Preserve GrpahModule node stack trace after torch package deserializaion re-tracing (#155638)

Summary:
urrently the node.meta["stack_trace"] is not preserved when we torch package/load GraphModule, which means the original stack trace is lost. When we re-trace the packaged graph module, we just get a stack trace like fx-generated._0......

Adding the node.meta["stack_trace"] to torch packaged graph module

Test Plan:
```
buck2 run @//mode/dev-nosan fbcode//caffe2/test:package -- -r  TestPackageFX
```

Rollback Plan:

Differential Revision: D76379692

Pull Request resolved: https://github.com/pytorch/pytorch/pull/155638
Approved by: https://github.com/angelayi

test/package/test_package_fx.py

@@ -187,6 +187,27 @@ class TestPackageFX(PackageTestCase):
         input = torch.rand(2, 3)
         self.assertEqual(loaded_traced(input), traced(input))
 
+    def test_package_gm_preserve_stack_trace(self):
+        class SimpleTest(torch.nn.Module):
+            def forward(self, x):
+                return torch.relu(x + 3.0)
+
+        st = SimpleTest()
+        traced = symbolic_trace(st)
+
+        for node in traced.graph.nodes:
+            node.meta["stack_trace"] = f"test_{node.name}"
+
+        f = BytesIO()
+        with PackageExporter(f) as pe:
+            pe.save_pickle("model", "model.pkl", traced)
+
+        f.seek(0)
+        pi = PackageImporter(f)
+        loaded_traced = pi.load_pickle("model", "model.pkl")
+        for node in loaded_traced.graph.nodes:
+            self.assertEqual(f"test_{node.name}", node.meta["stack_trace"])
+
 
 if __name__ == "__main__":
     run_tests()

torch/fx/graph_module.py

@@ -204,6 +204,14 @@ def _deserialize_graph_module(
     tracer_extras = body.get("_tracer_extras", {})
     graph = KeepModules().trace(com, **tracer_extras)
 
+    # Recover node.meta["stack_trace"] after re-tracing
+    node_meta_stack_trace = body.get("_graphmodule_graph_node_meta_stack_trace", None)
+    if node_meta_stack_trace is not None:
+        del body["_graphmodule_graph_node_meta_stack_trace"]
+        for node in graph.nodes:
+            if node_meta_stack_trace.get(node.name, None) is not None:
+                node.meta["stack_trace"] = node_meta_stack_trace[node.name]
+
     # Manually set Tracer class on the reconstructed Graph, to avoid
     # referencing the private local subclass KeepModules.
     graph._tracer_cls = tracer_cls
@@ -859,6 +867,16 @@ class {module_name}(torch.nn.Module):
         dict_without_graph["_graphmodule_cls_name"] = self.__class__.__name__
         del dict_without_graph["_graph"]
 
+        # Store node.meta["stack_trace"] so we can recover them after re-tracing during deserialization
+        node_meta_stack_trace = {
+            node.name: node.meta["stack_trace"]
+            for node in self.graph.nodes
+            if "stack_trace" in node.meta
+        }
+        dict_without_graph[
+            "_graphmodule_graph_node_meta_stack_trace"
+        ] = node_meta_stack_trace
+
         generated_module_name = f"fx-generated._{exporter.get_unique_id()}"
         python_code = self.recompile()
         import_block = _format_import_block(python_code.globals, exporter.importer)