Extensions/RES4LYF
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RES4LYF

Advanced samplers with new noise scaling math to enable SDE sampling with all publicly available native models; new unsampling/noise inversion methods and other advanced…

By ClownsharkBatwing·Created 2 years ago·Updated 17 days ago· 1,222
ClownsharkBatwing/RES4LYF
Nodes299
On cloudRunnable
CategoryRES4LYF/noise, RES4LYF/utilities
Stars1,222
Updated17 days ago

Nodes (299)

AdvancedNoise

Pick the noise your sampler starts from

RES4LYF/noise
Base64ToConditioning

Rebuild a CONDITIONING from an encoded string

RES4LYF/utilities
BongSampler

The no-fuss RES sampler drop-in

RES4LYF/samplers
CLIPTextEncodeFluxUnguided

Encode a Flux prompt without baking in guidance

RES4LYF/conditioning
ClownGuide AdaIN (HiDream)

Style transfer by matching feature statistics

RES4LYF/sampler_extensions
ClownGuide AttnInj (HiDream)

Style transfer through attention injection

RES4LYF/sampler_extensions
ClownGuide

RES4LYF's answer to img2img and ad-hoc ControlNet

RES4LYF/sampler_extensions
ClownGuide_FrequencySeparation

Apply a style guide to low or high detail bands

RES4LYF/sampler_extensions
ClownGuide Mean

Match the overall color and tone of a reference

RES4LYF/sampler_extensions
ClownGuidesAB

Drive a generation with two latent guides at once

RES4LYF/sampler_extensions
ClownGuides

Steer composition and style with guide images

RES4LYF/sampler_extensions
ClownGuide SelfRefine

Refine an image against its own estimate, no reference

RES4LYF/sampler_extensions
ClownGuides Sync

Bundle masked and unmasked latent guides for RES4LYF

RES4LYF/sampler_extensions
ClownGuides Sync_Advanced

The kitchen-sink guide behind RES4LYF faceswaps

RES4LYF/sampler_extensions
ClownGuide Style

Reference-image style transfer inside RES4LYF

RES4LYF/sampler_extensions
ClownGuide_Style_EdgeWidth

Soften scattersort seams with an edge mask

RES4LYF/sampler_extensions
ClownGuide_StyleNorm_Advanced_HiDream

Scattersort with per-component targeting

RES4LYF/sampler_extensions
ClownGuide_Style_TileSize

Tile scattersort for tighter reference adherence

RES4LYF/sampler_extensions
ClownGuides VideoAudio Mask

Mask a video by time range for guided sampling

RES4LYF/sampler_extensions
Legacy2_ClownInpaint

RES4LYF inpainting with separate masked and background guidance

RES4LYF/legacy/sampler_extensions
Legacy2_ClownInpaintSimple

The no-fuss RES4LYF inpainting node

RES4LYF/legacy/sampler_extensions
ClownModelLoader

Load model, CLIP(s) and VAE in one node with fp8 casting

RES4LYF/loaders
ClownOptions Automation

Schedule sampler parameters over time (and per frame)

