Merge pull request #4923 from vladmandic/sampler-dropdown-separators

Sampler dropdown separators

modules/api/helpers.py

@@ -16,6 +16,8 @@ def register_upload_store(getter_fn):
 
 
 def validate_sampler_name(name):
+    if sd_samplers.is_separator(name):  # dropdown divider, not a selectable sampler
+        raise HTTPException(status_code=404, detail="Sampler not found")
     config = sd_samplers.all_samplers_map.get(name, None)
     if config is not None:
         return name

modules/postprocess/yolo.py

@@ -612,7 +612,7 @@ class YoloRestorer(Detailer):
             if tab == 'extras': # fold the standalone sampler settings into the detailer accordion; values applied per-job in make_processing, never global opts
                 from modules import sd_samplers
                 sd_samplers.set_samplers()
-                sampler_choices = [s.name for s in sd_samplers.samplers if s.name != 'Same as primary']
+                sampler_choices = [s.name for s in sd_samplers.visible_samplers() if s.name != 'Same as primary']
                 with gr.Accordion('Sampler', open=False, elem_id=f"{tab}_detailer_sampler_accordion", elem_classes=["small-accordion"]):
                     with gr.Row():
                         d_sampler = gr.Dropdown(label='Sampling method', choices=sampler_choices, value='Default', elem_id=f"{tab}_detailer_sampler")

modules/processing_helpers.py

@@ -162,6 +162,8 @@ def get_sampler_name(sampler_index: int | None = None, img: bool = False) -> str
     else:
         sampler_name = "Default"
         log.warning(f'Sampler not found: index={sampler_index} available={[s.name for s in sd_samplers.samplers]} fallback={sampler_name}')
+    if sd_samplers.is_separator(sampler_name):  # divider row selected, treat as Default
+        sampler_name = "Default"
     if img and sampler_name == "PLMS":
         sampler_name = "Default"
         log.warning(f'Sampler not compatible: name=PLMS fallback={sampler_name}')

modules/sd_samplers.py

@@ -13,6 +13,15 @@ samplers_map = {}
 loaded_config = None
 
 
+def is_separator(name) -> bool:
+    return isinstance(name, str) and name.startswith('─')  # U+2500 box-drawing; dropdown divider rows
+
+
+def visible_samplers(img: bool = False):
+    pool = samplers_for_img2img if img else samplers
+    return [s for s in pool if not is_separator(s.name)]
+
+
 def find_sampler(name:str):
     if name is None or name == 'None':
         return all_samplers_map.get("Default", None)
@@ -66,7 +75,7 @@ def restore_default(model, requested="Default"):
 
 
 def create_sampler(name, model, scheduler_overrides=None):
-    if name is None or name == 'None':
+    if name is None or name == 'None' or is_separator(name):  # separator = dropdown divider, keep current scheduler
         return model.scheduler if model is not None else None
 
     # create default scheduler if it doesnt exist
@@ -172,6 +181,8 @@ def set_samplers():
     samplers_for_img2img = samplers
     samplers_map.clear()
     for sampler in all_samplers:
+        if is_separator(sampler.name):
+            continue
         samplers_map[sampler.name.lower()] = sampler.name
         for alias in sampler.aliases:
             samplers_map[alias.lower()] = sampler.name

