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Move custom_sampling category to parent level at the root of sampling category

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This commit is contained in:
Alexis Rolland 2026-05-10 15:31:09 +08:00
parent 6140e83c5c
commit 5a3bbe78b8
9 changed files with 38 additions and 38 deletions
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4
comfy_extras/nodes_advanced_samplers.py
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@ -45,7 +45,7 @@ class SamplerLCMUpscale(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="SamplerLCMUpscale",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Float.Input("scale_ratio", default=1.0, min=0.1, max=20.0, step=0.01, advanced=True),
io.Int.Input("scale_steps", default=-1, min=-1, max=1000, step=1, advanced=True),
@ -92,7 +92,7 @@ class SamplerEulerCFGpp(io.ComfyNode):
return io.Schema(
node_id="SamplerEulerCFGpp",
display_name="SamplerEulerCFG++",
category="experimental", # "sampling/custom_sampling/samplers"
category="experimental", # "sampling/samplers"
inputs=[
io.Combo.Input("version", options=["regular", "alternative"], advanced=True),
],

2
comfy_extras/nodes_align_your_steps.py
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@ -29,7 +29,7 @@ class AlignYourStepsScheduler(io.ComfyNode):
return io.Schema(
node_id="AlignYourStepsScheduler",
search_aliases=["AYS scheduler"],
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Combo.Input("model_type", options=["SD1", "SDXL", "SVD"]),
io.Int.Input("steps", default=10, min=1, max=10000),

2
comfy_extras/nodes_ar_video.py
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@ -53,7 +53,7 @@ class SamplerARVideo(io.ComfyNode):
return io.Schema(
node_id="SamplerARVideo",
display_name="Sampler AR Video",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Int.Input(
"num_frame_per_block",