RES4LYF/sampler_options
ClownOptions Combine

Merge several RES4LYF option nodes into one

RES4LYF/sampler_options
ClownOptions Cycles

Unsample-and-resample loops for refinement

RES4LYF/sampler_options
ClownOptions Detail Boost

Add detail during sampling, on a step window

RES4LYF/sampler_options
ClownOptions Extra Options

The text box for RES4LYF's hidden flags

RES4LYF/sampler_options
ClownOptions_FlowGuide

The sync_eps control for RES4LYF flow guiding

RES4LYF/sampler_options
ClownOptions Frameweights

Shape guidance across the frames of a video

RES4LYF/sampler_options
Legacy2_ClownOptions_FrameWeights

Feed a raw per-frame weight curve to RES4LYF

RES4LYF/legacy/sampler_options
ClownOptions Implicit Steps

Bongmath and implicit refinement, as an option node

RES4LYF/sampler_options
ClownOptions Latent Normalize

Rescale the latent during RES4LYF sampling

RES4LYF/sampler_options
ClownOptions Momentum

Add momentum to the RES4LYF sampling trajectory

RES4LYF/sampler_options
ClownOptions SDE

Tune the noise injection for SDE sampling

RES4LYF/sampler_options
ClownOptions SDE Mask

Add SDE noise to only part of the image

RES4LYF/sampler_options
Legacy2_ClownOptions_SDE_Noise

Feed your own latent as the SDE noise

RES4LYF/legacy/sampler_options
ClownOptions Sigma Scaling

Noise scaling and lying sigmas for RES4LYF

RES4LYF/sampler_options
ClownOptions Step Size

Overshoot control for RES4LYF samplers

RES4LYF/sampler_options
ClownOptions Swap Sampler

Switch solvers mid-denoise

RES4LYF/sampler_options
ClownOptions Tile Advanced

Tiled sampling settings for RES4LYF samplers

RES4LYF/sampler_options
ClownOptions Tile

Tiled sampling for RES4LYF

RES4LYF/sampler_options
ClownpileModelWanVideo

Torch.compile speedups for Wan video

RES4LYF/model
ClownRegionalConditioning

Different prompts for different regions

RES4LYF/conditioning
ClownRegionalConditioning2

Mask-based regional prompts, unlimited zones

RES4LYF/conditioning
ClownRegionalConditioning3

Two masked regions plus an unmasked catch-all

RES4LYF/conditioning
ClownRegionalConditioning_AB

Two prompts, two masked regions, one image

RES4LYF/conditioning
ClownRegionalConditioning_ABC

Three masked prompt regions in one image

RES4LYF/conditioning
ClownRegionalConditionings

Unlimited regional prompt zones via a bundle

RES4LYF/conditioning
Legacy2_ClownSampler

The sampler you build, from an older workflow

RES4LYF/legacy/samplers
Legacy2_ClownSamplerAdvanced

The RES4LYF sampler with every knob exposed

RES4LYF/legacy/samplers
ClownSamplerAdvanced

Every sampling knob the pack has

RES4LYF/samplers
ClownSampler

The sampler you build, not the one you run

RES4LYF/samplers
ClownSamplerSelector

Pick one solver from all 119 of them

RES4LYF/sampler_options
ClownScheduler

A sigma schedule you can shape by hand

RES4LYF/schedulers
ClownsharkChainsampler

Hand one sampler's latent to the next

RES4LYF/samplers
Legacy2_ClownsharKSampler

The all-in-one flow-matching sampler

RES4LYF/legacy/samplers
Legacy2_ClownsharKSamplerAutomation

Schedule eta and noise across the steps

RES4LYF/legacy/sampler_extensions
Legacy2_ClownsharKSamplerAutomation_Advanced

The legacy schedule bundler for the old ClownsharKSampler

RES4LYF/legacy/sampler_extensions
ClownsharKSampler

The all-in-one sampler for flow-matching models

RES4LYF/samplers
Legacy2_ClownsharKSamplerGuide

Steer a generation with a guide latent

RES4LYF/legacy/sampler_extensions
Legacy2_ClownsharKSamplerGuides

Dual guides for subject + background

RES4LYF/legacy/sampler_extensions
Legacy2_ClownsharKSamplerOptions

RES4LYF's noise settings, bundled into one legacy node

RES4LYF/legacy/sampler_extensions
ClownStyle_Attn_MMDiT

Style transfer at the attention level for Flux, SD3.5 and HiDream

RES4LYF/sampler_extensions
ClownStyle_Attn_UNet

Style transfer at the attention level for SD1.5 and SDXL

RES4LYF/sampler_extensions
ClownStyle_Block_MMDiT

Full transformer-block control for style transfer on MMDiT models

RES4LYF/sampler_extensions
ClownStyle_Block_UNet

Style transfer control at the ResBlock level for classic U-Net models

RES4LYF/sampler_extensions
ClownStyle_Boost

Push RES4LYF style transfer harder

RES4LYF/sampler_extensions
ClownStyle_MMDiT

Reference-image style transfer for Flux, SD3.5, HiDream and Chroma

RES4LYF/sampler_extensions
ClownStyle_ResBlock_UNet

Inject style at specific UNet blocks

RES4LYF/sampler_extensions
ClownStyle_SpatialBlock_UNet

Style transfer inside a U-Net's spatial transformer

RES4LYF/sampler_extensions
ClownStyle_TransformerBlock_UNet

The finest-grained style-transfer dial RES4LYF has

RES4LYF/sampler_extensions
ClownStyle_UNet

The node that actually turns a reference image into a style guide

RES4LYF/sampler_extensions
ConditioningAdd

Layer one conditioning onto another at a controlled strength

RES4LYF/conditioning
ConditioningAverageScheduler

Crossfade two prompts over the course of a run, not in one jump

RES4LYF/conditioning
ConditioningBatch4

Combine up to four conditionings in one node

RES4LYF/conditioning
ConditioningBatch8

Combine up to eight conditionings without a chain of combiners

RES4LYF/conditioning
ConditioningDownsample (T5)