modules/sd_samplers_diffusers.py

@@ -125,6 +125,7 @@ config.update({
     'DPM++ 1S': { 'solver_order': 2, 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "dpmsolver++", 'solver_type': "midpoint", 'lower_order_final': True, 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_flow_sigmas': False, 'use_beta_sigmas': False, 'final_sigmas_type': 'sigma_min' },
     'DPM++ SDE': { 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "sde-dpmsolver++", 'solver_type': "midpoint", 'lower_order_final': True, 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_flow_sigmas': False, 'use_beta_sigmas': False, 'use_lu_lambdas': False, 'final_sigmas_type': 'zero', 'timestep_spacing': 'linspace', 'solver_order': 1 },
     'DPM++ 2M SDE': { 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "sde-dpmsolver++", 'solver_type': "midpoint", 'lower_order_final': True, 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_flow_sigmas': False, 'use_beta_sigmas': False, 'use_lu_lambdas': False, 'final_sigmas_type': 'zero', 'timestep_spacing': 'linspace', 'solver_order': 2 },
+    'DPM++ 3M SDE': { 'thresholding': False, 'sample_max_value': 1.0, 'algorithm_type': "sde-dpmsolver++", 'solver_type': "midpoint", 'lower_order_final': True, 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_flow_sigmas': False, 'use_beta_sigmas': False, 'use_lu_lambdas': False, 'final_sigmas_type': 'zero', 'timestep_spacing': 'linspace', 'solver_order': 3 },
     'DPM++ 2M EDM': { 'solver_order': 2, 'solver_type': 'midpoint', 'final_sigmas_type': 'zero', 'algorithm_type': 'dpmsolver++' },
     'DPM++ Cosine': { 'solver_order': 2, 'sigma_schedule': "exponential", 'prediction_type': "v-prediction" },
     'DPM SDE': { 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_beta_sigmas': False, 'noise_sampler_seed': None, 'timestep_spacing': 'linspace', 'steps_offset': 0,  },
@@ -238,29 +239,27 @@ config.update({
 samplers_data_diffusers = [
     SamplerData('Default', None, [], {}),
 
-    SamplerData('UniPC', lambda model: DiffusionSampler('UniPC', UniPCMultistepScheduler, model), [], {}),
-    SamplerData('DDIM', lambda model: DiffusionSampler('DDIM', DDIMScheduler, model), [], {}),
+    SamplerData('── Euler ──', None, [], {}),
     SamplerData('Euler', lambda model: DiffusionSampler('Euler', EulerDiscreteScheduler, model), [], {}),
     SamplerData('Euler a', lambda model: DiffusionSampler('Euler a', EulerAncestralDiscreteScheduler, model), [], {}),
     SamplerData('Euler SGM', lambda model: DiffusionSampler('Euler SGM', EulerDiscreteScheduler, model), [], {}),
     SamplerData('Euler EDM', lambda model: DiffusionSampler('Euler EDM', EDMEulerScheduler, model), [], {}),
     SamplerData('Euler FlowMatch', lambda model: DiffusionSampler('Euler FlowMatch', FlowMatchEulerDiscreteScheduler, model), [], {}),
 
+    SamplerData('── DPM / DPM++ ──', None, [], {}),
     SamplerData('DPM++', lambda model: DiffusionSampler('DPM++', DPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM++ 2M', lambda model: DiffusionSampler('DPM++ 2M', DPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM++ 3M', lambda model: DiffusionSampler('DPM++ 3M', DPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM++ 1S', lambda model: DiffusionSampler('DPM++ 1S', DPMSolverSinglestepScheduler, model), [], {}),
     SamplerData('DPM++ SDE', lambda model: DiffusionSampler('DPM++ SDE', DPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM++ 2M SDE', lambda model: DiffusionSampler('DPM++ 2M SDE', DPMSolverMultistepScheduler, model), [], {}),
+    SamplerData('DPM++ 3M SDE', lambda model: DiffusionSampler('DPM++ 3M SDE', DPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM++ 2M EDM', lambda model: DiffusionSampler('DPM++ 2M EDM', EDMDPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM++ Cosine', lambda model: DiffusionSampler('DPM++ Cosine', CosineDPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM SDE', lambda model: DiffusionSampler('DPM SDE', DPMSolverSDEScheduler, model), [], {}),
-
     SamplerData('DPM++ Inverse', lambda model: DiffusionSampler('DPM++ Inverse', DPMSolverMultistepInverseScheduler, model), [], {}),
     SamplerData('DPM++ 2M Inverse', lambda model: DiffusionSampler('DPM++ 2M Inverse', DPMSolverMultistepInverseScheduler, model), [], {}),
     SamplerData('DPM++ 3M Inverse', lambda model: DiffusionSampler('DPM++ 3M Inverse', DPMSolverMultistepInverseScheduler, model), [], {}),
-
-    SamplerData('UniPC FlowMatch', lambda model: DiffusionSampler('UniPC FlowMatch', FlowUniPCMultistepScheduler, model), [], {}),
     SamplerData('DPM2 FlowMatch', lambda model: DiffusionSampler('DPM2 FlowMatch', FlowMatchDPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM2a FlowMatch', lambda model: DiffusionSampler('DPM2a FlowMatch', FlowMatchDPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM2++ 2M FlowMatch', lambda model: DiffusionSampler('DPM2++ 2M FlowMatch', FlowMatchDPMSolverMultistepScheduler, model), [], {}),
@@ -269,53 +268,75 @@ samplers_data_diffusers = [
     SamplerData('DPM2++ 2M SDE FlowMatch', lambda model: DiffusionSampler('DPM2++ 2M SDE FlowMatch', FlowMatchDPMSolverMultistepScheduler, model), [], {}),
     SamplerData('DPM2++ 3M SDE FlowMatch', lambda model: DiffusionSampler('DPM2++ 3M SDE FlowMatch', FlowMatchDPMSolverMultistepScheduler, model), [], {}),
 
