diff --git a/tensordict/_torch_func.py b/tensordict/_torch_func.py
index 463629fa5..455f93ee4 100644
--- a/tensordict/_torch_func.py
+++ b/tensordict/_torch_func.py
@@ -423,7 +423,7 @@ def _stack(
         from tensordict.tensorclass import NonTensorData
 
         return NonTensorData._stack_non_tensor(list_of_tensordicts, dim=dim)
-    elif is_tc:
+    if is_tc:
         tc_type = type(list_of_tensordicts[0])
         list_of_tensordicts = [tc._tensordict for tc in list_of_tensordicts]
 
diff --git a/tensordict/base.py b/tensordict/base.py
index f1493e1af..79d5ab4ed 100644
--- a/tensordict/base.py
+++ b/tensordict/base.py
@@ -8559,13 +8559,13 @@ def _convert_to_tensor(
         castable = None
         if isinstance(array, (float, int, bool)):
             castable = True
-        elif isinstance(array, np.ndarray) and array.dtype.names is not None:
-            return TensorDictBase.from_struct_array(array, device=self.device)
-        elif isinstance(array, np.ndarray):
-            castable = array.dtype.kind in ("c", "i", "f", "b", "u")
         elif isinstance(array, np.bool_):
             castable = True
             array = array.item()
+        elif isinstance(array, (np.ndarray, np.number)):
+            if array.dtype.names is not None:
+                return TensorDictBase.from_struct_array(array, device=self.device)
+            castable = array.dtype.kind in ("c", "i", "f", "b", "u")
         elif isinstance(array, (list, tuple)):
             array = np.asarray(array)
             castable = array.dtype.kind in ("c", "i", "f", "b", "u")
diff --git a/test/test_tensordict.py b/test/test_tensordict.py
index 5ff085150..34c068693 100644
--- a/test/test_tensordict.py
+++ b/test/test_tensordict.py
@@ -10386,7 +10386,7 @@ def test_memmap_stack_updates(self, tmpdir):
         data = torch.stack([NonTensorData(data=0), NonTensorData(data=1)], 0)
         assert is_non_tensor(data)
         data = torch.stack([data] * 3)
-        assert is_non_tensor(data)
+        assert is_non_tensor(data), data
         data = data.clone()
         assert is_non_tensor(data)
         data.memmap_(tmpdir)