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 01/21] 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 d704bf90..898c3dc1 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 29a3743f..b26f7998 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 @@ 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_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 638e0ac9..eb6c760c 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -304,6 +304,12 @@ class KDiffusionSampler:
 
         if p.sampler_noise_scheduler_override:
             sigmas = p.sampler_noise_scheduler_override(steps)
+        elif p.enable_karras:
+            sigma_max = p.sigma_max
+            sigma_min = p.sigma_min
+            rho = p.rho
+            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 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",
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 2e7d202d..9f634007 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, *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 001b9792..a65f8d85 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 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")
+
+                    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 create_ui():
                     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 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])
 
@@ -1043,6 +1085,10 @@ def create_ui():
                 (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 da820b39..6ea049ee 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -220,6 +220,9 @@ axis_options = [
     AxisOption("Sigma min", float, apply_field("s_tmin")),
     AxisOption("Sigma max", float, apply_field("s_tmax")),
     AxisOption("Sigma noise", float, apply_field("s_noise")),
+    AxisOption("Karras Scheduler Sigma Min", float, apply_field("sigma_min")),
+    AxisOption("Karras Scheduler Sigma Max", float, apply_field("sigma_max")),
+    AxisOption("Karras Scheduler rho", float, apply_field("rho")),
     AxisOption("Eta", float, apply_field("eta")),
     AxisOption("Clip skip", int, apply_clip_skip),
     AxisOption("Denoising", float, apply_field("denoising_strength")),

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 02/21] 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 eb6c760c..d428551d 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -308,7 +308,6 @@ class KDiffusionSampler:
             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 03/21] 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 898c3dc1..73af5acb 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -78,7 +78,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
                 processed_image.save(os.path.join(output_dir, filename))
 
 
-def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, enable_k_sched, sigma_min, sigma_max, rho, *args):
+def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, enable_k_sched, k_sched_type, sigma_min, sigma_max, rho, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     is_batch = mode == 5
@@ -156,6 +156,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
         inpainting_mask_invert=inpainting_mask_invert,
         override_settings=override_settings,
         enable_karras=enable_k_sched,
+        k_sched_type=k_sched_type,
         sigma_min=sigma_min,
         sigma_max=sigma_max,
         rho=rho
diff --git a/modules/processing.py b/modules/processing.py
index b26f7998..ad5d5960 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -106,7 +106,7 @@ class StableDiffusionProcessing:
     """
     The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
     """
-    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_karras: bool = False, sigma_min: float=0.1, sigma_max: float=10.0, rho: float=7.0):
+    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_karras: bool = False, k_sched_type: str = "karras", sigma_min: float=0.1, sigma_max: float=10.0, rho: float=7.0):
         if sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
@@ -147,6 +147,7 @@ class StableDiffusionProcessing:
         self.s_tmax = s_tmax or float('inf')  # not representable as a standard ui option
         self.s_noise = s_noise or opts.s_noise
         self.enable_karras = enable_karras
+        self.k_sched_type = k_sched_type
         self.sigma_max = sigma_max
         self.sigma_min = sigma_min
         self.rho = rho
@@ -563,6 +564,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Steps": p.steps,
         "Sampler": p.sampler_name,
         "Enable Custom Karras Schedule": p.enable_karras,
+        "Karras Scheduler Type": p.k_sched_type,
         "Karras Scheduler sigma_max": p.sigma_max,
         "Karras Scheduler sigma_min": p.sigma_min,
         "Karras Scheduler rho": p.rho,
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index d428551d..441c040e 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -44,6 +44,12 @@ sampler_extra_params = {
     'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'],
 }
 
