diff --git a/tensorflow/python/saved_model/function_deserialization.py b/tensorflow/python/saved_model/function_deserialization.py
index e8a9514dd56..9fcffc8ccdf 100644
--- a/tensorflow/python/saved_model/function_deserialization.py
+++ b/tensorflow/python/saved_model/function_deserialization.py
@@ -93,16 +93,6 @@ def _concrete_function_callable_with(function, inputs, allow_conversion):
     flatten_inputs = nest.flatten_up_to(expected_structure, inputs)
   except (TypeError, ValueError):
     return False
-  try:
-    # Verify that no input elements were dropped during flattening.
-    repacked = nest.pack_sequence_as(expected_structure, flatten_inputs)
-    # TODO(b/129422719): Namedtuple subclasses re-created through
-    # saved_model.load don't compare equal in type to the original in
-    # assert_same_structure. Fix that and we can take out check_types=False
-    # here.
-    nest.assert_same_structure(inputs, repacked, check_types=False)
-  except (TypeError, ValueError):
-    return False
 
   for arg, expected in zip(flatten_inputs, nest.flatten(expected_structure)):
     if isinstance(expected, tensor_spec.TensorSpec):
diff --git a/tensorflow/python/util/util.cc b/tensorflow/python/util/util.cc
index 6da3fdbf945..1d0dd695d74 100644
--- a/tensorflow/python/util/util.cc
+++ b/tensorflow/python/util/util.cc
@@ -730,9 +730,9 @@ bool AssertSameStructureHelper(
 
     // We treat two different namedtuples with identical name and fields
     // as having the same type.
-    const PyObject* o1_tuple = IsNamedtuple(o1, true);
+    const PyObject* o1_tuple = IsNamedtuple(o1, false);
     if (o1_tuple == nullptr) return false;
-    const PyObject* o2_tuple = IsNamedtuple(o2, true);
+    const PyObject* o2_tuple = IsNamedtuple(o2, false);
     if (o2_tuple == nullptr) {
       Py_DECREF(o1_tuple);
       return false;