Trim a bloated T5 conditioning down for speed

RES4LYF/conditioning
ConditioningOrthoCollin

An experimental T5/CLIP-weighted conditioning blend

RES4LYF/conditioning
Conditioning Recast FP64

Cast your conditioning to double precision

RES4LYF/precision
ConditioningToBase64

Dump a conditioning object out as text you can actually look at

RES4LYF/utilities
ConditioningTruncate

The fix for SD3.5's silent 77-token quality cliff

RES4LYF/conditioning
ConditioningZeroAndTruncate

The SD3.5-safe replacement for ConditioningZeroOut

RES4LYF/conditioning
Constant Scheduler

A flat (or linear) sigma ramp

RES4LYF/schedulers
CrossAttn_EraseReplace_HiDream

Erase and replace concepts in HiDream's two text encoders

advanced/conditioning
EmptyLatentImage64

A plain empty-latent source for RES4LYF workflows

RES4LYF/latents
EmptyLatentImageCustom

Empty latents for Cascade, 16-channel, and odd shapes

RES4LYF/latents
Film Grain

Kill the plasticky AI look with real grain

RES4LYF/images
FluxGuidanceDisable

Turning off Flux's baked-in guidance so real CFG works

RES4LYF/model_patches
FluxLoader

One node to load a whole Flux stack

RES4LYF/loaders
FluxOrthoCFGPatcher

Keeping real CFG from burning Flux images

RES4LYF/model_patches
Frames Concat

Stitch two image batches into one sequence

RES4LYF/images
Frames Concat Latent

Stitch two latents into one sequence

RES4LYF/latents
Frames Concat Latent Raw

Stitch two latent clips together, no re-encode

RES4LYF/latents
Frames Concat Masks

Stitching per-frame masks into RES4LYF's temporal mask

RES4LYF/masks
Frame Select

Pull one frame out of a batch

RES4LYF/images
Frame Select Latent

Pull one frame out of a batch as a latent

RES4LYF/latents
Frame Select Latent Raw

Pull one frame out as a latent

RES4LYF/latents
Frames Latent ReverseOrder

Flipping a video latent's frame order

RES4LYF/masks
Frames Masks Uninterpolate

Shrink a per-frame mask to Wan's latent frame rate

RES4LYF/masks
Frames Masks ZeroOut

Excluding a single frame from RES4LYF's temporal mask

RES4LYF/masks
Frames Slice

Trim a range of frames out of an image batch

RES4LYF/images
Frames Slice Latent

Trim video frames before the VAE decode

RES4LYF/latents
Frames Slice Latent Raw

Cutting a frame range out of a video latent

RES4LYF/latents
Frequency Separation Hard Light

Splitting detail from color, Photoshop-style

RES4LYF/images
Frequency Separation Hard Light LAB

Split detail from tone, edit, recombine

RES4LYF/images
Frequency Separation Linear Light

The gentler frequency-separation blend

RES4LYF/images
Image Channels LAB

Split an image into luminance and color

RES4LYF/images
Image Crop Location Exact

Crop by pixel coordinates, keep the paste-back data

RES4LYF/images
Image Gaussian Blur

A one-knob blur for masks and guides

RES4LYF/images
Image Get Color Swatches

Turning a flat-color layout into ordered zones

RES4LYF/images
Image Grain Add

Kill the plastic look with film grain

RES4LYF/images
Image Median Blur

Edge-friendly blur for cleanup and detail work

RES4LYF/images
Image Pair Split

Pulling two batched images back apart

RES4LYF/images
Image Repeat Tile To Size

Fill a canvas from a small tile

RES4LYF/images
Image Sharpen FS

A sharpen pass with median or gaussian character

RES4LYF/images
LatentBatch_channels

Color-grading a 4-channel latent directly

RES4LYF/latents
LatentBatch_channels_16

Channel-wise grading for Flux-style 16-channel latents

RES4LYF/latents
Latent Batcher

Turning one latent into a batch of copies

RES4LYF/latents
Latent Channels From To

Copy channel data between two latents

RES4LYF/latents
Latent Clear State Info

Wiping RES4LYF's stashed metadata off a latent

RES4LYF/latents
Latent CropGuides State Info

Keeping guide-crop bookkeeping in sync

RES4LYF/latents
Latent Display State Info

Printing what RES4LYF stashed on your latent

RES4LYF/latents
Latent Extract State Info

Read where a RES4LYF sampler left off

RES4LYF/latents
Latent Get Channel Means

Reading a latent's per-channel average

RES4LYF/latents
Latent Match Channelwise

Matching one latent's color stats to another

RES4LYF/latents
LatentNoiseBatch_fractal

Colored noise as a standalone starting point

RES4LYF/noise
LatentNoiseBatch_gaussian

Plain noise, with mean and spread under your control

RES4LYF/noise
LatentNoiseBatch_gaussian_channels

Hand-tuned starting noise, one channel at a time

RES4LYF/noise
LatentNoiseBatch_perlin

An Empty Latent Image that starts from structured noise

RES4LYF/noise
LatentNoised

Hand-control the noise you inject into a latent

RES4LYF/noise
LatentNoiseList

One latent in, a batch of noised variants out

RES4LYF/noise
Latent Normalize Channels

Fix color and contrast drift in the latent

RES4LYF/latents
LatentPhaseMagnitude

Blend two latents by structure and by texture, separately

RES4LYF/latents
LatentPhaseMagnitudeMultiply

Scale a latent's structure and texture, per channel

RES4LYF/latents
LatentPhaseMagnitudeOffset

Nudge a latent's structure and texture, per channel

RES4LYF/latents
LatentPhaseMagnitudePower

A nonlinear curve over a latent's structure and texture

RES4LYF/latents
Latent Replace State Info

Selectively overwrite a chained sampler's hidden state

RES4LYF/latents
Latent to Cuda

Move a latent onto (or off) the GPU

RES4LYF/latents
Latent to RawX

Pull the sampler's raw diffusion state out of a latent

RES4LYF/latents
Latent Transfer State Info

Reattach a chained sampler's hidden state to a new latent

RES4LYF/latents
Latent TrimVideo State Info

Trim frames off a video latent without breaking sampler state

RES4LYF/latents
Latent Upscale State Info

Scale a latent by a factor without leaving latent space

latent
LatentUpscaleWithVAE

Upscale a latent through a real VAE roundtrip

RES4LYF/latents
LayerPatcher

Patch specific transformer layers of a model at high precision

RES4LYF/patchers
Legacy_ClownSampler

The standalone SAMPLER version of RES4LYF's solver, kept for old workflows

RES4LYF/legacy/samplers
Legacy_ClownsharKSampler

The original all-in-one, with shift built in

RES4LYF/legacy/samplers
Legacy_ClownsharKSamplerGuides

Bundling img2img guidance and schedule for the old sampler

