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: [PATCH 01/13] Add custom karras scheduler

---
 modules/img2img.py                |  6 +++-
 modules/processing.py             | 10 ++++++-
 modules/sd_samplers_kdiffusion.py |  6 ++++
 modules/shared.py                 |  1 +
 modules/txt2img.py                |  6 +++-
 modules/ui.py                     | 46 +++++++++++++++++++++++++++++++
 scripts/xyz_grid.py               |  3 ++
 7 files changed, 75 insertions(+), 3 deletions(-)

diff --git a/modules/img2img.py b/modules/img2img.py
index d704bf9006d..898c3dc1029 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, *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, sigma_min, sigma_max, rho, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     is_batch = mode == 5
@@ -155,6 +155,10 @@ 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_karras=enable_k_sched,
+        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 29a3743f578..b26f799861d 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):
+    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):
         if sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
@@ -146,6 +146,10 @@ def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prom
         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_karras = enable_karras
+        self.sigma_max = sigma_max
+        self.sigma_min = sigma_min
+        self.rho = 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
@@ -558,6 +562,10 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     generation_params = {
         "Steps": p.steps,
         "Sampler": p.sampler_name,
+        "Enable Custom Karras Schedule": p.enable_karras,
+        "Karras Scheduler sigma_max": p.sigma_max,
+        "Karras Scheduler sigma_min": p.sigma_min,
+        "Karras 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/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 638e0ac92a2..eb6c760c23f 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -304,6 +304,12 @@ def get_sigmas(self, p, steps):
 
         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
+            print(f"\nsigma_min: {sigma_min}, sigma_max: {sigma_max}, rho: {rho}")
+            sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho, 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 0897f937a23..dbba0824d36 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -47,6 +47,7 @@
     "inpaint",
     "sampler",
     "checkboxes",
+    "karras_scheduler",
     "hires_fix",
     "dimensions",
     "cfg",
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 2e7d202d7b0..9f63400711f 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -7,7 +7,7 @@
 
 
 
-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):
+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):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     p = processing.StableDiffusionProcessingTxt2Img(
@@ -43,6 +43,10 @@ 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_karras=enable_k_sched,
+        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 001b9792356..a65f8d857a4 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -484,6 +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")
                             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)
 
@@ -510,6 +511,13 @@ 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"):
+                                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")
+
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
                             with FormRow(elem_id="txt2img_column_batch"):
@@ -578,6 +586,10 @@ def create_ui():
                     hr_prompt,
                     hr_negative_prompt,
                     override_settings,
+                    t2i_enable_k_sched,
+                    t2i_k_sched_sigma_max,
+                    t2i_k_sched_sigma_min,
+                    t2i_k_sched_rho
 
                 ] + custom_inputs,
 
@@ -627,6 +639,13 @@ 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"),
@@ -655,6 +674,10 @@ 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_k_sched_sigma_max, "Karras Scheduler sigma_max"),
+                (t2i_k_sched_sigma_min, "Karras Scheduler sigma_min"),
+                (t2i_k_sched_rho, "Karras Scheduler rho"),
                 *modules.scripts.scripts_txt2img.infotext_fields
             ]
             parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields, override_settings)
@@ -846,6 +869,14 @@ def copy_image(img):
                         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")
+
+                    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")
 
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
@@ -949,6 +980,10 @@ def select_img2img_tab(tab):
                     img2img_batch_output_dir,
                     img2img_batch_inpaint_mask_dir,
                     override_settings,
+                    i2i_enable_k_sched,
+                    i2i_k_sched_sigma_max,
+                    i2i_k_sched_sigma_min,
+                    i2i_k_sched_rho
                 ] + custom_inputs,
                 outputs=[
                     img2img_gallery,
@@ -1032,6 +1067,13 @@ def select_img2img_tab(tab):
                     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])
 
@@ -1043,6 +1085,10 @@ def select_img2img_tab(tab):
                 (steps, "Steps"),
                 (sampler_index, "Sampler"),
                 (restore_faces, "Face restoration"),
+                (i2i_enable_k_sched, "Enable Karras Schedule"),
+                (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"),
                 (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 da820b394d4..6ea049ee82b 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -220,6 +220,9 @@ def __init__(self, *args, **kwargs):
     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")),

From 90ec557d60289a89b4ea6cd9b311658fbe682dc3 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Mon, 22 May 2023 22:06:13 +0800
Subject: [PATCH 02/13] remove debug print

---
 modules/sd_samplers_kdiffusion.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index eb6c760c23f..d428551d30a 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -308,7 +308,6 @@ def get_sigmas(self, p, steps):
             sigma_max = p.sigma_max
             sigma_min = p.sigma_min
             rho = p.rho
-            print(f"\nsigma_min: {sigma_min}, sigma_max: {sigma_max}, rho: {rho}")
             sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho, 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())

