diff --git a/tensordict/_td.py b/tensordict/_td.py
index df6804077..bd2d3142a 100644
--- a/tensordict/_td.py
+++ b/tensordict/_td.py
@@ -1062,7 +1062,7 @@ def from_dict(cls, input_dict, batch_size=None, device=None, batch_dims=None):
                 "Cannot pass both batch_size and batch_dims to `from_dict`."
             )
 
-        batch_size_set = [] if batch_size is None else batch_size
+        batch_size_set = torch.Size(()) if batch_size is None else batch_size
         for key, value in list(input_dict.items()):
             if isinstance(value, (dict,)):
                 # we don't know if another tensor of smaller size is coming
diff --git a/tensordict/nn/common.py b/tensordict/nn/common.py
index 8f02faf13..53df615aa 100644
--- a/tensordict/nn/common.py
+++ b/tensordict/nn/common.py
@@ -14,7 +14,7 @@
 import torch
 from cloudpickle import dumps as cloudpickle_dumps, loads as cloudpickle_loads
 from tensordict._td import is_tensor_collection, TensorDictBase
-from tensordict._tensordict import unravel_key_list
+from tensordict._tensordict import _unravel_key_to_tuple, unravel_key_list
 from tensordict.functional import make_tensordict
 
 from tensordict.nn.functional_modules import (
@@ -255,9 +255,7 @@ def wrapper(_self, *args: Any, **kwargs: Any) -> Any:
                 if isinstance(dest, str):
                     dest = getattr(_self, dest)
                 for key in source:
-                    expected_key = (
-                        self.separator.join(key) if isinstance(key, tuple) else key
-                    )
+                    expected_key = self.separator.join(_unravel_key_to_tuple(key))
                     if len(args):
                         tensordict_values[key] = args[0]
                         args = args[1:]