RES4LYF/legacy/samplers
Legacy_SharkSampler

The older RES4LYF sampler, kept for old workflows

RES4LYF/legacy/samplers
Linear Quadratic Advanced

The linear-quadratic schedule with real knobs

RES4LYF/schedulers
Mask Bounding Box Aspect Ratio

Crop to a mask at the ratio you want

essentials/mask
MaskEdge

Extract just the boundary of a mask, for feathering hard region edges

RES4LYF/masks
MaskFloatToBoolean

Turn a soft, grayscale mask into a hard on/off one

RES4LYF/masks
Masks From Colors

Turn a color map into region masks for regional prompting

RES4LYF/images
Masks From Color Swatches

Turn a flat-color region map into one mask per zone

RES4LYF/images
Mask Sketch

Draw a mask by hand, right inside the node

image
Masks Unpack 16

Split a mask list into sixteen wireable outputs

RES4LYF/masks
Masks Unpack 4

Split a mask list into four wireable outputs

RES4LYF/masks
Masks Unpack 8

Split a mask list into eight wireable outputs

RES4LYF/masks
MaskToggle

An on/off switch for a mask, without rewiring your graph

RES4LYF/masks
ModelSamplingAdvanced

The shift knob that actually matters on flow-matching models

RES4LYF/model_shift
ModelSamplingAdvancedResolution

Shift that scales with your image size

RES4LYF/model_shift
ModelTimestepPatcher

Set the timestep shift for flow-matching models

RES4LYF/model_shift
PrepForUnsampling

Getting your images, masks, and latents ready for RES4LYF unsampling

RES4LYF/vae
ReAuraPatcher

RES4LYF's style-transfer patch for AuraFlow

RES4LYF/model_patches
ReAuraPatcherAdvanced

Block-level control over RES4LYF's AuraFlow style patch

RES4LYF/model_patches
ReChromaPatcher

Prep a Chroma model for RES4LYF's style tricks

RES4LYF/model_patches
ReChromaPatcherAdvanced

RES4LYF's block-level style patch for Chroma

RES4LYF/model_patches
ReFluxPatcher

Turn Flux into a style/reference engine for RES4LYF

RES4LYF/model_patches
ReFluxPatcherAdvanced

RES4LYF's style/faceswap patch for Flux, block by block

RES4LYF/model_patches
ReHiDreamPatcher

RES4LYF's style-transfer patch for HiDream

RES4LYF/model_patches
ReHiDreamPatcherAdvanced

Block-level control over RES4LYF's HiDream style patch

RES4LYF/model_patches
ReLTXVPatcher

RES4LYF's style-transfer patch for LTX Video

RES4LYF/model_patches
ReLTXVPatcherAdvanced

Block-level control over RES4LYF's LTX Video style patch

RES4LYF/model_patches
ReReduxPatcher

Precision control for Flux Redux inside RES4LYF's style-transfer system

RES4LYF/model_patches
ReSD35Patcher

RES4LYF's style-transfer patch for SD3.5

RES4LYF/model_patches
ReSD35PatcherAdvanced

Block-level control over RES4LYF's SD3.5 style patch

RES4LYF/model_patches
ReSDPatcher

Enable RES4LYF's style engine on your model at high precision

RES4LYF/model_patches
ReWanPatcher

Unlock RES4LYF's Wan video features

RES4LYF/model_patches
ReWanPatcherAdvanced

Sliding-window attention for long Wan videos

RES4LYF/model_patches
Legacy2_SamplerOptions_GarbageCollection

Trade sampling speed for fewer OOM crashes

RES4LYF/legacy/sampler_extensions
Legacy2_SamplerOptions_TimestepScaling

Rewriting the sigma-to-timestep math for Runge-Kutta samplers

RES4LYF/legacy/sampler_extensions
SD35Loader

One node for SD3.5's model, CLIP, and VAE

RES4LYF/loaders
SeedGenerator

One seed, plus the next one, on demand

RES4LYF/utilities
SetImageSize

One place to set width and height, wired everywhere

RES4LYF/images
SetImageSizeWithScale

One node for a base resolution and its scaled-up counterpart

RES4LYF/images
Set Precision

Run RES4LYF sampling in float32 or float64

RES4LYF/precision
Set Precision Advanced

Casting a latent to a specific numeric precision, and inspecting all three at once

RES4LYF/precision
Set Precision Universal

Force fp16/fp32/fp64 through your sampling graph

RES4LYF/precision
SharkChainsampler

Hand a half-sampled latent to the next sampler and change the rules

RES4LYF/samplers
SharkOptions

The noise and denoise settings for RES4LYF samplers

RES4LYF/sampler_options
SharkOptions Guide Cond

Attaching independent conditioning and CFG to a RES4LYF guide

RES4LYF/sampler_options
SharkOptions Guide Conds

Separate conditioning and CFG for masked vs. unmasked regions

RES4LYF/sampler_options
SharkOptions Guider Input

Feed a custom GUIDER into a RES4LYF sampler

RES4LYF/sampler_options
SharkOptions Start Step

Chaining sampler passes without losing your place

RES4LYF/sampler_options
SharkOptions UltraCascade Latent

Set the compressed latent size for UltraCascade sampling

RES4LYF/sampler_options
SharkSampler

The node that actually runs the sampling

RES4LYF/samplers
Sigmas2 Add

Elementwise addition for two noise schedules

RES4LYF/sigmas
Sigmas2 Mult

Use one schedule as an envelope for another

RES4LYF/sigmas
Sigmas Abs

Force a noise schedule back to positive

RES4LYF/sigmas
Sigmas AdaptiveNoiseFloor

A noise floor that reacts to the schedule instead of a fixed number

RES4LYF/sigmas
Sigmas AdaptiveStep

Spend more steps where the schedule is changing fastest

RES4LYF/sigmas
Sigmas Add

Nudge every noise level in your schedule up or down

RES4LYF/sigmas
Sigmas Append

Pad extra values onto the end of a schedule

RES4LYF/sigmas
Sigmas ArcCosine

Reshape a noise schedule with an inverse-trig curve

RES4LYF/sigmas
Sigmas ArcSine

Another inverse-trig reshape for a noise schedule

RES4LYF/sigmas
Sigmas ArcTangent

The one inverse-trig reshape that doesn't need normalizing

RES4LYF/sigmas
Sigmas Attractor

Run a noise schedule through a Lorenz system

RES4LYF/sigmas
Sigmas CatmullRom

Smooth and resample a noise schedule with spline interpolation

RES4LYF/sigmas
Sigmas Chaos

Perturb a noise schedule with a classic chaotic map

RES4LYF/sigmas
Sigmas Cleanup

The hygiene node for after you've been editing sigmas by hand

RES4LYF/sigmas
Sigmas CNFInverse

Remap a schedule's timing through a flow curve

RES4LYF/sigmas
Sigmas CollatzIteration

Yes, that Collatz conjecture, applied to your noise schedule

RES4LYF/sigmas
Sigmas Concat

Glue two noise schedules end to end

RES4LYF/sigmas
Sigmas ConwaySequence

Generate a noise schedule from an integer sequence

RES4LYF/sigmas
Sigmas Count

How many steps is that schedule, actually?

