diff --git a/torch/distributed/distributed_c10d.py b/torch/distributed/distributed_c10d.py
index b0fc0e0fd98e..13a950024af9 100644
--- a/torch/distributed/distributed_c10d.py
+++ b/torch/distributed/distributed_c10d.py
@@ -1616,7 +1616,7 @@ def scatter_object_list(
             element will store the object scattered to this rank.
         scatter_object_input_list (List[Any]): List of input objects to scatter.
             Each object must be picklable. Only objects on the ``src`` rank will
-             be scattered, and the argument can be ``None`` for non-src ranks.
+            be scattered, and the argument can be ``None`` for non-src ranks.
         src (int): Source rank from which to scatter
             ``scatter_object_input_list``.
         group: (ProcessGroup, optional): The process group to work on.
@@ -1646,7 +1646,7 @@ def scatter_object_list(
             "Expected argument scatter_object_output_list to be a list of size at least 1."
         )
 
-    my_rank = get_rank()
+    my_rank = get_rank(group)
     if my_rank == src:
         tensor_list, tensor_sizes = zip(
             *[_object_to_tensor(obj) for obj in scatter_object_input_list]
diff --git a/torch/testing/_internal/distributed/distributed_test.py b/torch/testing/_internal/distributed/distributed_test.py
index 1312ac409551..897e985576c2 100644
--- a/torch/testing/_internal/distributed/distributed_test.py
+++ b/torch/testing/_internal/distributed/distributed_test.py
@@ -4278,9 +4278,10 @@ def test_scatter_object_list(self):
                 if self.rank == src_rank
                 else [None for _ in collectives_object_test_list]
             )
-            scatter_list = scatter_list[: int(os.environ["WORLD_SIZE"])]
+            world_size = dist.get_world_size()
+            scatter_list = scatter_list[: world_size]
             i = 0
-            while len(scatter_list) < int(os.environ["WORLD_SIZE"]):
+            while len(scatter_list) < world_size:
                 scatter_list.append(scatter_list[i])
                 i += 1