code: def symbolic_trace(module):
      class Tracer(torch.fx.Tracer):
          def is_leaf_module(self, module, *args, **kwargs) -> bool:
              return isinstance(
                  module, MessagePassing
              ) or super().is_leaf_module(module, *args, **kwargs)
  
      return torch.fx.GraphModule(module, Tracer().trace(module))
  
file_path: pytorch_geometric/test/nn/test_sequential.py
imports: from collections import OrderedDict
  import torch
  import torch.fx
  from torch.nn import Dropout, Linear, ReLU
  import torch_geometric.typing
  from torch_geometric.nn import GCNConv, JumpingKnowledge, MessagePassing, SAGEConv, Sequential, global_mean_pool, to_hetero
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 3 for calling a global function with example usage: symbolic_trace(module) and returns: torch, unknown