RES4LYF/sigmas
Sigmas CrossProduct

The vector-math node in the sigma toolbox

RES4LYF/sigmas
Sigmas DeleteBelowFloor

Trim the tail off a noise schedule instead of clamping it

RES4LYF/sigmas
Sigmas DeleteDuplicates

Clean up a sigma schedule with repeated values

RES4LYF/sigmas
Sigmas DotProduct

Vector-math for two noise schedules, undocumented territory

RES4LYF/sigmas
Sigmas Easing

Bend a noise schedule with easing curves

RES4LYF/sigmas
Sigmas Fmod

Wrap a noise schedule into a repeating sawtooth

RES4LYF/sigmas
Sigmas Frac

Keep only the fractional part of every noise value

RES4LYF/sigmas
Sigmas From Text

Type a noise schedule by hand

RES4LYF/sigmas
Sigmas GammaBeta

Reshape a noise schedule with the gamma and beta functions

RES4LYF/sigmas
Sigmas Gaussian

Run a noise schedule through the bell curve, five different ways

RES4LYF/sigmas
Sigmas GaussianCDF

The S-curve version of a noise schedule

RES4LYF/sigmas
Sigmas GilbreathSequence

Generate a noise schedule from a number-theory conjecture about primes

RES4LYF/sigmas
Sigmas HarmonicDecay

Generate a schedule that falls off like the harmonic series

RES4LYF/sigmas
Sigmas Hyperbolic

Reshape a noise schedule with sinh, cosh, tanh and friends

RES4LYF/sigmas
Sigmas If

Pick per-step between two schedules based on a condition

RES4LYF/sigmas
Sigmas InvLerp

Turn raw sigma values into a 0-1 position within a range

RES4LYF/sigmas
Sigmas Iteration Karras

Build an up-then-down noise schedule for unsampling loops

RES4LYF/schedulers
Sigmas Iteration Polyexp

The poly-exponential sibling of the up-down chainsampler schedule

RES4LYF/schedulers
Sigmas KernelSmooth

Smooth out a jagged noise schedule

RES4LYF/sigmas
Sigmas LambertW

Reshape a schedule with the inverse of x times e^x

RES4LYF/sigmas
Sigmas LangevinDynamics

A noise schedule generated from the physics diffusion models are built on

RES4LYF/sigmas
Sigmas Lerp

Blend two noise schedules by a proportion

RES4LYF/sigmas
Sigmas LinearSine

Ripple a sine wave into your noise schedule

RES4LYF/sigmas
Sigmas Logarithm2

Compress a noise schedule with a base-2 log

RES4LYF/sigmas
Sigmas Math1

Write your own formula to generate a noise schedule

RES4LYF/sigmas
Sigmas Math3

Write your own sigma-schedule formula

RES4LYF/sigmas
Sigmas Modulus

Wrap a sigma schedule with a remainder operation

RES4LYF/sigmas
Sigmas Mult

Scale a whole noise schedule by one number

RES4LYF/sigmas
Sigmas Noise Inversion

The two schedules an unsample-then-resample pass needs

RES4LYF/sigmas
Sigmas NormalizingFlows

A schedule generator built from ML's normalizing flows

RES4LYF/sigmas
Sigmas Pad

Append a value onto a sigma schedule

RES4LYF/sigmas
Sigmas Percentile

Rescale a schedule off its typical values, not its extremes

RES4LYF/sigmas
Sigmas PersistentHomology

A schedule generator borrowed from topology

RES4LYF/sigmas
Sigmas Power

Reshape a schedule with a single exponent

RES4LYF/sigmas
SigmasPreview

Actually see the schedule you built

RES4LYF/sigmas
Sigmas QuantileNorm

Make one schedule statistically match another

RES4LYF/sigmas
Sigmas Quotient

Scale a whole schedule by one number

RES4LYF/sigmas
Sigmas ReactionDiffusion

Run a sigma schedule through a Turing-pattern simulation

RES4LYF/sigmas
Sigmas Recast

Change a sigma schedule's floating-point precision

RES4LYF/precision
Sigmas Resample

Stretch or compress a schedule to a different step count

RES4LYF/sigmas
Sigmas Rescale

Set denoise by noise level, not by slicing steps

RES4LYF/sigmas
Sigmas RiemannianFlow

Pace a schedule out with curved-space geometry

RES4LYF/sigmas
SigmasSchedulePreview

Actually see what a scheduler does to your sigmas

RES4LYF/sigmas
Sigmas SetFloor

Swap a schedule's minimum value for a different one

RES4LYF/sigmas
Sigmas Sigmoid

Reshape a noise schedule through an S-curve

RES4LYF/sigmas
Sigmas SmoothStep

Ease a schedule in and out like a graphics engineer would

RES4LYF/sigmas
Sigmas Split

Cut a noise schedule in two for chain sampling

RES4LYF/sigmas
Sigmas Split Value

Cut a noise schedule in two for two-stage sampling

RES4LYF/sigmas
Sigmas SquareRoot

Compress a schedule's high end with a square root

RES4LYF/sigmas
Sigmas Start

Take the front slice of a schedule for chained samplers

RES4LYF/sigmas
Sigmas StepwiseMultirate

Build a multi-stage schedule in one node

RES4LYF/sigmas
Sigmas TimeStep

Transform a schedule by timestep and decay

RES4LYF/sigmas
Sigmas Truncate

Cut a schedule down to its first N steps

RES4LYF/sigmas
Sigmas Unpad

Undo whatever Sigmas Pad added

RES4LYF/sigmas
Sigmas Variance Floor

Clamp steps too big for variance-locked SDE

RES4LYF/sigmas
Sigmas ZetaEta

Transform a schedule through the Riemann zeta family

RES4LYF/sigmas