+k_diffusion_scheduler = {
+    'karras': k_diffusion.sampling.get_sigmas_karras,
+    'exponential': k_diffusion.sampling.get_sigmas_exponential,
+    'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential
+}
+
 
 class CFGDenoiser(torch.nn.Module):
     """
@@ -305,10 +311,15 @@ class KDiffusionSampler:
         if p.sampler_noise_scheduler_override:
             sigmas = p.sampler_noise_scheduler_override(steps)
         elif p.enable_karras:
-            sigma_max = p.sigma_max
-            sigma_min = p.sigma_min
-            rho = p.rho
-            sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho, device=shared.device)
+            print(p.k_sched_type, p.sigma_min, p.sigma_max, p.rho)
+            sigmas_func = k_diffusion_scheduler[p.k_sched_type]
+            sigmas_kwargs = {
+                'sigma_min': p.sigma_min,
+                'sigma_max': p.sigma_max
+            }
+            if p.k_sched_type != 'exponential':
+                sigmas_kwargs['rho'] = p.rho
+            sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device)
         elif self.config is not None and self.config.options.get('scheduler', None) == 'karras':
             sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item())
 
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 9f634007..28d30568 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -7,7 +7,7 @@ from modules.ui import plaintext_to_html
 
 
 
-def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, enable_k_sched, sigma_min, sigma_max, rho, *args):
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, enable_k_sched, k_sched_type, sigma_min, sigma_max, rho, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     p = processing.StableDiffusionProcessingTxt2Img(
@@ -44,6 +44,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
         hr_negative_prompt=hr_negative_prompt,
         override_settings=override_settings,
         enable_karras=enable_k_sched,
+        k_sched_type=k_sched_type,
         sigma_min=sigma_min,
         sigma_max=sigma_max,
         rho=rho
diff --git a/modules/ui.py b/modules/ui.py
index a65f8d85..28d4f1d1 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -514,9 +514,10 @@ def create_ui():
                     elif category == "karras_scheduler":
                         with FormGroup(visible=False, elem_id="txt2img_karras_scheduler") as t2i_k_sched_options:
                             with FormRow(elem_id="txt2img_karras_scheduler_row1", variant="compact"):
-                                t2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min")
-                                t2i_k_sched_sigma_min = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max")
-                                t2i_k_sched_rho = gr.Slider(minimum=3.0, maximum=10.0, step=0.5, label='rho', value=7.0, elem_id="txt2img_rho")
+                                t2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras')
+                                t2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min")
+                                t2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max")
+                                t2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho")
 
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
@@ -587,8 +588,9 @@ def create_ui():
                     hr_negative_prompt,
                     override_settings,
                     t2i_enable_k_sched,
-                    t2i_k_sched_sigma_max,
+                    t2i_k_sched_type,
                     t2i_k_sched_sigma_min,
+                    t2i_k_sched_sigma_max,
                     t2i_k_sched_rho
 
                 ] + custom_inputs,
@@ -674,7 +676,8 @@ def create_ui():
                 (hr_prompt, "Hires prompt"),
                 (hr_negative_prompt, "Hires negative prompt"),
                 (hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()),
-                (t2i_enable_k_sched, "Enable CustomKarras Schedule"),
+                (t2i_enable_k_sched, "Enable Custom Karras Schedule"),
+                (t2i_k_sched_type, "Karras Scheduler Type"),
                 (t2i_k_sched_sigma_max, "Karras Scheduler sigma_max"),
                 (t2i_k_sched_sigma_min, "Karras Scheduler sigma_min"),
                 (t2i_k_sched_rho, "Karras Scheduler rho"),
@@ -874,9 +877,10 @@ def create_ui():
                     elif category == "karras_scheduler":
                         with FormGroup(visible=False, elem_id="img2img_karras_scheduler") as i2i_k_sched_options:
                             with FormRow(elem_id="img2img_karras_scheduler_row1", variant="compact"):
-                                i2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min")
-                                i2i_k_sched_sigma_min = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max")
-                                i2i_k_sched_rho = gr.Slider(minimum=3.0, maximum=10.0, step=0.5, label='rho', value=7.0, elem_id="txt2img_rho")
+                                i2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras')
+                                i2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min")
+                                i2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max")
+                                i2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho")
 
