code: def custom_to_pil(x, process=True, mode="RGB"):
      x = x.detach().cpu()
      if process:
          x = post_process_tensor(x)
      x = x.numpy()
      if process:
          x = (255 * x).astype(np.uint8)
      x = Image.fromarray(x)
      if not x.mode == mode:
          x = x.convert(mode)
      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 3 for calling a global function with example usage: custom_to_pil(x, process, mode) and returns: x