56
comfy_extras/nodes_custom_sampler.py
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@ -17,7 +17,7 @@ class BasicScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="BasicScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Model.Input("model"),
io.Combo.Input("scheduler", options=comfy.samplers.SCHEDULER_NAMES),
@ -47,7 +47,7 @@ class KarrasScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="KarrasScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
@ -69,7 +69,7 @@ class ExponentialScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="ExponentialScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
@ -90,7 +90,7 @@ class PolyexponentialScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="PolyexponentialScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
@ -112,7 +112,7 @@ class LaplaceScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="LaplaceScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
@ -136,7 +136,7 @@ class SDTurboScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SDTurboScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Model.Input("model"),
io.Int.Input("steps", default=1, min=1, max=10),
@ -160,7 +160,7 @@ class BetaSamplingScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="BetaSamplingScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Model.Input("model"),
io.Int.Input("steps", default=20, min=1, max=10000),
@ -182,7 +182,7 @@ class VPScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="VPScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("beta_d", default=19.9, min=0.0, max=5000.0, step=0.01, round=False, advanced=True), #TODO: fix default values
@ -204,7 +204,7 @@ class SplitSigmas(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SplitSigmas",
category="sampling/custom_sampling/sigmas",
category="sampling/sigmas",
inputs=[
io.Sigmas.Input("sigmas"),
io.Int.Input("step", default=0, min=0, max=10000),
@ -228,7 +228,7 @@ class SplitSigmasDenoise(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SplitSigmasDenoise",
category="sampling/custom_sampling/sigmas",
category="sampling/sigmas",
inputs=[
io.Sigmas.Input("sigmas"),
io.Float.Input("denoise", default=1.0, min=0.0, max=1.0, step=0.01),
@ -254,7 +254,7 @@ class FlipSigmas(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="FlipSigmas",
category="sampling/custom_sampling/sigmas",
category="sampling/sigmas",
inputs=[io.Sigmas.Input("sigmas")],
outputs=[io.Sigmas.Output()]
)
@ -276,7 +276,7 @@ class SetFirstSigma(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SetFirstSigma",
category="sampling/custom_sampling/sigmas",
category="sampling/sigmas",
inputs=[
io.Sigmas.Input("sigmas"),
io.Float.Input("sigma", default=136.0, min=0.0, max=20000.0, step=0.001, round=False),
@ -298,7 +298,7 @@ class ExtendIntermediateSigmas(io.ComfyNode):
return io.Schema(
node_id="ExtendIntermediateSigmas",
search_aliases=["interpolate sigmas"],
category="sampling/custom_sampling/sigmas",
category="sampling/sigmas",
inputs=[
io.Sigmas.Input("sigmas"),
io.Int.Input("steps", default=2, min=1, max=100),
@ -351,7 +351,7 @@ class SamplingPercentToSigma(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplingPercentToSigma",
category="sampling/custom_sampling/sigmas",
category="sampling/sigmas",
inputs=[
io.Model.Input("model"),
io.Float.Input("sampling_percent", default=0.0, min=0.0, max=1.0, step=0.0001),
@ -379,7 +379,7 @@ class KSamplerSelect(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="KSamplerSelect",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[io.Combo.Input("sampler_name", options=comfy.samplers.SAMPLER_NAMES)],
outputs=[io.Sampler.Output()]
)
@ -396,7 +396,7 @@ class SamplerDPMPP_3M_SDE(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplerDPMPP_3M_SDE",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
@ -421,7 +421,7 @@ class SamplerDPMPP_2M_SDE(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplerDPMPP_2M_SDE",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Combo.Input("solver_type", options=['midpoint', 'heun']),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
@ -448,7 +448,7 @@ class SamplerDPMPP_SDE(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplerDPMPP_SDE",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
@ -474,7 +474,7 @@ class SamplerDPMPP_2S_Ancestral(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplerDPMPP_2S_Ancestral",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
@ -494,7 +494,7 @@ class SamplerEulerAncestral(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplerEulerAncestral",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
@ -515,7 +515,7 @@ class SamplerEulerAncestralCFGPP(io.ComfyNode):
return io.Schema(
node_id="SamplerEulerAncestralCFGPP",
display_name="SamplerEulerAncestralCFG++",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Float.Input("eta", default=1.0, min=0.0, max=1.0, step=0.01, round=False),
io.Float.Input("s_noise", default=1.0, min=0.0, max=10.0, step=0.01, round=False),
@ -537,7 +537,7 @@ class SamplerLMS(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplerLMS",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[io.Int.Input("order", default=4, min=1, max=100, advanced=True)],
outputs=[io.Sampler.Output()]
)
@ -554,7 +554,7 @@ class SamplerDPMAdaptative(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplerDPMAdaptative",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Int.Input("order", default=3, min=2, max=3, advanced=True),
io.Float.Input("rtol", default=0.05, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
@ -585,7 +585,7 @@ class SamplerER_SDE(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="SamplerER_SDE",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Combo.Input("solver_type", options=["ER-SDE", "Reverse-time SDE", "ODE"]),
io.Int.Input("max_stage", default=3, min=1, max=3, advanced=True),
@ -623,7 +623,7 @@ class SamplerSASolver(io.ComfyNode):
return io.Schema(
node_id="SamplerSASolver",
search_aliases=["sde"],
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Model.Input("model"),
io.Float.Input("eta", default=1.0, min=0.0, max=10.0, step=0.01, round=False, advanced=True),
@ -668,7 +668,7 @@ class SamplerSEEDS2(io.ComfyNode):
return io.Schema(
node_id="SamplerSEEDS2",
search_aliases=["sde", "exp heun"],
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[
io.Combo.Input("solver_type", options=["phi_1", "phi_2"]),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, tooltip="Stochastic strength", advanced=True),
@ -899,7 +899,7 @@ class DisableNoise(io.ComfyNode):
return io.Schema(
node_id="DisableNoise",
search_aliases=["zero noise"],
category="sampling/custom_sampling/noise",
category="sampling/noise",
inputs=[],
outputs=[io.Noise.Output()]
)
@ -916,7 +916,7 @@ class RandomNoise(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="RandomNoise",
category="sampling/custom_sampling/noise",
category="sampling/noise",
inputs=[io.Int.Input("noise_seed", default=0, min=0, max=0xffffffffffffffff, control_after_generate=True)],
outputs=[io.Noise.Output()]
)

2
comfy_extras/nodes_flux.py
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@ -215,7 +215,7 @@ class Flux2Scheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="Flux2Scheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=4096),
io.Int.Input("width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=1),

2
comfy_extras/nodes_gits.py
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@ -340,7 +340,7 @@ class GITSScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="GITSScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Float.Input("coeff", default=1.20, min=0.80, max=1.50, step=0.05, advanced=True),
io.Int.Input("steps", default=10, min=2, max=1000),

2
comfy_extras/nodes_lt.py
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@ -484,7 +484,7 @@ class LTXVScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="LTXVScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("max_shift", default=2.05, min=0.0, max=100.0, step=0.01),

2
comfy_extras/nodes_optimalsteps.py
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@ -31,7 +31,7 @@ class OptimalStepsScheduler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="OptimalStepsScheduler",
category="sampling/custom_sampling/schedulers",
category="sampling/schedulers",
inputs=[
io.Combo.Input("model_type", options=["FLUX", "Wan", "Chroma"]),
io.Int.Input("steps", default=20, min=3, max=1000),

4
comfy_extras/nodes_void.py
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@ -392,7 +392,7 @@ class VOIDWarpedNoiseSource(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="VOIDWarpedNoiseSource",
category="sampling/custom_sampling/noise",
category="sampling/noise",
inputs=[
io.Latent.Input("warped_noise",
tooltip="Warped noise latent from VOIDWarpedNoise"),
@ -454,7 +454,7 @@ class VOIDSampler(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="VOIDSampler",
category="sampling/custom_sampling/samplers",
category="sampling/samplers",
inputs=[],
outputs=[io.Sampler.Output()],
)