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
@@ -981,8 +985,9 @@ def create_ui():
                     img2img_batch_inpaint_mask_dir,
                     override_settings,
                     i2i_enable_k_sched,
-                    i2i_k_sched_sigma_max,
+                    i2i_k_sched_type,
                     i2i_k_sched_sigma_min,
+                    i2i_k_sched_sigma_max,
                     i2i_k_sched_rho
                 ] + custom_inputs,
                 outputs=[
@@ -1085,7 +1090,8 @@ def create_ui():
                 (steps, "Steps"),
                 (sampler_index, "Sampler"),
                 (restore_faces, "Face restoration"),
-                (i2i_enable_k_sched, "Enable Karras Schedule"),
+                (i2i_enable_k_sched, "Enable Custom Karras Schedule"),
+                (i2i_k_sched_type, "Karras Scheduler Type"),
                 (i2i_k_sched_sigma_max, "Karras Scheduler sigma_max"),
                 (i2i_k_sched_sigma_min, "Karras Scheduler sigma_min"),
                 (i2i_k_sched_rho, "Karras Scheduler rho"),
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 6ea049ee..cea43c18 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -10,7 +10,7 @@ import numpy as np
 import modules.scripts as scripts
 import gradio as gr
 
-from modules import images, sd_samplers, processing, sd_models, sd_vae
+from modules import images, sd_samplers, processing, sd_models, sd_vae, sd_samplers_kdiffusion
 from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
 from modules.shared import opts, state
 import modules.shared as shared
@@ -220,6 +220,7 @@ axis_options = [
     AxisOption("Sigma min", float, apply_field("s_tmin")),
     AxisOption("Sigma max", float, apply_field("s_tmax")),
     AxisOption("Sigma noise", float, apply_field("s_noise")),
+    AxisOption("Karras Scheduler Type", str, apply_field("k_sched_type"), choices=lambda: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]),
     AxisOption("Karras Scheduler Sigma Min", float, apply_field("sigma_min")),
     AxisOption("Karras Scheduler Sigma Max", float, apply_field("sigma_max")),
     AxisOption("Karras Scheduler rho", float, apply_field("rho")),

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 04/21] 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 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")),

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 05/21] 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 73af5acb..bec4354f 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 3fb05d79..260a573a 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 @@ 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_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 08d31080..9e157db8 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 441c040e..4d8f57a7 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -44,6 +44,7 @@ sampler_extra_params = {
     '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 @@ class KDiffusionSampler:
 
         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 28d30568..dd52e710 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 06/21] 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 260a573a..5e50f1d6 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -13,7 +13,7 @@ from skimage import exposure
 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 07/21] 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 9e157db8..08d31080 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 4d8f57a7..ba0cf08e 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -312,7 +312,6 @@ class KDiffusionSampler:
         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 08/21] 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 5e50f1d6..d9703fe8 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -13,7 +13,7 @@ from skimage import exposure
 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 09/21] 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 d9703fe8..68f7f168 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 fd5c0799..6d53bdc6 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 create_ui():
                 (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 10/21] 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 ba0cf08e..e2f18b54 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -272,6 +272,12 @@ class KDiffusionSampler:
 
         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 11/21] 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 e2f18b54..7364ed44 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -318,10 +318,11 @@ class KDiffusionSampler:
         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 6d53bdc6..fa3a41eb 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 create_ui():
                             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 12/21] 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 7364ed44..969ef02b 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -274,8 +274,9 @@ class KDiffusionSampler:
             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 13/21] 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 46f342cb..9583c7dc 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) {

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: [PATCH 14/21] 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(-)

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"),

From 70650f87a42615a62568a896403156d0065621b4 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 23 May 2023 11:34:51 +0800
Subject: [PATCH 15/21] Use better way to impl

---
 modules/processing.py             | 16 +---------------
 modules/sd_samplers_kdiffusion.py | 19 +++++++++++++------
 2 files changed, 14 insertions(+), 21 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 0a0181de..29a3743f 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 = "", sigma_min: float=0.0, sigma_max: float=0.0, rho: float=0.0):
+    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):
         if sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
@@ -146,11 +146,6 @@ 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 = 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
@@ -560,18 +555,9 @@ 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 = {
         "Steps": p.steps,
         "Sampler": p.sampler_name,
-        "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/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 969ef02b..5fea08b0 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -295,6 +295,13 @@ 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
+            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:
@@ -318,15 +325,15 @@ class KDiffusionSampler:
 
         if p.sampler_noise_scheduler_override:
             sigmas = p.sampler_noise_scheduler_override(steps)
-        elif p.enable_custom_k_sched:
+        elif opts.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_func = k_diffusion_scheduler[opts.k_sched_type]
             sigmas_kwargs = {
-                'sigma_min': p.sigma_min or sigma_min,
-                'sigma_max': p.sigma_max or sigma_max
+                'sigma_min': opts.sigma_min or sigma_min,
+                'sigma_max': opts.sigma_max or sigma_max
             }
-            if p.k_sched_type != 'exponential':
-                sigmas_kwargs['rho'] = p.rho
+            if opts.k_sched_type != 'exponential':
+                sigmas_kwargs['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())

