ComfyUI Node: SamplerOptions_TimestepScaling

SamplerOptions_TimestepScaling:

The SamplerOptions_TimestepScaling node is designed to enhance the flexibility and precision of the sampling process by allowing you to modify the formulas that govern the relationship between sigma and timesteps. This node is particularly useful for those who wish to experiment with different scaling methods, such as Runge-Kutta Ci values, to achieve more refined control over the sampling dynamics. By patching the t_fn and sigma_fn formulas, this node provides a mechanism to adjust the scaling of midpoints, which can lead to improved results in terms of image quality and detail. This capability is especially beneficial for AI artists looking to fine-tune their workflows to achieve specific artistic effects or to explore new creative possibilities.

SamplerOptions_TimestepScaling Input Parameters:

sampler

The sampler parameter is a required input that specifies the sampler to be used. It acts as the base component that will be modified by the node to include additional options for timestep scaling. This parameter is crucial as it determines the initial configuration upon which the scaling modifications will be applied.

t_fn_formula

The t_fn_formula parameter allows you to define a custom formula for the t_fn, which is used to calculate the relationship between sigma and timesteps. The default formula is 1/((sigma).exp()+1), and it can be modified to experiment with different scaling behaviors. This parameter supports multiline input, enabling complex formula definitions. Adjusting this formula can significantly impact the sampling process, potentially leading to different artistic outcomes.

sigma_fn_formula

The sigma_fn_formula parameter lets you specify a custom formula for the sigma_fn, which is responsible for converting timesteps back to sigma values. The default formula is ((1-t)/t).log(), and like the t_fn_formula, it supports multiline input for more intricate formula configurations. By altering this formula, you can influence the noise schedule and the overall behavior of the sampler, which can be used to achieve various artistic effects.

SamplerOptions_TimestepScaling Output Parameters:

sampler

The output sampler is the modified version of the input sampler, now equipped with additional options for timestep scaling. This output retains all the original functionalities of the input sampler but includes the custom t_fn and sigma_fn formulas specified by the user. The modified sampler can be used in subsequent nodes to generate images with the desired scaling effects, providing a tailored sampling experience.

SamplerOptions_TimestepScaling Usage Tips:

• Experiment with different t_fn_formula and sigma_fn_formula values to see how they affect the final image. Small changes can lead to significant differences in texture and detail.
• Use this node in conjunction with other sampler nodes to create a more complex and nuanced sampling pipeline, allowing for greater artistic control and experimentation.

SamplerOptions_TimestepScaling Common Errors and Solutions:

InvalidFormulaError

• Explanation: This error occurs when the provided t_fn_formula or sigma_fn_formula contains syntax errors or unsupported operations.
• Solution: Double-check the formulas for any typos or unsupported mathematical operations. Ensure that the formulas are correctly formatted and use valid mathematical expressions.

MissingSamplerError

• Explanation: This error is raised when the sampler input is not provided or is invalid.
• Solution: Ensure that a valid sampler is connected to the sampler input. Verify that the sampler is correctly configured and compatible with this node.