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The SamplerCustomAdvanced node performs advanced latent space sampling using custom noise, guidance, and sampling configurations. It processes a latent image through a guided sampling process with customizable noise generation and sigma schedules, producing both the final sampled output and a denoised version when available.

Inputs

ParameterDescriptionData TypeRequiredRange
noiseThe noise generator that provides the initial noise pattern and seed for the sampling processNOISEYes-
guiderThe guidance model that directs the sampling process toward desired outputsGUIDERYes-
samplerThe sampling algorithm that defines how the latent space is traversed during generationSAMPLERYes-
sigmasThe sigma schedule that controls the noise levels throughout the sampling stepsSIGMASYes-
latent_imageThe initial latent representation that serves as the starting point for sampling. Supports optional noise_mask for selective denoising, and optional downscale_ratio_spacial and downscale_ratio_temporal keys for advanced latent handlingLATENTYes-

Outputs

Output NameDescriptionData Type
outputThe final sampled latent representation after completing the sampling process. Any downscale_ratio_spacial or downscale_ratio_temporal keys from the input latent are removed from this outputLATENT
denoised_outputA denoised version of the output when the sampling process produces an intermediate clean prediction (x0), otherwise returns the same as the output. When available, this represents the model’s best estimate of the clean latent at each stepLATENT
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