code: def lift(x, y, z, intrinsics):
      # parse intrinsics
      intrinsics = intrinsics.cuda()
      fx = intrinsics[:, 0, 0]
      fy = intrinsics[:, 1, 1]
      cx = intrinsics[:, 0, 2]
      cy = intrinsics[:, 1, 2]
      sk = intrinsics[:, 0, 1]
  
      x_lift = (
          (
              x
              - cx.unsqueeze(-1)
              + cy.unsqueeze(-1) * sk.unsqueeze(-1) / fy.unsqueeze(-1)
              - sk.unsqueeze(-1) * y / fy.unsqueeze(-1)
          )
          / fx.unsqueeze(-1)
          * z
      )
      y_lift = (y - cy.unsqueeze(-1)) / fy.unsqueeze(-1) * z
  
      # homogeneous
      return torch.stack(
          (x_lift, y_lift, z, torch.ones_like(z).cuda()), dim=-1
      )
  
file_path: insightface/reconstruction/PBIDR/code/utils/rend_util.py
imports: import numpy
  import imageio
  import skimage
  import cv2
  import torch
  from torch.nn import functional
label_desc: Use image node_id 7 for calling a global function with example usage: lift(x, y, z, intrinsics) and returns: torch