I encountered a problem. My network is trained with tensors of size BxCx128x128, but I need to verify its image reconstruction performance with images of size 1024x1024. To make the reconstruction smooth, I need to split my input of size BxCx1024x1024 into BxCx128x128  tensors with overlap, which are then fed to the network for reconstruction. Then, the reconstructed tensors of size BxCx128x128 should be used for reconstructing the tensor of size BxCx1024x1024 by averaging the overlaping elements. Note that (Size(in)-128)/stride may be not a integer. How to use padding strategy to ensure that every element is cropped at least for one time? How to implement the process of recovering the BxCx1024x1024 tensor from overlapping BxCx128x128 tensors? Could anyone give me some suggestions? Thanks advance for your consideration.