StableCascade_StageB_Conditioning64

Wiring Stage C's output into Stage B

RES4LYF/conditioning
StableCascade_StageC_VAEEncode_Exact

Encoding an image into Stage C's latent space at a size you actually chose

RES4LYF/vae
StyleModelApplyStyle

RES4LYF's Flux Redux applicator, with an actual strength dial

RES4LYF/conditioning
Tan Scheduler

A tangent-shaped noise schedule you can bend

RES4LYF/schedulers
Tan Scheduler 2

Hand-shape your denoising curve

RES4LYF/schedulers
Tan Scheduler 2 Simple

Shape your own sigma curve with a tangent function

RES4LYF/schedulers
TemporalCrossAttnMask

Windowing which frames actually hear your prompt in Wan

RES4LYF/masks
TemporalMaskGenerator

The simplest way to split a Wan clip into two prompts

RES4LYF/masks
TemporalSplitAttnMask

Windowing self-attention and cross-attention separately in Wan

RES4LYF/masks
TemporalSplitAttnMask (Midframe)

Splitting self- and cross-attention at one pivot point each

RES4LYF/masks
TextBox1

A plain multiline text node for your prompts

RES4LYF/text
TextBox2

Two prompt boxes in one node, and that's the whole pitch

RES4LYF/text
TextBox3

Three multiline text boxes in one node, nothing fancier than that

RES4LYF/text
TextBoxConcatenate

Build prompts out of parts instead of retyping the whole thing

RES4LYF/text
TextConcatenate

Glue two strings together in RES4LYF

RES4LYF/text
TextLoadFile

Load a .txt off disk into your workflow

RES4LYF/text
TextShuffle

Randomize word order in a prompt, reproducibly

RES4LYF/text
TextShuffleAndTruncate

Shuffle your tags and cut the prompt to fit the encoder

RES4LYF/text
TextTruncateTokens

Know exactly what CLIP is going to cut before it cuts it

RES4LYF/text
TorchCompileModelAura

Free-ish speed for AuraFlow, if you'll eat a slow first run

RES4LYF/model_patches
TorchCompileModelFluxAdv

Torch.compile for Flux, with a scalpel instead of an on/off switch

RES4LYF/model_patches
TorchCompileModels

The generic torch.compile node for whatever doesn't have a dedicated one

RES4LYF/model_patches
TorchCompileModelSD35

Torch.compile scoped to SD3.5's MMDiT

RES4LYF/model_patches
Legacy2_UltraSharkSampler

The legacy all-in-one sampler for Stable Cascade and UltraCascade

RES4LYF/legacy/samplers/UltraCascade
UltraSharkSampler Tiled

The tiled UltraCascade sampler in RES4LYF

RES4LYF/legacy/samplers/ultracascade
UNetSave

Bake a patched model to disk so you stop re-running the merge

RES4LYF/model_merging
VAEEncodeAdvanced

Encode with resizing and masks built in

RES4LYF/vae
VAEStyleTransferLatent

The style transfer node that works across almost every model family

RES4LYF/vae
Readme

SUPERIOR SAMPLING WITH RES4LYF: THE POWER OF BONGMATH

RES_3M vs. Uni-PC (WAN). Typically only 20 steps are needed with RES samplers. Far more are needed with Uni-PC and other common samplers, and they never reach the same level of quality.

res_3m_vs_unipc_1 res_3m_vs_unipc_2

INSTALLATION

If you are using a venv, you will need to first run from within your ComfyUI folder (that contains your "venv" folder):

Linux:

source venv/bin/activate

Windows:

venv\Scripts\activate

Then, "cd" into your "custom_nodes" folder and run the following commands:

git clone https://github.com/ClownsharkBatwing/RES4LYF/

cd RES4LYF

If you are using a venv, run these commands:

pip install -r requirements.txt

Alternatively, if you are using the portable version of ComfyUI you will need to replace "pip" with the path to your embedded pip executable. For example, on Windows:

X:\path\to\your\comfy_portable_folder\python_embedded\Scripts\pip.exe install -r requirements.txt

IMPORTANT UPDATE INFO

The previous versions will remain available but with "Legacy" prepended to their names.

If you wish to use the sampler menu shown below, you will need to install https://github.com/rgthree/rgthree-comfy (which I highly recommend you have regardless).

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If these menus do not show up after restarting ComfyUI and refreshing the page (hit F5, not just "r") verify that these menus are enabled in the rgthree settings (click the gear in the bottom left of ComfyUI, select rgthree, and ensure "Auto Nest Subdirectories" is checked):

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NEW VERSION DOCUMENTATION

I have prepared a detailed explanation of many of the concepts of sampling with exmaples in this workflow. There's also many tips, explanations of parameters, and all of the most important nodes are laid out for you to see. Some new workflow-enhancing tricks like "chainsamplers" are demonstrated, and regional AND temporal prompting are explained (supporting Flux, HiDream, SD3.5, AuraFlow, and WAN - you can even change the conditioning on a frame-by-frame basis!).

