class_docstr: This is torch, but with cat that resizes tensors to appropriate dimensions if they do not match;
  this makes it possible to create pictures with dimensions that are multiples of 8 rather than 64
code: def cat(self, tensors, *args, **kwargs):
      if len(tensors) == 2:
          a, b = tensors
          if a.shape[-2:] != b.shape[-2:]:
              a = torch.nn.functional.interpolate(
                  a, b.shape[-2:], mode="nearest"
              )
  
          tensors = (a, b)
  
      return torch.cat(tensors, *args, **kwargs)
  
file_path: stable-diffusion-webui/modules/sd_hijack_unet.py
imports: import torch
  from packaging import version
  from modules import devices
  from modules.sd_hijack_utils import CondFunc
label_desc: Use image node_id 2 for calling the TorchHijackForUnet obj's underlying member method code with example usage: obj.cat(tensors) and returns: torch