code: def forward(self, g, x, *args, **kwargs):
      out = torch.zeros_like(x)
      out.requires_grad = True
      return out
  
imports: import torch
  from torch import nn
  import torch.nn.functional
  import dgl
  from dgl.nn.pytorch.conv import *
  import dgl.function
  import math
  from dgl.utils import expand_as_pair
  from dgl.nn.functional import edge_softmax
  from torch.nn import Parameter
  import torch
  from torch import Tensor
  from ..scatter_utils import *
  from typing import Optional, Tuple, Union
label_desc: Use image node_id 1 for calling the ZeroConv obj's underlying member method code with example usage: obj.forward(g, x) and returns: out