code: def forward(self, input, compute_grad=False):
      if self.embed_fn is not None:
          input = self.embed_fn(input)
  
      x = input
  
      for l in range(0, self.num_layers - 1):
          lin = getattr(self, "lin" + str(l))
  
          if l in self.skip_in:
              x = torch.cat([x, input], 1) / np.sqrt(2)
  
          x = lin(x)
  
          if l < self.num_layers - 2:
              x = self.softplus(x)
  
      return x
  
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 2 for calling the ImplicitNetwork obj's underlying member method code with example usage: obj.forward(input, compute_grad) and returns: x