code: def forward(ctx, x, quality):
      lst_img = []
      for img in x:
          img = _to_pil_image(img.detach().clone().cpu())
          virtualpath = BytesIO()
          img.save(virtualpath, "JPEG", quality=quality)
          lst_img.append(_to_tensor(Image.open(virtualpath)))
      return x.new_tensor(torch.stack(lst_img))
  
file_path: advertorch/advertorch/functional.py
imports: import torch
  from torchvision import transforms
  from PIL import Image
label_desc: Use image node_id 1 for calling the JPEGEncodingDecoding obj's underlying member method code with example usage: obj.forward(ctx, x, quality) and returns: x