-    SamplerData('Heun', lambda model: DiffusionSampler('Heun', HeunDiscreteScheduler, model), [], {}),
-    SamplerData('Heun FlowMatch', lambda model: DiffusionSampler('Heun FlowMatch', FlowMatchHeunDiscreteScheduler, model), [], {}),
-    SamplerData('Flash FlowMatch', lambda model: DiffusionSampler('Flash FlowMatch', FlashFlowMatchEulerDiscreteScheduler, model), [], {}),
-
+    SamplerData('── UniPC / DEIS ──', None, [], {}),
+    SamplerData('UniPC', lambda model: DiffusionSampler('UniPC', UniPCMultistepScheduler, model), [], {}),
+    SamplerData('UniPC FlowMatch', lambda model: DiffusionSampler('UniPC FlowMatch', FlowUniPCMultistepScheduler, model), [], {}),
     SamplerData('DEIS', lambda model: DiffusionSampler('DEIS', DEISMultistepScheduler, model), [], {}),
     SamplerData('SA Solver', lambda model: DiffusionSampler('SA Solver', SASolverScheduler, model), [], {}),
     SamplerData('DC Solver', lambda model: DiffusionSampler('DC Solver', DCSolverMultistepScheduler, model), [], {}),
 
-    SamplerData('DDPM', lambda model: DiffusionSampler('DDPM', DDPMScheduler, model), [], {}),
-    SamplerData('DDPM Parallel', lambda model: DiffusionSampler('DDPM Parallel', DDPMParallelScheduler, model), [], {}),
-    SamplerData('DDIM Parallel', lambda model: DiffusionSampler('DDIM Parallel', DDIMParallelScheduler, model), [], {}),
-    SamplerData('PNDM', lambda model: DiffusionSampler('PNDM', PNDMScheduler, model), [], {}),
-    SamplerData('IPNDM', lambda model: DiffusionSampler('IPNDM', IPNDMScheduler, model), [], {}),
-    SamplerData('LMSD', lambda model: DiffusionSampler('LMSD', LMSDiscreteScheduler, model), [], {}),
+    SamplerData('── Heun / KDPM2 ──', None, [], {}),
+    SamplerData('Heun', lambda model: DiffusionSampler('Heun', HeunDiscreteScheduler, model), [], {}),
+    SamplerData('Heun FlowMatch', lambda model: DiffusionSampler('Heun FlowMatch', FlowMatchHeunDiscreteScheduler, model), [], {}),
     SamplerData('KDPM2', lambda model: DiffusionSampler('KDPM2', KDPM2DiscreteScheduler, model), [], {}),
     SamplerData('KDPM2 a', lambda model: DiffusionSampler('KDPM2 a', KDPM2AncestralDiscreteScheduler, model), [], {}),
-    SamplerData('CMSI', lambda model: DiffusionSampler('CMSI', CMStochasticIterativeScheduler, model), [], {}),
 
