code: def expand(num_classes, dtype, tensor):
      e = torch.zeros(
          tensor.size(0),
          num_classes,
          dtype=dtype,
          device=torch.device("cuda"),
      )
      e = e.scatter(1, tensor.unsqueeze(1), 1.0)
      return e
  
imports: import os
  import torch
  import numpy
  from PIL import Image
  from functools import partial
  from image_classification.autoaugment import AutoaugmentImageNetPolicy
  import torchvision.datasets
  import torchvision.transforms
label_desc: Use image node_id 5 for calling a global function with example usage: expand(num_classes, dtype, tensor) and returns: e