code: def test_compile(device):
      x = torch.randn(3, 8, device=device)
      edge_index = torch.tensor(
          [[0, 1, 1, 2], [1, 0, 2, 1]], device=device
      )
  
      model = GCN(8, 16, num_layers=3).to(device)
      compiled_model = torch.compile(model)
  
      expected = model(x, edge_index)
      out = compiled_model(x, edge_index)
      assert torch.allclose(out, expected, atol=1e-6)
  
imports: import os
  import os.path
  import random
  import sys
  import warnings
  import pytest
  import torch
  import torch.nn.functional
  import torch_geometric.typing
  from torch_geometric.data import Data
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import SAGEConv
  from torch_geometric.nn.models import GAT, GCN, GIN, PNA, EdgeCNN, GraphSAGE
  from torch_geometric.profile import benchmark
  from torch_geometric.testing import onlyFullTest, onlyLinux, onlyNeighborSampler, onlyOnline, withCUDA, withPackage
label_desc: Use image node_id 11 for calling a global function with example usage: test_compile(device) without return types