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
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes:
- SamplerCustom
- Reroute
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, )