-    SamplerData('VDM Solver', lambda model: DiffusionSampler('VDM Solver', VDMScheduler, model), [], {}),
-    SamplerData('BDIA DDIM', lambda model: DiffusionSampler('BDIA DDIM', BDIA_DDIMScheduler, model), [], {}),
+    SamplerData('── ER-SDE ──', None, [], {}),
     SamplerData('ER-SDE', lambda model: DiffusionSampler('ER-SDE', ERSDEScheduler, model), [], {}),
     SamplerData('ER-SDE 2M', lambda model: DiffusionSampler('ER-SDE 2M', ERSDEScheduler, model), [], {}),
     SamplerData('ER-SDE 3M', lambda model: DiffusionSampler('ER-SDE 3M', ERSDEScheduler, model), [], {}),
     SamplerData('ER-SDE FlowMatch', lambda model: DiffusionSampler('ER-SDE FlowMatch', ERSDEScheduler, model), [], {}),
     SamplerData('ER-SDE 2M FlowMatch', lambda model: DiffusionSampler('ER-SDE 2M FlowMatch', ERSDEScheduler, model), [], {}),
     SamplerData('ER-SDE 3M FlowMatch', lambda model: DiffusionSampler('ER-SDE 3M FlowMatch', ERSDEScheduler, model), [], {}),
+
+    SamplerData('── Classic ──', None, [], {}),
+    SamplerData('DDIM', lambda model: DiffusionSampler('DDIM', DDIMScheduler, model), [], {}),
+    SamplerData('DDIM Parallel', lambda model: DiffusionSampler('DDIM Parallel', DDIMParallelScheduler, model), [], {}),
+    SamplerData('DDPM', lambda model: DiffusionSampler('DDPM', DDPMScheduler, model), [], {}),
+    SamplerData('DDPM Parallel', lambda model: DiffusionSampler('DDPM Parallel', DDPMParallelScheduler, model), [], {}),
+    SamplerData('PNDM', lambda model: DiffusionSampler('PNDM', PNDMScheduler, model), [], {}),
+    SamplerData('IPNDM', lambda model: DiffusionSampler('IPNDM', IPNDMScheduler, model), [], {}),
+    SamplerData('LMSD', lambda model: DiffusionSampler('LMSD', LMSDiscreteScheduler, model), [], {}),
+
+    SamplerData('── Distilled ──', None, [], {}),
     SamplerData('LCM', lambda model: DiffusionSampler('LCM', LCMScheduler, model), [], {}),
     SamplerData('LCM FlowMatch', lambda model: DiffusionSampler('LCM FlowMatch', FlowMatchLCMScheduler, model), [], {}),
     SamplerData('TCD', lambda model: DiffusionSampler('TCD', TCDScheduler, model), [], {}),
     SamplerData('TDD', lambda model: DiffusionSampler('TDD', TDDScheduler, model), [], {}),
     SamplerData('PeRFlow', lambda model: DiffusionSampler('PeRFlow', PeRFlowScheduler, model), [], {}),
     SamplerData('UFOGen', lambda model: DiffusionSampler('UFOGen', UFOGenScheduler, model), [], {}),
+    SamplerData('CMSI', lambda model: DiffusionSampler('CMSI', CMStochasticIterativeScheduler, model), [], {}),
+    SamplerData('Flash FlowMatch', lambda model: DiffusionSampler('Flash FlowMatch', FlashFlowMatchEulerDiscreteScheduler, model), [], {}),
+
+    SamplerData('── Misc / Video ──', None, [], {}),
+    SamplerData('VDM Solver', lambda model: DiffusionSampler('VDM Solver', VDMScheduler, model), [], {}),
+    SamplerData('BDIA DDIM', lambda model: DiffusionSampler('BDIA DDIM', BDIA_DDIMScheduler, model), [], {}),
     SamplerData('CogX DDIM', lambda model: DiffusionSampler('CogX DDIM', CogVideoXDDIMScheduler, model), [], {}),
 
