diff --git a/userbenchmark/dynamo/dynamobench/_dynamo/testing.py b/userbenchmark/dynamo/dynamobench/_dynamo/testing.py
index 8a0f95670b..b4c022e8d8 100644
--- a/userbenchmark/dynamo/dynamobench/_dynamo/testing.py
+++ b/userbenchmark/dynamo/dynamobench/_dynamo/testing.py
@@ -311,7 +311,9 @@ def _fn(*args, **kwargs):
     return _fn
 
 
-def make_test_cls_with_patches(cls, cls_prefix, fn_suffix, *patches, xfail_prop=None):
+def make_test_cls_with_patches(
+    cls, cls_prefix, fn_suffix, *patches, xfail_prop=None, decorator=lambda x: x
+):
     DummyTestClass = type(f"{cls_prefix}{cls.__name__}", cls.__bases__, {})
     DummyTestClass.__qualname__ = DummyTestClass.__name__
 
@@ -326,7 +328,7 @@ def make_test_cls_with_patches(cls, cls_prefix, fn_suffix, *patches, xfail_prop=
             new_fn.__name__ = new_name
             if xfail_prop is not None and hasattr(fn, xfail_prop):
                 new_fn = unittest.expectedFailure(new_fn)
-            setattr(DummyTestClass, new_name, new_fn)
+            setattr(DummyTestClass, new_name, decorator(new_fn))
         # NB: Doesn't handle slots correctly, but whatever
         elif not hasattr(DummyTestClass, name):
             setattr(DummyTestClass, name, getattr(cls, name))
diff --git a/userbenchmark/dynamo/dynamobench/common.py b/userbenchmark/dynamo/dynamobench/common.py
index 2ecadef60e..48ea0496da 100644
--- a/userbenchmark/dynamo/dynamobench/common.py
+++ b/userbenchmark/dynamo/dynamobench/common.py
@@ -75,6 +75,7 @@
         graph_break_reasons,
         maybe_enable_compiled_autograd,
     )
+import torch._functorch.config
 from torch._functorch.aot_autograd import set_model_name
 from torch._inductor import config as inductor_config, metrics
 from torch._subclasses.fake_tensor import FakeTensorMode
@@ -3155,6 +3156,11 @@ def get_example_inputs(self):
         action="store_true",
         help="Runs a dynamic shapes version of the benchmark, if available.",
     )
+    parser.add_argument(
+        "--propagate-real-tensors",
+        action="store_true",
+        help="Capture as much data dependent as you can by unsoundly propagating real tensors",
+    )
     parser.add_argument(
         "--dynamic-batch-only",
         action="store_true",
@@ -3603,6 +3609,11 @@ def run(runner, args, original_dir=None):
     if args.dynamic_shapes:
         if not args.dynamic_batch_only:
             torch._dynamo.config.assume_static_by_default = False
+    if args.propagate_real_tensors:
+        # TODO: Separate flag for data dependent
+        torch._dynamo.config.capture_scalar_outputs = True
+        torch._dynamo.config.capture_dynamic_output_shape_ops = True
+        torch._functorch.config.fake_tensor_propagate_real_tensors = True
     if args.specialize_int:
         torch._dynamo.config.specialize_int = True
     if args.ci: