code: def test_my_conv_aggr(aggr):
      x = torch.randn(4, 8)
      edge_index = torch.tensor([[0, 1, 2, 3], [0, 0, 1, 1]])
      edge_weight = torch.randn(edge_index.size(1))
  
      conv = MyConv(8, 32, aggr=aggr)
      out = conv(x, edge_index, edge_weight)
      assert out.size() == (4, 32)
  
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 4 for calling a global function with example usage: test_my_conv_aggr(aggr) without return types