+    SamplerData('──── Res4Lyf ────', None, [], {}),
+
+    SamplerData('── ABNorsett ──', None, [], {}),
     SamplerData('ABNorsett 2M', lambda model: DiffusionSampler('ABNorsett 2M', ABNorsettScheduler, model), [], {}),
     SamplerData('ABNorsett 3M', lambda model: DiffusionSampler('ABNorsett 3M', ABNorsettScheduler, model), [], {}),
     SamplerData('ABNorsett 4M', lambda model: DiffusionSampler('ABNorsett 4M', ABNorsettScheduler, model), [], {}),
+
+    SamplerData('── Lawson ──', None, [], {}),
     SamplerData('Lawson 2S A', lambda model: DiffusionSampler('Lawson 2S A', LawsonScheduler, model), [], {}),
     SamplerData('Lawson 2S B', lambda model: DiffusionSampler('Lawson 2S B', LawsonScheduler, model), [], {}),
     SamplerData('Lawson 4S', lambda model: DiffusionSampler('Lawson 4S', LawsonScheduler, model), [], {}),
+
+    SamplerData('── ETD-RK ──', None, [], {}),
     SamplerData('ETD-RK 2S', lambda model: DiffusionSampler('ETD-RK 2S', ETDRKScheduler, model), [], {}),
     SamplerData('ETD-RK 3S A', lambda model: DiffusionSampler('ETD-RK 3S A', ETDRKScheduler, model), [], {}),
     SamplerData('ETD-RK 3S B', lambda model: DiffusionSampler('ETD-RK 3S B', ETDRKScheduler, model), [], {}),
     SamplerData('ETD-RK 4S A', lambda model: DiffusionSampler('ETD-RK 4S A', ETDRKScheduler, model), [], {}),
     SamplerData('ETD-RK 4S B', lambda model: DiffusionSampler('ETD-RK 4S B', ETDRKScheduler, model), [], {}),
+
+    SamplerData('── PEC ──', None, [], {}),
     SamplerData('PEC 423', lambda model: DiffusionSampler('PEC 423', PECScheduler, model), [], {}),
     SamplerData('PEC 433', lambda model: DiffusionSampler('PEC 433', PECScheduler, model), [], {}),
+
+    SamplerData('── RES ──', None, [], {}),
     SamplerData('RES-Unified 2S', lambda model: DiffusionSampler('RES-Unified 2S', RESUnifiedScheduler, model), [], {}),
     SamplerData('RES-Unified 3S', lambda model: DiffusionSampler('RES-Unified 3S', RESUnifiedScheduler, model), [], {}),
     SamplerData('RES-Unified 2M', lambda model: DiffusionSampler('RES-Unified 2M', RESUnifiedScheduler, model), [], {}),
@@ -326,25 +347,44 @@ samplers_data_diffusers = [
     SamplerData('RES-Multistep 3M', lambda model: DiffusionSampler('RES-Multistep 3M', RESMultistepScheduler, model), [], {}),
     SamplerData('RES-SDE 2S', lambda model: DiffusionSampler('RES-SDE 2S', RESSinglestepSDEScheduler, model), [], {}),
     SamplerData('RES-SDE 3S', lambda model: DiffusionSampler('RES-SDE 3S', RESSinglestepSDEScheduler, model), [], {}),
+
+    SamplerData('── DEIS (Res4Lyf) ──', None, [], {}),
     SamplerData('DEIS-Multistep', lambda model: DiffusionSampler('DEIS-Multistep', RESDEISMultistepScheduler, model), [], {}),
     SamplerData('DEIS-Unified 1S', lambda model: DiffusionSampler('DEIS-Unified 1S', RESUnifiedScheduler, model), [], {}),
     SamplerData('DEIS-Unified 2M', lambda model: DiffusionSampler('DEIS-Unified 2M', RESUnifiedScheduler, model), [], {}),
+
+    SamplerData('── Sigma profiles ──', None, [], {}),
     SamplerData('Sigmoid Sigma', lambda model: DiffusionSampler('Sigmoid Sigma', CommonSigmaScheduler, model), [], {}),
     SamplerData('Sine Sigma', lambda model: DiffusionSampler('Sine Sigma', CommonSigmaScheduler, model), [], {}),
     SamplerData('Easing Sigma', lambda model: DiffusionSampler('Easing Sigma', CommonSigmaScheduler, model), [], {}),
     SamplerData('Arcsine Sigma', lambda model: DiffusionSampler('Arcsine Sigma', CommonSigmaScheduler, model), [], {}),
     SamplerData('Smoothstep Sigma', lambda model: DiffusionSampler('Smoothstep Sigma', CommonSigmaScheduler, model), [], {}),
-    SamplerData('Langevin Dynamics', lambda model: DiffusionSampler('Langevin Dynamics', LangevinDynamicsScheduler, model), [], {}),
