diff --git a/userbenchmark/dynamo/dynamobench/_dynamo/testing.py b/userbenchmark/dynamo/dynamobench/_dynamo/testing.py
index ee7fb48d2..fc4cc3603 100644
--- a/userbenchmark/dynamo/dynamobench/_dynamo/testing.py
+++ b/userbenchmark/dynamo/dynamobench/_dynamo/testing.py
@@ -95,9 +95,7 @@ def collect_results(
     results.append(buffers)
     for example in example_inputs:
         if isinstance(example, (tuple, list)):
-            for inp in example:
-                if isinstance(inp, torch.Tensor):
-                    results.append(inp.grad)
+            results.extend(inp.grad for inp in example if isinstance(inp, torch.Tensor))
         else:
             if isinstance(example, torch.Tensor):
                 results.append(example.grad)
diff --git a/userbenchmark/dynamo/dynamobench/_dynamo/utils.py b/userbenchmark/dynamo/dynamobench/_dynamo/utils.py
index 345abcd76..9f2c7b0c9 100644
--- a/userbenchmark/dynamo/dynamobench/_dynamo/utils.py
+++ b/userbenchmark/dynamo/dynamobench/_dynamo/utils.py
@@ -1535,9 +1535,10 @@ def checkpoint_params(gm):
         rng_state = torch.clone(torch.random.get_rng_state())
         if torch.cuda.is_available():
             cuda_rng_state = torch.clone(torch.cuda.get_rng_state())
-        saved_state = []
-        for param in itertools.chain(gm.parameters(), gm.buffers()):
-            saved_state.append((param, param._version, torch.clone(param)))
+        saved_state = [
+            (param, param._version, torch.clone(param))
+            for param in itertools.chain(gm.parameters(), gm.buffers())
+        ]
 
     def restore():
         with torch.no_grad():