_tmin
         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_custom_k_sched = enable_custom_k_sched
-        self.k_sched_type = k_sched_type
-        self.sigma_max = sigma_max
-        self.sigma_min = sigma_min
-        self.rho = rho
+        self.enable_custom_k_sched = opts.custom_k_sched
+        self.k_sched_type = k_sched_type or opts.k_sched_type
+        self.sigma_max = sigma_max or opts.sigma_max
+        self.sigma_min = sigma_min or opts.sigma_min
+        self.rho = rho or opts.rho
         self.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts}
         self.override_settings_restore_afterwards = override_settings_restore_afterwards
         self.is_using_inpainting_conditioning = False
diff --git a/modules/shared.py b/modules/shared.py
index 069b37d8..a0e762d2 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -47,7 +47,6 @@ ui_reorder_categories = [
     "inpaint",
     "sampler",
     "checkboxes",
-    "kdiffusion_scheduler",
     "hires_fix",
     "dimensions",
     "cfg",
@@ -518,6 +517,11 @@ 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"]}),
+    '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"),
     '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/modules/txt2img.py b/modules/txt2img.py
index dd52e710..2e7d202d 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, k_sched_type, 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, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     p = processing.StableDiffusionProcessingTxt2Img(
@@ -43,11 +43,6 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
         hr_prompt=hr_prompt,
         hr_negative_prompt=hr_negative_prompt,
         override_settings=override_settings,
-        enable_custom_k_sched=enable_k_sched,
-        k_sched_type=k_sched_type,
-        sigma_min=sigma_min,
-        sigma_max=sigma_max,
-        rho=rho
     )
 
     p.scripts = modules.scripts.scripts_txt2img
diff --git a/modules/ui.py b/modules/ui.py
index fa3a41eb..001b9792 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -484,7 +484,6 @@ 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 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)
 
@@ -511,14 +510,6 @@ 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 == "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=0.0, 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:
                             with FormRow(elem_id="txt2img_column_batch"):
@@ -587,11 +578,6 @@ def create_ui():
                     hr_prompt,
                     hr_negative_prompt,
                     override_settings,
-                    t2i_enable_k_sched,
-                    t2i_k_sched_type,
-                    t2i_k_sched_sigma_min,
-                    t2i_k_sched_sigma_max,
-                    t2i_k_sched_rho
 
                 ] + custom_inputs,
 
@@ -641,13 +627,6 @@ def create_ui():
                 show_progress = False,
             )
 
-            t2i_enable_k_sched.change(
-                fn=lambda x: gr_show(x),
-                inputs=[t2i_enable_k_sched],
-                outputs=[t2i_k_sched_options],
-                show_progress=False
-            )
-
             txt2img_paste_fields = [
                 (txt2img_prompt, "Prompt"),
                 (txt2img_negative_prompt, "Negative prompt"),
@@ -676,11 +655,6 @@ 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 Custom KDiffusion Schedule"),
-                (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)
@@ -872,15 +846,6 @@ 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 KDiffusion Scheduler', value=False, elem_id="txt2img_enable_k_sched")
-
-                    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=0.0, 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:
@@ -984,11 +949,6 @@ def create_ui():
                     img2img_batch_output_dir,
                     img2img_batch_inpaint_mask_dir,
                     override_settings,
-                    i2i_enable_k_sched,
-                    i2i_k_sched_type,
-                    i2i_k_sched_sigma_min,
-                    i2i_k_sched_sigma_max,
-                    i2i_k_sched_rho
                 ] + custom_inputs,
                 outputs=[
                     img2img_gallery,
@@ -1072,13 +1032,6 @@ def create_ui():
                     outputs=[prompt, negative_prompt, styles],
                 )
 
-            i2i_enable_k_sched.change(
-                fn=lambda x: gr_show(x),
-                inputs=[i2i_enable_k_sched],
-                outputs=[i2i_k_sched_options],
-                show_progress=False
-            )
-
             token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
             negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[img2img_negative_prompt, steps], outputs=[negative_token_counter])
 
@@ -1090,11 +1043,6 @@ def create_ui():
                 (steps, "Steps"),
                 (sampler_index, "Sampler"),
                 (restore_faces, "Face restoration"),
-                (i2i_enable_k_sched, "Enable Custom KDiffusion Schedule"),
-                (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"),
-- 
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/shared.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 1601fccebca2dc5a806a0d2f0d33aa2da81a28fb Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Wed, 24 May 2023 00:18:09 +0800
Subject: Use automatic instead of None/default

---
 modules/sd_samplers_kdiffusion.py | 6 +++---
 modules/shared.py                 | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

(limited to 'modules/shared.py')

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index eff2e32d..a4c797c6 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -46,7 +46,7 @@ sampler_extra_params = {
 
 k_diffusion_samplers_map = {x.name: x for x in samplers_data_k_diffusion}
 k_diffusion_scheduler = {
-    'None': None,
+    'Automatic': None,
     'karras': k_diffusion.sampling.get_sigmas_karras,
     'exponential': k_diffusion.sampling.get_sigmas_exponential,
     'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential
@@ -296,7 +296,7 @@ class KDiffusionSampler:
 
         k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
 
-        if opts.k_sched_type != "None":
+        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
@@ -325,7 +325,7 @@ class KDiffusionSampler:
 
         if p.sampler_noise_scheduler_override:
             sigmas = p.sampler_noise_scheduler_override(steps)
-        elif opts.k_sched_type != "None":
+        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]
             sigmas_kwargs = {
diff --git a/modules/shared.py b/modules/shared.py
index b24f52dd..da7f7cfb 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -517,7 +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}),
-    'k_sched_type':  OptionInfo("default", "scheduler type", gr.Dropdown, {"choices": ["None", "karras", "exponential", "polyexponential"]}),
+    '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."),
     '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/shared.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