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: [PATCH 03/13] 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(-)

diff --git a/modules/img2img.py b/modules/img2img.py
index 898c3dc1029..73af5acbbe6 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 b26f799861d..ad5d59607ea 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 @@ def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prom
         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 d428551d30a..441c040e454 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -44,6 +44,12 @@
     '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 @@ def get_sigmas(self, p, steps):
         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 9f63400711f..28d30568870 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -7,7 +7,7 @@
 
 
 
-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 a65f8d857a4..28d4f1d1ee2 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 copy_image(img):
                     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 select_img2img_tab(tab):
                     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 select_img2img_tab(tab):
                 (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 6ea049ee82b..cea43c1882b 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -10,7 +10,7 @@
 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 @@ def __init__(self, *args, **kwargs):
     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")),

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: [PATCH 04/13] 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(-)

diff --git a/modules/processing.py b/modules/processing.py
index ad5d59607ea..3fb05d79bc3 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 dbba0824d36..069b37d83fe 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -47,7 +47,7 @@
     "inpaint",
     "sampler",
     "checkboxes",
-    "karras_scheduler",
+    "kdiffusion_scheduler",
     "hires_fix",
     "dimensions",
     "cfg",
diff --git a/modules/ui.py b/modules/ui.py
index 28d4f1d1ee2..fd5c07995a7 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 copy_image(img):
                         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 select_img2img_tab(tab):
                 (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 cea43c1882b..74ece252757 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -220,10 +220,10 @@ def __init__(self, *args, **kwargs):
     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")),

From 7882f76da45de7279c7db0dd17b6aca82b7ddf46 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Mon, 22 May 2023 23:26:28 +0800
Subject: [PATCH 05/13] Replace karras by k_diffusion, fix gen info

---
 modules/img2img.py                |  2 +-
 modules/processing.py             | 14 +++++++-------
 modules/sd_hijack.py              |  1 +
 modules/sd_samplers_kdiffusion.py |  3 ++-
 modules/txt2img.py                |  2 +-
 5 files changed, 12 insertions(+), 10 deletions(-)

diff --git a/modules/img2img.py b/modules/img2img.py
index 73af5acbbe6..bec4354f6a0 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -155,7 +155,7 @@ 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_karras=enable_k_sched,
+        enable_custom_k_sched=enable_k_sched,
         k_sched_type=k_sched_type,
         sigma_min=sigma_min,
         sigma_max=sigma_max,
diff --git a/modules/processing.py b/modules/processing.py
index 3fb05d79bc3..260a573a1c0 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, 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 = "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)
 
@@ -146,7 +146,7 @@ def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prom
         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_karras = enable_karras
+        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
@@ -563,11 +563,11 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     generation_params = {
         "Steps": p.steps,
         "Sampler": p.sampler_name,
-        "Enable Custom Karras Schedule": p.enable_karras,
-        "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,
+        "Enable Custom Karras Schedule": p.enable_custom_k_sched or None,
+        "kdiffusion Scheduler Type": p.k_sched_type if p.enable_custom_k_sched else None,
+        "kdiffusion Scheduler sigma_max": p.sigma_max if p.enable_custom_k_sched else None,
+        "kdiffusion Scheduler sigma_min": p.sigma_min if p.enable_custom_k_sched else None,
+        "kdiffusion Scheduler rho": p.rho if p.enable_custom_k_sched else None,
         "CFG scale": p.cfg_scale,
         "Image CFG scale": getattr(p, 'image_cfg_scale', None),
         "Seed": all_seeds[index],
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 08d31080f45..9e157db8835 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -41,6 +41,7 @@ def list_optimizers():
 
     optimizers.clear()
     optimizers.extend(new_optimizers)
+    print(optimizers)
 
 
 def apply_optimizations():
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 441c040e454..4d8f57a799e 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -44,6 +44,7 @@
     'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'],
 }
 
+k_diffusion_samplers_map = {x.name: x for x in samplers_data_k_diffusion}
 k_diffusion_scheduler = {
     'karras': k_diffusion.sampling.get_sigmas_karras,
     'exponential': k_diffusion.sampling.get_sigmas_exponential,
@@ -310,7 +311,7 @@ def get_sigmas(self, p, steps):
 
         if p.sampler_noise_scheduler_override:
             sigmas = p.sampler_noise_scheduler_override(steps)
-        elif p.enable_karras:
+        elif p.enable_custom_k_sched:
             print(p.k_sched_type, p.sigma_min, p.sigma_max, p.rho)
             sigmas_func = k_diffusion_scheduler[p.k_sched_type]
             sigmas_kwargs = {
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 28d30568870..dd52e710d05 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -43,7 +43,7 @@ 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_karras=enable_k_sched,
+        enable_custom_k_sched=enable_k_sched,
         k_sched_type=k_sched_type,
         sigma_min=sigma_min,
         sigma_max=sigma_max,

