ComfyUI Node: Merge many sigmas by average

Merge many sigmas by average:

The "Merge many sigmas by average" node is designed to combine multiple sigma tensors by calculating their average. This node is particularly useful in scenarios where you have multiple sigma values and you want to derive a single, averaged sigma tensor from them. By averaging the sigmas, you can achieve a more balanced and representative sigma value, which can be beneficial for various sampling and scheduling tasks in AI art generation. This node simplifies the process of merging multiple sigma inputs, ensuring that the resulting sigma tensor is a mean of all provided inputs, thus providing a consistent and smooth output.

Merge many sigmas by average Input Parameters:

sigmas_1

This is the primary sigma tensor input. It is a required parameter and must be provided for the node to function. The sigma tensor represents a set of values used in the sampling process. The node will use this tensor as the base for averaging with other optional sigma inputs.

sigmas_2 to sigmas_25

These are optional sigma tensor inputs. Each of these parameters can be provided to include additional sigma tensors in the averaging process. The more sigma tensors you provide, the more comprehensive the averaging will be. These inputs allow for flexibility in the number of sigma tensors you want to merge, ranging from 2 to 25 additional sigma tensors.

Merge many sigmas by average Output Parameters:

SIGMAS

The output is a single sigma tensor that represents the average of all provided sigma inputs. This averaged sigma tensor can be used in subsequent nodes or processes that require a sigma value. The averaging process ensures that the output sigma tensor is balanced and representative of all input sigma tensors.

Merge many sigmas by average Usage Tips:

• Ensure that all sigma inputs provided are of the same shape and type to avoid inconsistencies in the averaging process.
• Use this node when you have multiple sigma values from different sources or stages and you want to derive a single, averaged sigma value for uniformity.
• Experiment with different combinations of sigma inputs to see how the averaged output affects your sampling or scheduling tasks.

Merge many sigmas by average Common Errors and Solutions:

TypeError: expected Tensor as element 0 in argument 0, but got `<type>` instead

• Explanation: This error occurs when one or more of the provided sigma inputs are not tensors.
• Solution: Ensure that all sigma inputs are valid tensors before passing them to the node.

RuntimeError: stack expects each tensor to be equal size, but got sizes <size1> and <size2>

• Explanation: This error happens when the sigma tensors provided have different shapes or sizes.
• Solution: Verify that all sigma tensors have the same shape and size before merging them.

ValueError: No sigma inputs provided

• Explanation: This error occurs when the required sigmas_1 input is not provided.
• Solution: Make sure to provide at least the sigmas_1 input for the node to function correctly.