+
+    SamplerData('── Riemannian Flow ──', None, [], {}),
     SamplerData('Euclidean Flow', lambda model: DiffusionSampler('Euclidean Flow', RiemannianFlowScheduler, model), [], {}),
     SamplerData('Hyperbolic Flow', lambda model: DiffusionSampler('Hyperbolic Flow', RiemannianFlowScheduler, model), [], {}),
     SamplerData('Spherical Flow', lambda model: DiffusionSampler('Spherical Flow', RiemannianFlowScheduler, model), [], {}),
     SamplerData('Lorentzian Flow', lambda model: DiffusionSampler('Lorentzian Flow', RiemannianFlowScheduler, model), [], {}),
+
+    SamplerData('── Langevin ──', None, [], {}),
+    SamplerData('Langevin Dynamics', lambda model: DiffusionSampler('Langevin Dynamics', LangevinDynamicsScheduler, model), [], {}),
+
+    SamplerData('── Linear-RK ──', None, [], {}),
     SamplerData('Linear-RK 2', lambda model: DiffusionSampler('Linear-RK 2', LinearRKScheduler, model), [], {}),
     SamplerData('Linear-RK 3', lambda model: DiffusionSampler('Linear-RK 3', LinearRKScheduler, model), [], {}),
     SamplerData('Linear-RK 4', lambda model: DiffusionSampler('Linear-RK 4', LinearRKScheduler, model), [], {}),
     SamplerData('Linear-RK Euler', lambda model: DiffusionSampler('Linear-RK Euler', LinearRKScheduler, model), [], {}),
     SamplerData('Linear-RK Heun', lambda model: DiffusionSampler('Linear-RK Heun', LinearRKScheduler, model), [], {}),
     SamplerData('Linear-RK Ralston', lambda model: DiffusionSampler('Linear-RK Ralston', LinearRKScheduler, model), [], {}),
+
+    SamplerData('── Explicit RK ──', None, [], {}),
+    SamplerData('Specialized-RK 3S', lambda model: DiffusionSampler('Specialized-RK 3S', SpecializedRKScheduler, model), [], {}),
+    SamplerData('Specialized-RK 4S', lambda model: DiffusionSampler('Specialized-RK 4S', SpecializedRKScheduler, model), [], {}),
+    SamplerData('Runge-Kutta 4/4', lambda model: DiffusionSampler('Runge-Kutta 4/4', RungeKutta44Scheduler, model), [], {}),
+    SamplerData('Runge-Kutta 5/7', lambda model: DiffusionSampler('Runge-Kutta 5/7', RungeKutta57Scheduler, model), [], {}),
+    SamplerData('Runge-Kutta 6/7', lambda model: DiffusionSampler('Runge-Kutta 6/7', RungeKutta67Scheduler, model), [], {}),
+
+    SamplerData('── Implicit RK ──', None, [], {}),
     SamplerData('Lobatto 2', lambda model: DiffusionSampler('Lobatto 2', LobattoScheduler, model), [], {}),
     SamplerData('Lobatto 3', lambda model: DiffusionSampler('Lobatto 3', LobattoScheduler, model), [], {}),
     SamplerData('Lobatto 4', lambda model: DiffusionSampler('Lobatto 4', LobattoScheduler, model), [], {}),
@@ -354,12 +394,6 @@ samplers_data_diffusers = [
     SamplerData('Gauss-Legendre 2S', lambda model: DiffusionSampler('Gauss-Legendre 2S', GaussLegendreScheduler, model), [], {}),
     SamplerData('Gauss-Legendre 3S', lambda model: DiffusionSampler('Gauss-Legendre 3S', GaussLegendreScheduler, model), [], {}),
     SamplerData('Gauss-Legendre 4S', lambda model: DiffusionSampler('Gauss-Legendre 4S', GaussLegendreScheduler, model), [], {}),
-    SamplerData('Specialized-RK 3S', lambda model: DiffusionSampler('Specialized-RK 3S', SpecializedRKScheduler, model), [], {}),
-    SamplerData('Specialized-RK 4S', lambda model: DiffusionSampler('Specialized-RK 4S', SpecializedRKScheduler, model), [], {}),
-    SamplerData('Runge-Kutta 4/4', lambda model: DiffusionSampler('Runge-Kutta 4/4', RungeKutta44Scheduler, model), [], {}),
-    SamplerData('Runge-Kutta 5/7', lambda model: DiffusionSampler('Runge-Kutta 5/7', RungeKutta57Scheduler, model), [], {}),
-    SamplerData('Runge-Kutta 6/7', lambda model: DiffusionSampler('Runge-Kutta 6/7', RungeKutta67Scheduler, model), [], {}),
-
     SamplerData('Same as primary', None, [], {}),
 ]
 

