code: def hessian(y, xs):
      """
      Convenience method for computing hessians. Note that this is slow in high
      dimensions because computing hessians in a reverse-mode AD library like
      PyTorch is inherently slow (note the for loop).
      """
      dys = torch.autograd.grad(y, xs, create_graph=True)
      flat_dy = torch.cat([dy.reshape(-1) for dy in dys])
      H = []
      for dyi in flat_dy:
          Hi = torch.cat(
              [
                  Hij.reshape(-1)
                  for Hij in torch.autograd.grad(
                      dyi, xs, retain_graph=True
                  )
              ]
          )
          H.append(Hi)
      H = torch.stack(H)
      return H
  
label_desc: Use image node_id 1 for calling a global function with example usage: hessian(y, xs) and returns: H