[example_workflows/intro to clownsampling.json ](https://github.com/ClownsharkBatwing/RES4LYF/blob/main/example_workflows/intro%20to%20clownsampling.json)

intro to clownsampling

STYLE TRANSFER

Supported models: HiDream, Flux, Chroma, AuraFlow, SD1.5, SDXL, SD3.5, Stable Cascade, LTXV, and WAN. Also supported: Stable Cascade (and UltraPixel) which has an excellent understanding of style (https://github.com/ClownsharkBatwing/UltraCascade).

Currently, best results are with HiDream or Chroma, or Flux with a style lora (Flux Dev is very lacking with style knowledge). Include some mention of the style you wish to use in the prompt. (Try with the guide off to confirm the prompt is not doing the heavy lifting!)

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For example, the prompt for the below was simply "a gritty illustration of a japanese woman with traditional hair in traditional clothes". Mostly you just need to make clear whether it's supposed to be a photo or an illustration, etc. so that the conditioning isn't fighting the style guide (every model has its inherent biases).

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COMPOSITION GUIDE; OUTPUT; STYLE GUIDE

style example

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KILL FLUX BLUR (and HiDream blur)

Consecutive seeds, no cherrypicking.

antiblur

REGIONAL CONDITIONING

Unlimited zones! Over 10 zones have been used in one image before.

Currently supported models: HiDream, Flux, Chroma, SD3.5, SD1.5, SDXL, AuraFlow, and WAN.

Masks can be drawn freely, or more traditional rigid ones may be used, such as in this example:

image

ComfyUI_16020_

ComfyUI_12157_

ComfyUI_12039_

TEMPORAL CONDITIONING

Unlimited zones! Ability to change the prompt for each frame.

Currently supported models: WAN.

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temporal conditioning 09580

VIDEO 2 VIDEO EDITING

Viable with any video model, demo with WAN:

wan vid2vid compressed

PREVIOUS VERSION NODE DOCUMENTATION

At the heart of this repository is the "ClownsharKSampler", which was specifically designed to support both rectified flow and probability flow models. It features 69 different selectible samplers (44 explicit, 18 fully implicit, 7 diagonally implicit) all available in both ODE or SDE modes with 20 noise types, 9 noise scaling modes, and options for implicit Runge-Kutta sampling refinement steps. Several new explicit samplers are implemented, most notably RES_2M, RES_3S, and RES_5S. Additionally, img2img capabilities include both latent image guidance and unsampling/resampling (via new forms of rectified noise inversion).

A particular emphasis of this project has been to facilitate modulating parameters vs. time, which can facilitate large gains in image quality from the sampling process. To this end, a wide variety of sigma, latent, and noise manipulation nodes are included.

Much of this work remains experimental and is subject to further changes.

ClownSampler

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SharkSampler

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ClownsharKSampler

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This is an all-in-one sampling node designed for convenience without compromising on control or quality.

There are several key sections to the parameters which will be explained below.

INPUTS

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The only two mandatory inputs here are "model" and "latent_image".

POSITIVE and NEGATIVE: If you connect nothing to either of these inputs, the node will automatically generate null conditioning. If you are unsampling, you actually don't need to hook up any conditioning at all (and will set CFG = 1.0). In most cases, merely using the positive conditioning will suffice, unless you really need to use a specific negative prompt.

SIGMAS: If a sigmas scheduler node is connected to this input, it will override the scheduler and steps settings chosen within the node.

NOISE SETTINGS

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NOISE_TYPE_INIT: This sets the initial noise type applied to the latent image.

NOISE_TYPE_SDE: This sets the noise type used during SDE sampling. Note that SDE sampling is identical to ODE sampling in most ways - the difference is that noise is added after each step. It's like a form of carefully controlled continuous noise injection.

NOISE_MODE_SDE: This determines what method is used for scaling the amount of noise to be added based on the "eta" setting below. They are listed in order of strength of the effect.

ETA: This controls how much noise is added after each step. Note that for most of the noise modes, anything equal to or greater than 1.0 will trigger internal scaling to prevent NaN errors. The exception is the noise mode "exp" which allows for settings far above 1.0.

NOISE_SEED: Largely identical to the setting in KSampler. Set to -1 to have it increment the most recently used seed (by the workflow) by 1.

CONTROL_AFTER_GENERATE: Self-explanatory. I recommend setting to "fixed" or "increment" (as you don't have to reload the workflow to regenerate something, you can just decement it by one).

SAMPLER SETTINGS

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SAMPLER_MODE: In virtually all situations, use "standard". However, if you are unsampling, set to "unsample", and if you are resampling (the stage after unsampling), set to "resample". Both of these modes will disable noise addition within ComfyUI, which is essential for these methods to work properly.

SAMPLER_NAME: This is used similarly to the KSampler setting. This selects the explicit sampler type. Note the use of numbers and letters at the end of each sampler name: "2m, 3m, 2s, 3s, 5s, etc."

Samplers that end in "s" use substeps between each step. One ending with "2s" has two stages per step, therefore costs two model calls per step (Euler costs one - model calls are what determine inference time). "3s" would take three model calls per step, and therefore take three times as long to run as Euler. However, the increase in accuracy can be very dramatic, especially when using noise (SDE sampling). The "res" family of samplers are particularly notable (they are effectively refinements of the dpmpp family, with new, higher order, much more accurate versions implemented here).

Samplers that end in "m" are "multistep" samplers, which instead of issuing new model calls for substeps, recycle previous steps as estimations for these substeps. They're less accurate, but all run at Euler speed (one model call per step). Sometimes this can be an advantage, as multistep samplers tend to converge more linearly toward a target image. This can be useful for img2img transformations, unsampling, or when using latent image guides.

