code: def __init__(self, out_channels):
      super().__init__(aggr="add")
      self.lin = Linear(-1, out_channels)
  
imports: import random
  import pytest
  import torch
  from torch_geometric.data import HeteroData
  from torch_geometric.datasets import FakeHeteroDataset
  from torch_geometric.nn import GATConv, GCN2Conv, GCNConv, HeteroConv, Linear, MessagePassing, SAGEConv
  from torch_geometric.profile import benchmark
  from torch_geometric.testing import get_random_edge_index, onlyLinux, withCUDA, withPackage
label_desc: Use image node_id 1 to create a new CustomConv object from inherited base classes: MessagePassing with example: obj = CustomConv(out_channels)