ComfyUI Node: Pre CFG norm neg to pos

Pre CFG norm neg to pos:

The "Pre CFG norm neg to pos" node is designed to normalize the negative conditioning output to match the norm of the positive conditioning output in AI models. This process ensures that the negative conditioning is scaled appropriately, which can help in achieving more balanced and accurate results during the model's inference phase. By normalizing the negative conditioning, this node helps in maintaining consistency and stability in the model's outputs, especially when dealing with complex conditioning scenarios. This node is particularly useful in scenarios where the negative conditioning might otherwise overpower or underrepresent the positive conditioning, leading to skewed results.

Pre CFG norm neg to pos Input Parameters:

model

This parameter represents the AI model that will be patched with the normalization function. It is essential for the node to have access to the model to apply the necessary changes. The model parameter ensures that the node can clone and modify the model's behavior as required.

enabled

This boolean parameter determines whether the normalization function is active. When set to true, the node will perform the normalization of the negative conditioning to match the positive conditioning's norm. If set to false, the node will bypass the normalization process. The default value is true, allowing the normalization to be applied unless explicitly disabled.

Pre CFG norm neg to pos Output Parameters:

model

The output is the modified AI model with the normalization function applied. This model will now include the pre-configuration patch that normalizes the negative conditioning to match the positive conditioning's norm. This ensures that the model's inference process benefits from the balanced conditioning outputs.

Pre CFG norm neg to pos Usage Tips:

• Ensure the enabled parameter is set to true if you want the normalization to be applied. This is the default setting, but it's good to double-check.
• Use this node when you notice that the negative conditioning is disproportionately affecting the model's output compared to the positive conditioning.
• Combine this node with other pre-configuration nodes to fine-tune the model's behavior and achieve more precise results.

Pre CFG norm neg to pos Common Errors and Solutions:

"Model not provided"

• Explanation: This error occurs when the model parameter is not supplied to the node.
• Solution: Ensure that you provide a valid model to the node. Check the input connections and verify that the model is correctly passed to the node.

"Normalization not applied"

• Explanation: This error might occur if the enabled parameter is set to false.
• Solution: Verify that the enabled parameter is set to true to ensure the normalization function is active.