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KSamplerSelect

Documentation

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

The KSamplerSelect node is designed to select a specific sampler based on the provided sampler name. It abstracts the complexity of sampler selection, allowing users to easily switch between different sampling strategies for their tasks.

Input types

Required

  • sampler_name
    • Specifies the name of the sampler to be selected. This parameter determines which sampling strategy will be used, impacting the overall sampling behavior and results.
    • Comfy dtype: COMBO[STRING]
    • Python dtype: str

Output types

  • sampler
    • Comfy dtype: SAMPLER
    • Returns the selected sampler object, ready to be used for sampling tasks.
    • Python dtype: comfy.samplers.Sampler

Usage tips

Source code

class KSamplerSelect:
    @classmethod
    def INPUT_TYPES(s):
        return {"required":
                    {"sampler_name": (comfy.samplers.SAMPLER_NAMES, ),
                      }
               }
    RETURN_TYPES = ("SAMPLER",)
    CATEGORY = "sampling/custom_sampling/samplers"

    FUNCTION = "get_sampler"

    def get_sampler(self, sampler_name):
        sampler = comfy.samplers.sampler_object(sampler_name)
        return (sampler, )