This node allows you to easily create batches from any type of Data. This is invaluable when working with Loops as often you will have different amounts of image generations or data to process depending on the iteration. This node silently ignores any missing inputs allowing you to be conditional with your batches.
Supported Data types are Tensors (images, latents, models, etc), Lists, Tuples and Primitive data types (strings, integers, floats, etc).
When batching images, the final output size will match the dimensions of the very first input image. We recommend creating batches of a single type per node, mixing and matching different types of data into the same batch may have unexpected behavior.
HOVER OVER THE INPUTS AND OUTPUTS FOR MORE INFO.
By VykosX·Created 2 years ago·Updated 2 years ago· 147
🪟 Fallback Any Batch
input1
input2
input3
input4
input5
input6
batch
◄method_for_imageslanczos►
Category🐺 VykosX-ControlFlowUtils
Inputs (7)
Name
Type
Default
Description
method_for_images
COMBO
lanczos
Image scaling algorithm to use when creating image batches
input1opt
*
Data to join into a batch.
May be a tensor, list, tuple or primitive
input2opt
*
Data to join into a batch.
May be a tensor, list, tuple or primitive
input3opt
*
Data to join into a batch.
May be a tensor, list, tuple or primitive
input4opt
*
Data to join into a batch.
May be a tensor, list, tuple or primitive
input5opt
*
Data to join into a batch.
May be a tensor, list, tuple or primitive
input6opt
*
Data to join into a batch.
May be a tensor, list, tuple or primitive
