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SamplerEulerAncestral

Documentation

  • Class name: SamplerEulerAncestral
  • Category: sampling/custom_sampling/samplers
  • Output node: False

This node provides a mechanism to generate samples using the Euler Ancestral sampling method, tailored for specific noise and step size adjustments.

Input types

Required

  • eta
    • Specifies the step size for the Euler method, influencing the granularity of the sampling process.
    • Comfy dtype: FLOAT
    • Python dtype: float
  • s_noise
    • Determines the scale of noise to be added at each step, affecting the variability of the samples.
    • Comfy dtype: FLOAT
    • Python dtype: float

Output types

  • sampler
    • Comfy dtype: SAMPLER
    • Outputs a sampler configured for Euler Ancestral sampling, ready for generating samples.
    • Python dtype: comfy.samplers.KSampler

Usage tips

  • Infra type: CPU
  • Common nodes: unknown

Source code

class SamplerEulerAncestral:
    @classmethod
    def INPUT_TYPES(s):
        return {"required":
                    {"eta": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
                     "s_noise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
                      }
               }
    RETURN_TYPES = ("SAMPLER",)
    CATEGORY = "sampling/custom_sampling/samplers"

    FUNCTION = "get_sampler"

    def get_sampler(self, eta, s_noise):
        sampler = comfy.samplers.ksampler("euler_ancestral", {"eta": eta, "s_noise": s_noise})
        return (sampler, )