access .is_leaf before .grad (#1210)

thunder/core/proxies.py

@@ -1951,7 +1951,7 @@ def tensorproxy(t: torch.Tensor, /, *, name: None | str, history: None | tuple =
     dtype = dtypes.to_dtype(t.dtype)
 
     grad = None
-    if t.grad is not None:
+    if t.is_leaf and t.grad is not None:
         grad_pr = None
         if history is not None:
             attr_pr = ProvenanceRecord(inst=PseudoInst.CONSTANT, inputs=[], value="grad")

thunder/tests/test_networks.py

@@ -28,8 +28,9 @@
 all_test_executors_and_dynamo = _all_test_executors() + [DynamoThunderExecutor]
 
 
+# see https://docs.pytest.org/en/stable/how-to/capture-warnings.html#recwarn for the recwarn fixture
 @instantiate(dtypes=(thunder.float32,), executors=all_test_executors_and_dynamo)
-def test_nanogpt_complete(executor, device, dtype):
+def test_nanogpt_complete(executor, device, dtype, recwarn):
     tdtype = ttorch.to_torch_dtype(dtype)
     make = partial(make_tensor, dtype=torch.int64, device=device)
 
@@ -46,6 +47,10 @@ def test_nanogpt_complete(executor, device, dtype):
 
     assert_close(torch_result, thunder_result)
 
+    if recwarn:
+        for r in recwarn:
+            assert "The .grad attribute of a Tensor that is not a leaf Tensor is being accessed." not in str(r.message)
+
 
 # TODO Investigate grad inconsistency
 # TODO: Add float16 and bfloat16 comparison tests here and to all other tests in