code: def test_compile_hetero_conv_graph_breaks(device):
      import torch._dynamo as dynamo
  
      data = HeteroData()
      data["a"].x = torch.randn(50, 16, device=device)
      data["b"].x = torch.randn(50, 16, device=device)
      edge_index = get_random_edge_index(50, 50, 100, device=device)
      data["a", "to", "b"].edge_index = edge_index
      data["b", "to", "a"].edge_index = edge_index.flip([0])
  
      conv = HeteroConv(
          {
              ("a", "to", "b"): SAGEConv(16, 32),
              ("b", "to", "a"): SAGEConv(16, 32),
          }
      ).to(device)
  
      explanation = dynamo.explain(conv)(
          data.x_dict, data.edge_index_dict
      )
      assert explanation.graph_break_count == 0
  
      compiled_conv = torch.compile(conv)
  
      expected = conv(data.x_dict, data.edge_index_dict)
      out = compiled_conv(data.x_dict, data.edge_index_dict)
      assert len(out) == len(expected)
      for key in expected.keys():
          assert torch.allclose(out[key], expected[key], atol=1e-6)
  
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 6 for calling a global function with example usage: test_compile_hetero_conv_graph_breaks(device) without return types