code: def test_copy():
      conv = MyConv(8, 32)
      conv2 = copy.copy(conv)
  
      assert conv != conv2
      assert torch.equal(conv.lin_l.weight, conv2.lin_l.weight)
      assert torch.equal(conv.lin_r.weight, conv2.lin_r.weight)
      assert conv.lin_l.weight.data_ptr == conv2.lin_l.weight.data_ptr
      assert conv.lin_r.weight.data_ptr == conv2.lin_r.weight.data_ptr
  
      conv = copy.deepcopy(conv)
      assert conv != conv2
      assert torch.equal(conv.lin_l.weight, conv2.lin_l.weight)
      assert torch.equal(conv.lin_r.weight, conv2.lin_r.weight)
      assert conv.lin_l.weight.data_ptr != conv2.lin_l.weight.data_ptr
      assert conv.lin_r.weight.data_ptr != conv2.lin_r.weight.data_ptr
  
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 8 for calling a global function with example usage: test_copy() without return types