code: def gradient(self, x):
      x.requires_grad_(True)
      y = self.forward(x)[:, :1]
      d_output = torch.ones_like(
          y, requires_grad=False, device=y.device
      )
      gradients = torch.autograd.grad(
          outputs=y,
          inputs=x,
          grad_outputs=d_output,
          create_graph=True,
          retain_graph=True,
          only_inputs=True,
      )[0]
      return gradients.unsqueeze(1)
  
imports: import torch
  import torch.nn
  import numpy
  import trimesh
  import os
  from utils import rend_util
  from model.embedder import *
  from model.ray_tracing import RayTracing
  from model.sample_network import SampleNetwork
label_desc: Use image node_id 3 for calling the ImplicitNetwork obj's underlying member method code with example usage: obj.gradient(x) and returns: gradients