I don’t know what “the entire network and architecture will do the reshuffling” means, but would claim the importance of reshuffling the data depends on the actual batch.
I.e. if you are concatenating the images in the batch dimension, I don’t think the order matters as the batch will be processed as one input. On the other hand, if the concatenation is done in another dimension, you should check which layers “use” this dimension. E.g. if it’s the channel dimension, I would expect that conv kernels “learn” the order.