code: def __init__(self, in_channels: int, out_channels: int):
      super().__init__()
      self.lin_src = torch.nn.Linear(in_channels, out_channels)
      self.lin_dst = torch.nn.Linear(in_channels, out_channels)
  
file_path: pytorch_geometric/test/nn/test_compile_conv.py
imports: import pytest
  import torch
  from torch import Tensor
  from torch_geometric.nn import GCNConv, SAGEConv
  from torch_geometric.profile import benchmark
  from torch_geometric.testing import onlyFullTest, onlyLinux, withCUDA, withPackage
  from torch_geometric.utils import scatter
label_desc: Use image node_id 1 to create a new MySAGEConv object from inherited base classes: torch.nn with example: obj = MySAGEConv(in_channels, out_channels)