code: def post_process_tensor(x):
      x = torch.clamp(x, -1.0, 1.0)
      x = (x + 1.0) / 2.0
      x = x.permute(1, 2, 0)
      return x
  
file_path: transformers/examples/research_projects/vqgan-clip/img_processing.py
imports: import numpy
  import PIL
  import torch
  import torchvision.transforms
  import torchvision.transforms.functional
  from PIL import Image
label_desc: Use image node_id 4 for calling a global function with example usage: post_process_tensor(x) and returns: x