IMPLICIT_SAMPLER_NAME: This is very useful with SD3.5 Medium for improving coherence, reducing artifacts and mutations, etc. It may be difficult to use with a model like Flux unless you plan on setting up a queue of generations and walking away. It will use the explicit step type as a predictor for each of the implicit substeps, so if you choose a slow explicit sampler, you will be waiting a long time. Euler, res_2m, deis_2m, etc. will often suffice as a predictor for implicit sampling, though any sampler may be used. Try "res_5s" as your explicit sampler type, and "gauss-legendre_5s", if you wish to demonstrate your commitment to climate change (and image quality).

Setting this to "none" has the same effect as setting implicit_steps = 0.

SCHEDULER AND DENOISE SETTINGS

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These are identical in most ways to the settings by the same name in KSampler.

SCHEDULER: There is one extra sigma scheduler offered by default: "beta57" which is the beta schedule with modified parameters (alpha = 0.5, beta = 0.7).

IMPLICIT_STEPS: This controls the number of implicit steps to run. Note that it will double, triple, etc. the runtime as you increase the stepcount. Typically, gains diminish quickly after 2-3 implicit steps.

DENOISE: This is identical to the KSampler setting. Controls the amount of noise removed from the image. Note that with this method, the effect will change significantly depending on your choice of scheduler.

DENOISE_ALT: Instead of splitting the sigma schedule like "denoise", this multiplies them. The results are different, but track more closely from one scheduler to another when using the same value. This can be particularly useful for img2img workflows.

CFG: This is identical to the KSampler setting. Typically, you'll set this to 1.0 (to disable it) when using Flux, if you're using Flux guidance. However, the effect is quite nice when using dedistilled models if you use "CLIP Text Encode" without any Flux guidance, and set CFG to 3.0.

If you've never quite understood CFG, you can think of it this way. Imagine you're walking down the street and see what looks like an enticing music festival in the distance (your positive conditioning). You're on the fence about attending, but then, suddenly, a horde of pickleshark cannibals come storming out of a nearby bar (your negative conditioning). Together, the two team up to drive you toward the music festival. That's CFG.

SHIFT SETTINGS

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These are present for convenience as they are used in virtually every workflow.

SHIFT: This is the same as "shift" for the ModelSampling nodes for SD3.5, AuraFlow, etc., and is equivalent to "max_shift" for Flux. Set this value to -1 to disable setting shift (or max_shift) within the node.

BASE_SHIFT: This is only used by Flux. Set this value to -1 to disable setting base_shift within the node.

SHIFT_SCALING: This changes how the shift values are calculated. "exponential" is the default used by Flux, whereas "linear" is the default used by SD3.5 and AuraFlow. In most cases, "exponential" leads to better results, though "linear" has some niche uses.

Sampler and noise mode list

Explicit samplers

Bolded samplers are added as options to the sampler dropdown in ComyfUI (an ODE and SDE version for each).

res_2m

res_2/3/5s

deis_2/3/4m

ralston_2/3/4s

dpmpp_2/3m

dpmpp_sde_2s

dpmpp_2/3s

midpoint_2s

heun_2/3s

houwen-wray_3s

kutta_3s

ssprk3_3s

rk38_4s

rk4_4s

dormand-prince_6s

dormand-prince_13s

bogacki-shampine_7s

ddim

euler

Fully Implicit Samplers

gauss-legendre_2/3/4/5s

radau_(i/ii)a_2/3s

lobatto_iii(a/b/c/d/star)_2/3s

Diagonally Implicit Samplers

kraaijevanger_spijker_2s

qin_zhang_2s

pareschi_russo_2s

pareschi_russo_alt_2s

crouzeix_2/3s

irk_exp_diag_2s (features an exponential integrator)

PREVIOUS FLUX WORKFLOWS

TXT2IMG:

This uses my amateur cell phone lora, which is freely available (https://huggingface.co/ClownsharkBatwing/CSBW_Style/blob/main/amateurphotos_1_amateurcellphonephoto_recapt2.safetensors). It significantly reduces the plastic, blurred look of Flux Dev. image image

INPAINTING:

image image

UNSAMPLING (Dual guides with masks):

image image

PREVIOUS WORKFLOWS

THE FOLLOWING WORKFLOWS ARE FOR A PREVIOUS VERSION OF THE NODE. These will still work! You will, however, need to manually delete and recreate the sampler and guide nodes and input the settings as they appear in the screenshots. The layout of the nodes has been changed slightly. To replicate their behavior precisely, add to the new extra_options box in ClownsharKSampler: truncate_conditioning=true (if that setting was used in the screenshot for the node).

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TXT2IMG Workflow:

image

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TXT2IMG Workflow (Latent Image Guides): image

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Input image: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/txt2img%20guided%20SD35M%20input.png

TXT2IMG Workflow (Dual Guides with Masking): image

image

Input images and mask: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/txt2img%20dual%20guides%20with%20mask%20SD35M%20input1.png https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/txt2img%20dual%20guides%20with%20mask%20SD35M%20input2.png https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/txt2img%20dual%20guides%20with%20mask%20SD35M%20mask.png

IMG2IMG Workflow (Unsampling):

image

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Input image: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20unsampling%20SD35L%20input.png

IMG2IMG Workflow (Unsampling with SDXL):

image

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Input image: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20unsampling%20SDXL%20input.png

IMG2IMG Workflow (Unsampling with latent image guide):

image

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Input image: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20guided%20unsampling%20SD35M%20input.png

IMG2IMG Workflow (Unsampling with dual latent image guides and masking):

image

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Input images and mask: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20dual%20guided%20masked%20unsampling%20SD35M%20input1.png https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20dual%20guided%20masked%20unsampling%20SD35M%20input2.png https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20dual%20guided%20masked%20unsampling%20SD35M%20mask.png