1.6 KiB
1.6 KiB
TT Guided Upscale KSampler TT_GuidedUpscaleKSamplerNode
This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.
Runs guided diffusion sampling with optional latent upscaling after generation. Extends the standard Guided KSampler with a built-in upscale step.
Inputs
| Parameter | Type | Required | Description |
|---|---|---|---|
latent |
LATENT | Yes | Input latent tensor |
guider |
GUIDER | Yes | Configured Guider with conditioning |
sigmas |
SIGMAS | Yes | Noise schedule |
sampler |
SAMPLER | Yes | Sampler algorithm |
random_noise |
NOISE | Yes | Noise generator with seed |
scale_latent |
BOOLEAN | Yes | Enable latent upscaling after sampling |
scale_factor |
COMBO | No | Upscale multiplier, default 1x (advanced) |
scale_method |
COMBO | No | Interpolation method, default bicubic (advanced) |
Outputs
| Parameter | Type | Description |
|---|---|---|
SAMPLES |
LATENT | Sampled latent tensor |
Usage
Toggle scale_latent to enable upscaling after sampling. Scale factor and method are in advanced inputs. Use for hi-res fix workflows without a
separate upscale node.