SamplerCustom

Documentation

• Class name: SamplerCustom

• Category: sampling/custom_sampling

• Output node: False

The SamplerCustom node is designed to provide a flexible and customizable sampling mechanism for various applications. It enables users to select and configure different sampling strategies tailored to their specific needs, enhancing the adaptability and efficiency of the sampling process.

Input types

Parameter	Comfy dtype	Description
model	MODEL	The ‘model’ input type specifies the model to be used for sampling, playing a crucial role in determining the sampling behavior and output.
add_noise	BOOLEAN	The ‘add_noise’ input type allows users to specify whether noise should be added to the sampling process, influencing the diversity and characteristics of the generated samples.
noise_seed	INT	The ‘noise_seed’ input type provides a seed for the noise generation, ensuring reproducibility and consistency in the sampling process when adding noise.
cfg	FLOAT	The ‘cfg’ input type sets the configuration for the sampling process, allowing for fine-tuning of the sampling parameters and behavior.
positive	CONDITIONING	The ‘positive’ input type represents positive conditioning information, guiding the sampling process towards generating samples that align with specified positive attributes.
negative	CONDITIONING	The ‘negative’ input type represents negative conditioning information, steering the sampling process away from generating samples that exhibit specified negative attributes.
sampler	SAMPLER	The ‘sampler’ input type selects the specific sampling strategy to be employed, directly impacting the nature and quality of the generated samples.
sigmas	SIGMAS	The ‘sigmas’ input type defines the noise levels to be used in the sampling process, affecting the exploration of the sample space and the diversity of the output.
latent_image	LATENT	The ‘latent_image’ input type provides an initial latent image for the sampling process, serving as a starting point for sample generation.

Output types

Parameter	Comfy dtype	Description
output	LATENT	The ‘output’ represents the primary result of the sampling process, containing the generated samples.
denoised_output	LATENT	The ‘denoised_output’ represents the samples after a denoising process has been applied, potentially enhancing the clarity and quality of the generated samples.