code: def __init__(self, in_channels, out_channels, bias=True):
      super(LinearConv, self).__init__()
  
      self.in_channels = in_channels
      self.out_channels = out_channels
      self.linear = torch.nn.Linear(in_channels, out_channels, bias)
  
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 to create a new LinearConv object from inherited base classes: nn with example: obj = LinearConv(in_channels, out_channels, bias)