SamplerDPMPP_3M_SDE

Documentation

• Class name: SamplerDPMPP_3M_SDE
• Category: sampling/custom_sampling/samplers
• Output node: False

This node provides a method to obtain a sampler specifically designed for DPM-Solver++(3M) SDE models, allowing for the generation of samples based on specified noise levels and device preferences.

Input types

Required

• eta
  • Defines the scale of the noise to be applied during the sampling process, influencing the diversity and quality of generated samples.
  • Comfy dtype: FLOAT
  • Python dtype: float
• s_noise
  • Specifies the noise scale used in the sampling process, affecting the variance of the generated samples.
  • Comfy dtype: FLOAT
  • Python dtype: float
• noise_device
  • Determines whether the sampling computations are performed on a CPU or GPU, impacting performance and efficiency.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str

Output types

• sampler
  • Comfy dtype: SAMPLER
  • Produces a sampler configured for DPM-Solver++(3M) SDE models, ready to generate samples based on the provided noise parameters.
  • Python dtype: comfy.samplers.ksampler

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class SamplerDPMPP_3M_SDE:
    @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}),
                     "noise_device": (['gpu', 'cpu'], ),
                      }
               }
    RETURN_TYPES = ("SAMPLER",)
    CATEGORY = "sampling/custom_sampling/samplers"

    FUNCTION = "get_sampler"

    def get_sampler(self, eta, s_noise, noise_device):
        if noise_device == 'cpu':
            sampler_name = "dpmpp_3m_sde"
        else:
            sampler_name = "dpmpp_3m_sde_gpu"
        sampler = comfy.samplers.ksampler(sampler_name, {"eta": eta, "s_noise": s_noise})
        return (sampler, )