From 78aed1fa4a984b2714ad11f33cbb20007aec2a34 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 23 May 2023 11:47:32 +0800
Subject: [PATCH 16/21] Fix xyz

---
 scripts/xyz_grid.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 74ece252..cb618e18 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -220,10 +220,10 @@ axis_options = [
     AxisOption("Sigma min", float, apply_field("s_tmin")),
     AxisOption("Sigma max", float, apply_field("s_tmax")),
     AxisOption("Sigma noise", float, apply_field("s_noise")),
-    AxisOption("KDiffusion Scheduler Type", str, apply_field("k_sched_type"), choices=lambda: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]),
-    AxisOption("KDiffusion Scheduler Sigma Min", float, apply_field("sigma_min")),
-    AxisOption("KDiffusion Scheduler Sigma Max", float, apply_field("sigma_max")),
-    AxisOption("KDiffusion Scheduler rho", float, apply_field("rho")),
+    AxisOption("KDiffusion Scheduler Type", str, apply_override("k_sched_type"), choices=lambda: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]),
+    AxisOption("KDiffusion Scheduler Sigma Min", float, apply_override("sigma_min")),
+    AxisOption("KDiffusion Scheduler Sigma Max", float, apply_override("sigma_max")),
+    AxisOption("KDiffusion Scheduler rho", float, apply_override("rho")),
     AxisOption("Eta", float, apply_field("eta")),
     AxisOption("Clip skip", int, apply_clip_skip),
     AxisOption("Denoising", float, apply_field("denoising_strength")),

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: [PATCH 17/21] 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(-)

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"),

From 27962ded4a5303548559d14fe2cae373d7a5e5ac Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 23 May 2023 23:50:19 +0800
Subject: [PATCH 18/21] Fix ruff error

---
 scripts/xyz_grid.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index cb618e18..a4126e78 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -220,7 +220,7 @@ axis_options = [
     AxisOption("Sigma min", float, apply_field("s_tmin")),
     AxisOption("Sigma max", float, apply_field("s_tmax")),
     AxisOption("Sigma noise", float, apply_field("s_noise")),
-    AxisOption("KDiffusion Scheduler Type", str, apply_override("k_sched_type"), choices=lambda: [x for x in sd_samplers_kdiffusion.k_diffusion_scheduler]),
+    AxisOption("KDiffusion Scheduler Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)),
     AxisOption("KDiffusion Scheduler Sigma Min", float, apply_override("sigma_min")),
     AxisOption("KDiffusion Scheduler Sigma Max", float, apply_override("sigma_max")),
     AxisOption("KDiffusion Scheduler rho", float, apply_override("rho")),

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: [PATCH 19/21] Use automatic instead of None/default

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

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"),

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: [PATCH 20/21] 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(-)

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")),

From a69b71a37f1fd32a60fbd87beed13f4f280400bd Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Wed, 24 May 2023 20:40:37 +0800
Subject: [PATCH 21/21] use Schedule instead of Sched

---
 modules/generation_parameters_copypaste.py | 24 +++++++++++-----------
 modules/sd_samplers_kdiffusion.py          |  8 ++++----
 scripts/xyz_grid.py                        |  8 ++++----
 3 files changed, 20 insertions(+), 20 deletions(-)

diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 4f827a6f..1443c5cd 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -306,17 +306,17 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
     if "RNG" not in res:
         res["RNG"] = "GPU"
 
-    if "KDiff Sched Type" not in res:
-        res["KDiff Sched Type"] = "Automatic"
+    if "KDiff Schedule Type" not in res:
+        res["KDiff Schedule Type"] = "Automatic"
 
