ComfyUI Node: CADS

CADS:

The CADS node is designed to enhance the noise generation process in AI models, particularly for conditioning and unconditioning steps. It introduces a controlled noise mechanism that adjusts the noise level based on specific parameters, ensuring a more refined and targeted application of noise. This node is beneficial for AI artists looking to fine-tune the noise characteristics in their models, leading to more precise and desirable outcomes in generated images. By leveraging the CADS node, you can achieve a balance between noise and signal, which is crucial for generating high-quality AI art.

CADS Input Parameters:

model

This parameter specifies the model to which the CADS node will be applied. It is essential for defining the context in which the noise adjustments will take place.

noise_scale

This parameter controls the scale of the noise applied to the model. It ranges from -5.0 to 5.0, with a default value of 0.25. Adjusting this parameter will impact the intensity of the noise, allowing you to fine-tune the noise level to achieve the desired effect.

t1

This parameter sets the lower threshold for the noise application, ranging from 0.0 to 1.0, with a default value of 0.6. It determines the point at which the noise starts to be applied, influencing the initial noise intensity.

t2

This parameter sets the upper threshold for the noise application, ranging from 0.0 to 1.0, with a default value of 0.9. It defines the point at which the noise application stops, affecting the duration and extent of the noise.

rescale

This optional parameter allows for rescaling the noise, ranging from 0.0 to 1.0, with a default value of 0.0. It helps in adjusting the noise distribution to match the desired characteristics.

start_step

This optional parameter specifies the starting step for noise application, ranging from -1 to 10000, with a default value of -1. It determines when the noise application begins in the process.

total_steps

This optional parameter defines the total number of steps for noise application, ranging from -1 to 10000, with a default value of -1. It sets the overall duration for the noise application process.

apply_to

This optional parameter determines whether the noise is applied to conditioning, unconditioning, or both. The options are "uncond", "cond", and "both". It allows for targeted noise application based on the specific needs of the model.

key

This optional parameter specifies the key for the noise target, with options "y" and "c_crossattn". It helps in identifying the target for noise application within the model.

noise_type

This optional parameter defines the type of noise to be generated, with options "normal", "uniform", and "exponential". It allows for selecting the noise distribution that best suits the desired outcome.

CADS Output Parameters:

MODEL

The output of the CADS node is the modified model with the applied noise adjustments. This output is crucial for further processing and generating refined AI art, as it incorporates the controlled noise characteristics defined by the input parameters.

CADS Usage Tips:

• Experiment with different noise_scale values to find the optimal noise intensity for your specific model and artistic goals.
• Use the t1 and t2 parameters to control the start and end points of noise application, ensuring that the noise is applied precisely where needed.
• Adjust the rescale parameter to fine-tune the noise distribution and achieve a more balanced noise effect.
• Select the appropriate apply_to option to target noise application to conditioning, unconditioning, or both, based on your model's requirements.

CADS Common Errors and Solutions:

Warning, NaNs during rescale

• Explanation: This warning indicates that NaN (Not a Number) values were encountered during the rescaling process.
• Solution: Check the rescale parameter and ensure it is set correctly. Adjust the noise parameters to avoid extreme values that could lead to NaNs.

Noise target key not found

• Explanation: This error occurs when the specified key for the noise target is not found in the model.
• Solution: Verify the key parameter and ensure it matches the available keys in the model. Use "y" or "c_crossattn" as appropriate.

Invalid noise type

• Explanation: This error indicates that an invalid noise type was specified.
• Solution: Ensure the noise_type parameter is set to one of the valid options: "normal", "uniform", or "exponential".