code: def __init__(
      self,
      in_channels: Union[int, Tuple[int, int]],
      out_channels: int,
      aggr: str = "add",
  ):
      super().__init__(aggr=aggr)
  
      if isinstance(in_channels, int):
          in_channels = (in_channels, in_channels)
  
      self.lin_l = Linear(in_channels[0], out_channels)
      self.lin_r = Linear(in_channels[1], out_channels)
  
imports: import copy
  from typing import Tuple, Union
  import pytest
  import torch
  from torch import Tensor
  from torch.nn import Linear
  import torch_geometric.typing
  from torch_geometric.nn import MessagePassing, aggr
  from torch_geometric.typing import Adj, OptPairTensor, OptTensor, Size, SparseTensor
  from torch_geometric.utils import add_self_loops, scatter, spmm, to_torch_csc_tensor
label_desc: Use image node_id 1 to create a new MyConv object from inherited base classes: MessagePassing with example: obj = MyConv(in_channels, out_channels, aggr)