-    if "KDiff Sched max sigma" not in res:
-        res["KDiff Sched max sigma"] = 14.6
+    if "KDiff Schedule max sigma" not in res:
+        res["KDiff Schedule max sigma"] = 14.6
 
-    if "KDiff Sched min sigma" not in res:
-        res["KDiff Sched min sigma"] = 0.3
+    if "KDiff Schedule min sigma" not in res:
+        res["KDiff Schedule min sigma"] = 0.3
 
-    if "KDiff Sched rho" not in res:
-        res["KDiff Sched rho"] = 7.0
+    if "KDiff Schedule rho" not in res:
+        res["KDiff Schedule rho"] = 7.0
 
     return res
 
@@ -330,10 +330,10 @@ infotext_to_setting_name_mapping = [
     ('Conditional mask weight', 'inpainting_mask_weight'),
     ('Model hash', 'sd_model_checkpoint'),
     ('ENSD', 'eta_noise_seed_delta'),
-    ('KDiff Sched Type', 'k_sched_type'),
-    ('KDiff Sched max sigma', 'sigma_max'),
-    ('KDiff Sched min sigma', 'sigma_min'),
-    ('KDiff Sched rho', 'rho'),
+    ('KDiff Schedule Type', 'k_sched_type'),
+    ('KDiff Schedule max sigma', 'sigma_max'),
+    ('KDiff Schedule min sigma', 'sigma_min'),
+    ('KDiff Schedule rho', 'rho'),
     ('Noise multiplier', 'initial_noise_multiplier'),
     ('Eta', 'eta_ancestral'),
     ('Eta DDIM', 'eta_ddim'),
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index d2d172e4..9c9d9f17 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -328,18 +328,18 @@ class KDiffusionSampler:
             }
 
             sigmas_func = k_diffusion_scheduler[opts.k_sched_type]
-            p.extra_generation_params["KDiff Sched Type"] = opts.k_sched_type
+            p.extra_generation_params["KDiff Schedule Type"] = opts.k_sched_type
 
             if opts.sigma_min != 0.3:
                 # take 0.0 as model default
                 sigmas_kwargs['sigma_min'] = opts.sigma_min or m_sigma_min
-                p.extra_generation_params["KDiff Sched min sigma"] = opts.sigma_min
+                p.extra_generation_params["KDiff Schedule min sigma"] = opts.sigma_min
             if opts.sigma_max != 14.6:
                 sigmas_kwargs['sigma_max'] = opts.sigma_max or m_sigma_max
-                p.extra_generation_params["KDiff Sched max sigma"] = opts.sigma_max
+                p.extra_generation_params["KDiff Schedule max sigma"] = opts.sigma_max
             if opts.k_sched_type != 'exponential':
                 sigmas_kwargs['rho'] = opts.rho
-                p.extra_generation_params["KDiff Sched rho"] = opts.rho
+                p.extra_generation_params["KDiff Schedule rho"] = opts.rho
 
             sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device)
         elif self.config is not None and self.config.options.get('scheduler', None) == 'karras':
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 41fc2107..089d375e 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -220,10 +220,10 @@ axis_options = [
     AxisOption("Sigma min", float, apply_field("s_tmin")),
     AxisOption("Sigma max", float, apply_field("s_tmax")),
     AxisOption("Sigma noise", float, apply_field("s_noise")),
-    AxisOption("KDiff Sched Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)),
-    AxisOption("KDiff Sched min sigma", float, apply_override("sigma_min")),
-    AxisOption("KDiff Sched max sigma", float, apply_override("sigma_max")),
-    AxisOption("KDiff Sched rho", float, apply_override("rho")),
+    AxisOption("KDiff Schedule Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)),
+    AxisOption("KDiff Schedule min sigma", float, apply_override("sigma_min")),
+    AxisOption("KDiff Schedule max sigma", float, apply_override("sigma_max")),
+    AxisOption("KDiff Schedule rho", float, apply_override("rho")),
     AxisOption("Eta", float, apply_field("eta")),
     AxisOption("Clip skip", int, apply_clip_skip),
     AxisOption("Denoising", float, apply_field("denoising_strength")),