From 7dc9d9e27e157ccd7a0c59405a3aaf4f1ca7e194 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Mon, 22 May 2023 23:34:16 +0800
Subject: [PATCH 06/13] only add metadata when k_sched is actually been used

---
 modules/processing.py | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 260a573a1c0..5e50f1d63e9 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -13,7 +13,7 @@
 from typing import Any, Dict, List
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_samplers_kdiffusion
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -560,14 +560,16 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     if uses_ensd:
         uses_ensd = sd_samplers_common.is_sampler_using_eta_noise_seed_delta(p)
 
+    use_custom_k_sched = p.enable_custom_k_sched and p.sampler_name in sd_samplers_kdiffusion.k_diffusion_samplers_map
+
     generation_params = {
         "Steps": p.steps,
         "Sampler": p.sampler_name,
-        "Enable Custom Karras Schedule": p.enable_custom_k_sched or None,
-        "kdiffusion Scheduler Type": p.k_sched_type if p.enable_custom_k_sched else None,
-        "kdiffusion Scheduler sigma_max": p.sigma_max if p.enable_custom_k_sched else None,
-        "kdiffusion Scheduler sigma_min": p.sigma_min if p.enable_custom_k_sched else None,
-        "kdiffusion Scheduler rho": p.rho if p.enable_custom_k_sched else None,
+        "Enable Custom Karras Schedule": use_custom_k_sched or None,
+        "kdiffusion Scheduler Type": p.k_sched_type if use_custom_k_sched else None,
+        "kdiffusion Scheduler sigma_max": p.sigma_max if use_custom_k_sched else None,
+        "kdiffusion Scheduler sigma_min": p.sigma_min if use_custom_k_sched else None,
+        "kdiffusion Scheduler rho": p.rho if use_custom_k_sched else None,
         "CFG scale": p.cfg_scale,
         "Image CFG scale": getattr(p, 'image_cfg_scale', None),
         "Seed": all_seeds[index],

From 5dfb1f597b47b1028ee010df2ed8642e2beb6c1c Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Mon, 22 May 2023 23:36:16 +0800
Subject: [PATCH 07/13] remove not related code

---
 modules/sd_hijack.py              | 1 -
 modules/sd_samplers_kdiffusion.py | 1 -
 2 files changed, 2 deletions(-)

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 9e157db8835..08d31080f45 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -41,7 +41,6 @@ def list_optimizers():
 
     optimizers.clear()
     optimizers.extend(new_optimizers)
-    print(optimizers)
 
 
 def apply_optimizations():
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 4d8f57a799e..ba0cf08e5bf 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -312,7 +312,6 @@ def get_sigmas(self, p, steps):
         if p.sampler_noise_scheduler_override:
             sigmas = p.sampler_noise_scheduler_override(steps)
         elif p.enable_custom_k_sched:
-            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,

From 4365c35bf9e2a777e2ebddc15c5ea94000407071 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Mon, 22 May 2023 23:41:14 +0800
Subject: [PATCH 08/13] Avoid loop import

---
 modules/processing.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/modules/processing.py b/modules/processing.py
index 5e50f1d63e9..d9703fe8a89 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -13,7 +13,7 @@
 from typing import Any, Dict, List
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_samplers_kdiffusion
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -560,6 +560,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     if uses_ensd:
         uses_ensd = sd_samplers_common.is_sampler_using_eta_noise_seed_delta(p)
 
+    # avoid loop import
+    from modules import sd_samplers_kdiffusion
     use_custom_k_sched = p.enable_custom_k_sched and p.sampler_name in sd_samplers_kdiffusion.k_diffusion_samplers_map
 
     generation_params = {

From 302d95c72697ecaf436445817f4676e70ba68f20 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Mon, 22 May 2023 23:43:06 +0800
Subject: [PATCH 09/13] Minor naming fixes

