code: def show(thing, domain=(0, 1), **kwargs):
    
    if isinstance(thing, np.ndarray):
      rank = len(thing.shape)
      if rank == 4:
        log.debug("Show is assuming rank 4 tensor to be a list of images.")
        images(thing, domain=domain, **kwargs)
      elif rank in (2, 3):
        log.debug("Show is assuming rank 2 or 3 tensor to be an image.")
        image(thing, domain=domain, **kwargs)
      else:
        log.warning("Show only supports numpy arrays of rank 2-4. Using repr().")
        print(repr(thing))
    elif isinstance(thing, (list, tuple)):
      log.debug("Show is assuming list or tuple to be a collection of images.")
      images(thing, domain=domain, **kwargs)
    else:
      log.warning("Show only supports numpy arrays so far. Using repr().")
      print(repr(thing))
docs: Display a nupmy array without having to specify what it represents.
  
    This module will attempt to infer how to display your tensor based on its
    rank, shape and dtype. rank 4 tensors will be displayed as image grids, rank
    2 and 3 tensors as images.