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The SamplerDPMAdaptative node implements an adaptive DPM (Diffusion Probabilistic Model) sampler that automatically adjusts step sizes during the sampling process. It uses tolerance-based error control to determine optimal step sizes, balancing computational efficiency with sampling accuracy. This adaptive approach helps maintain quality while potentially reducing the number of steps needed.

Inputs

ParameterDescriptionData TypeRequiredRange
orderThe order of the sampler method (default: 3)INTYes2-3
rtolRelative tolerance for error control (default: 0.05)FLOATYes0.0-100.0
atolAbsolute tolerance for error control (default: 0.0078)FLOATYes0.0-100.0
h_initInitial step size (default: 0.05)FLOATYes0.0-100.0
pcoeffProportional coefficient for step size control (default: 0.0)FLOATYes0.0-100.0
icoeffIntegral coefficient for step size control (default: 1.0)FLOATYes0.0-100.0
dcoeffDerivative coefficient for step size control (default: 0.0)FLOATYes0.0-100.0
accept_safetySafety factor for step acceptance (default: 0.81)FLOATYes0.0-100.0
etaStochasticity parameter (default: 0.0)FLOATYes0.0-100.0
s_noiseNoise scaling factor (default: 1.0)FLOATYes0.0-100.0

Outputs

Output NameDescriptionData Type
samplerReturns a configured DPM adaptive sampler instanceSAMPLER
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