---
 modules/processing.py | 10 +++++-----
 modules/ui.py         |  4 ++--
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index d9703fe8a89..68f7f16824a 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -567,11 +567,11 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     generation_params = {
         "Steps": p.steps,
         "Sampler": p.sampler_name,
-        "Enable Custom Karras Schedule": use_custom_k_sched or None,
-        "kdiffusion Scheduler Type": p.k_sched_type if use_custom_k_sched else None,
-        "kdiffusion Scheduler sigma_max": p.sigma_max if use_custom_k_sched else None,
-        "kdiffusion Scheduler sigma_min": p.sigma_min if use_custom_k_sched else None,
-        "kdiffusion Scheduler rho": p.rho if use_custom_k_sched else None,
+        "Enable Custom KDiffusion Schedule": use_custom_k_sched or None,
+        "KDiffusion Scheduler Type": p.k_sched_type if use_custom_k_sched else None,
+        "KDiffusion Scheduler sigma_max": p.sigma_max if use_custom_k_sched else None,
+        "KDiffusion Scheduler sigma_min": p.sigma_min if use_custom_k_sched else None,
+        "KDiffusion Scheduler rho": p.rho if use_custom_k_sched else None,
         "CFG scale": p.cfg_scale,
         "Image CFG scale": getattr(p, 'image_cfg_scale', None),
         "Seed": all_seeds[index],
diff --git a/modules/ui.py b/modules/ui.py
index fd5c07995a7..6d53bdc66f9 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -676,7 +676,7 @@ 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 Karras Schedule"),
+                (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"),
@@ -1090,7 +1090,7 @@ def select_img2img_tab(tab):
                 (steps, "Steps"),
                 (sampler_index, "Sampler"),
                 (restore_faces, "Face restoration"),
-                (i2i_enable_k_sched, "Enable Custom Karras Schedule"),
+                (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"),

From 65a87ccc9bf92a0fd24a453e2837dd2d19bbf5ce Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 23 May 2023 00:09:49 +0800
Subject: [PATCH 10/13] Add error information for recursion error

---
 modules/sd_samplers_kdiffusion.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index ba0cf08e5bf..e2f18b54295 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -272,6 +272,12 @@ def launch_sampling(self, steps, func):
 
         try:
             return func()
+        except RecursionError:
+            print(
+                'rho>5 with polyexponential scheduler may cause this error.'
+                'You should try to use smaller rho instead.'
+            )
+            return self.last_latent
         except sd_samplers_common.InterruptedException:
             return self.last_latent
 

From 403b304162b670597f20b01f147bb042eb78ee5c Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 23 May 2023 00:29:38 +0800
Subject: [PATCH 11/13] use sigma_max/min in model if sigma_max/min is 0

---
 modules/sd_samplers_kdiffusion.py | 5 +++--
 modules/ui.py                     | 4 ++--
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index e2f18b54295..7364ed44efd 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -318,10 +318,11 @@ def get_sigmas(self, p, steps):
         if p.sampler_noise_scheduler_override:
             sigmas = p.sampler_noise_scheduler_override(steps)
         elif p.enable_custom_k_sched:
+            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[p.k_sched_type]
             sigmas_kwargs = {
-                'sigma_min': p.sigma_min,
-                'sigma_max': p.sigma_max
+                'sigma_min': p.sigma_min or sigma_min,
+                'sigma_max': p.sigma_max or sigma_max
             }
             if p.k_sched_type != 'exponential':
                 sigmas_kwargs['rho'] = p.rho
diff --git a/modules/ui.py b/modules/ui.py
index 6d53bdc66f9..fa3a41eb8d2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -516,7 +516,7 @@ def create_ui():
                             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")
+                                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":
@@ -879,7 +879,7 @@ def copy_image(img):
                             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")
+                                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":

From 38aaad654bec640e99beb42964d09357878179bd Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 23 May 2023 09:38:30 +0800
Subject: [PATCH 12/13] Better hint for user

Co-authored-by: catboxanon <122327233+catboxanon@users.noreply.github.com>
---
 modules/sd_samplers_kdiffusion.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 7364ed44efd..969ef02b15c 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -274,8 +274,9 @@ def launch_sampling(self, steps, func):
             return func()
         except RecursionError:
             print(
-                'rho>5 with polyexponential scheduler may cause this error.'
-                'You should try to use smaller rho instead.'
+                'Encountered RecursionError during sampling, returning last latent. '
+                'rho >5 with a polyexponential scheduler may cause this error. '
+                'You should try to use a smaller rho value instead.'
             )
             return self.last_latent
         except sd_samplers_common.InterruptedException:

From 89c44bbc15488a3d42eb63adee867b77ec432b09 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 23 May 2023 09:52:15 +0800
Subject: [PATCH 13/13] Add hint for custom k_diffusion scheduler

---
 javascript/hints.js | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/javascript/hints.js b/javascript/hints.js
index 46f342cb9cf..9583c7dc16a 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -113,7 +113,12 @@ 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."
+    "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"
 };
 
 function updateTooltipForSpan(span) {