ComfyUI Node: Create Raw Sigma Schedule 🎭🅐🅓

Create Raw Sigma Schedule 🎭🅐🅓:

The ADE_RawSigmaSchedule node is designed to generate a sigma schedule based on a raw beta schedule, which is essential for controlling the noise levels during the diffusion process in AI-generated animations. This node allows you to customize the sigma schedule by specifying various parameters such as the linear start and end values, sampling method, and other advanced settings. By fine-tuning these parameters, you can achieve more precise control over the diffusion process, leading to higher quality and more consistent animation results. The node is particularly useful for AI artists looking to experiment with different noise schedules to optimize their animation outputs.

Create Raw Sigma Schedule 🎭🅐🅓 Input Parameters:

raw_beta_schedule

This parameter specifies the raw beta schedule to be used for generating the sigma schedule. It is a list of predefined beta schedules that dictate the noise levels at each step of the diffusion process. The choice of beta schedule can significantly impact the quality and characteristics of the generated animation.

linear_start

This parameter sets the starting value for the linear interpolation of the beta schedule. It controls the initial noise level in the diffusion process. The default value is 0.00085, with a minimum of 0.0 and a maximum of 1.0. Adjusting this value can help in fine-tuning the initial noise characteristics.

linear_end

This parameter sets the ending value for the linear interpolation of the beta schedule. It controls the final noise level in the diffusion process. The default value is 0.012, with a minimum of 0.0 and a maximum of 1.0. Modifying this value can help in achieving the desired noise reduction towards the end of the diffusion process.

sampling

This parameter specifies the sampling method to be used. It is a list of available sampling methods that dictate how the noise levels are applied during the diffusion process. The choice of sampling method can affect the smoothness and consistency of the generated animation.

lcm_original_timesteps

This parameter sets the number of original timesteps for the Least Common Multiple (LCM) sampling method. It is an integer value with a default of 50, a minimum of 1, and a maximum of 1000. This parameter is only relevant if the LCM sampling method is selected and helps in controlling the granularity of the noise schedule.

lcm_zsnr

This boolean parameter specifies whether to apply Zero Signal-to-Noise Ratio (ZSnR) adjustments to the sigma schedule. The default value is False. Enabling this option can help in reducing noise artifacts in the generated animation, leading to cleaner results.

Create Raw Sigma Schedule 🎭🅐🅓 Output Parameters:

SIGMA_SCHEDULE

The output of this node is a sigma schedule, which is a structured representation of the noise levels to be applied at each step of the diffusion process. This schedule is crucial for controlling the quality and characteristics of the generated animation, allowing for more precise and consistent results.

Create Raw Sigma Schedule 🎭🅐🅓 Usage Tips:

• Experiment with different raw_beta_schedule options to find the one that best suits your animation style and desired noise characteristics.
• Adjust the linear_start and linear_end values to fine-tune the initial and final noise levels, respectively, for better control over the diffusion process.
• Choose the appropriate sampling method based on the specific requirements of your animation project to achieve smoother and more consistent results.
• If using the LCM sampling method, carefully set the lcm_original_timesteps to control the granularity of the noise schedule.
• Enable the lcm_zsnr option if you encounter noise artifacts in your animations to achieve cleaner results.

Create Raw Sigma Schedule 🎭🅐🅓 Common Errors and Solutions:

Weighted Average cannot be taken of Sigma Schedules that do not have the same amount of sigmas

• Explanation: This error occurs when attempting to combine two sigma schedules that have different numbers of sigmas.
• Solution: Ensure that both sigma schedules have the same number of sigmas before attempting to combine them.

Invalid beta schedule alias

• Explanation: This error occurs when an invalid or unsupported beta schedule alias is provided.
• Solution: Verify that the raw_beta_schedule parameter is set to a valid and supported beta schedule alias from the predefined list.

Incompatible sampling method

• Explanation: This error occurs when an incompatible sampling method is selected.
• Solution: Ensure that the sampling parameter is set to a valid and supported sampling method from the available list.

LCM timesteps out of range

• Explanation: This error occurs when the lcm_original_timesteps parameter is set to a value outside the allowed range.
• Solution: Adjust the lcm_original_timesteps parameter to a value within the allowed range of 1 to 1000.

ZSnR adjustment failed

• Explanation: This error occurs when the ZSnR adjustment could not be applied to the sigma schedule.
• Solution: Ensure that the lcm_zsnr parameter is set correctly and that the sigma schedule is compatible with ZSnR adjustments.