scripts/i2i_folder.py

@@ -68,7 +68,7 @@ class I2IFolderScript(scripts_manager.Script):
         with gr.Row():
             sampler_override = gr.Dropdown(
                 label="Sampler (empty = use panel)",
-                choices=[""] + [s.name for s in sd_samplers.samplers_for_img2img],
+                choices=[""] + [s.name for s in sd_samplers.visible_samplers(img=True)],
                 value="",
                 elem_id=self.elem_id("sampler_override"),
             )

scripts/xyz/xyz_grid_classes.py

@@ -218,8 +218,8 @@ axis_options = [
     AxisOption("[Process] Model args", str, apply_task_args),
     AxisOption("[Process] Processing args", str, apply_processing),
     AxisOption("[Process] Server options", str, apply_options),
-    AxisOptionTxt2Img("[Sampler] Name", str, apply_sampler, fmt=format_value_add_label, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
-    AxisOptionImg2Img("[Sampler] Name", str, apply_sampler, fmt=format_value_add_label, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers_for_img2img]),
+    AxisOptionTxt2Img("[Sampler] Name", str, apply_sampler, fmt=format_value_add_label, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.visible_samplers()]),
+    AxisOptionImg2Img("[Sampler] Name", str, apply_sampler, fmt=format_value_add_label, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.visible_samplers(img=True)]),
     AxisOption("[Sampler] Sigma method", str, apply_setting("schedulers_sigma"), choices=lambda: ['default', 'karras', 'betas', 'exponential', 'lambdas', 'flowmatch']),
     AxisOption("[Sampler] Sigma adjust", float, apply_setting("schedulers_sigma_adjust")),
     AxisOption("[Sampler] Timestep spacing", str, apply_setting("schedulers_timestep_spacing"), choices=lambda: ['default', 'linspace', 'leading', 'trailing']),
@@ -239,7 +239,7 @@ axis_options = [
     AxisOption("[Guidance] Rescale", float, apply_field("cfg_rescale")),
     AxisOption("[Guidance] Modular name", str, apply_guidance, choices=lambda: ['Default', 'CFG', 'Auto', 'Zero', 'PAG', 'APG', 'SLG', 'SEG', 'TCFG', 'FDG']),
     AxisOption("[Refine] Upscaler", str, apply_field("hr_upscaler"), cost=0.3, choices=lambda: [x.name for x in shared.sd_upscalers]),
-    AxisOption("[Refine] Sampler", str, apply_hr_sampler_name, fmt=format_value_add_label, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
+    AxisOption("[Refine] Sampler", str, apply_hr_sampler_name, fmt=format_value_add_label, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.visible_samplers()]),
     AxisOption("[Refine] Denoising strength", float, apply_field("denoising_strength")),
     AxisOption("[Refine] Hires steps", int, apply_field("hr_second_pass_steps")),
     AxisOption("[Refine] Refiner start", float, apply_field("refiner_start")),