Add custom karras scheduler

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

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],

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())
 

modules/shared.py

@@ -47,6 +47,7 @@ ui_reorder_categories = [
     "inpaint",
     "sampler",
     "checkboxes",
+    "karras_scheduler",
     "hires_fix",
     "dimensions",
     "cfg",

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

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"),

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")),