Update

[ghstack-poisoned]

tensordict/_torch_func.py

@@ -419,11 +419,11 @@ def _stack(
     if not len(list_of_tensordicts):
         raise RuntimeError("list_of_tensordicts cannot be empty")
     is_tc = any(is_tensorclass(td) for td in list_of_tensordicts)
-    if all(is_non_tensor(td) for td in list_of_tensordicts):
-        from tensordict.tensorclass import NonTensorData
+    if is_tc:
+        if all(is_non_tensor(td) for td in list_of_tensordicts):
+            from tensordict.tensorclass import NonTensorData
 
-        return NonTensorData._stack_non_tensor(list_of_tensordicts, dim=dim)
-    elif is_tc:
+            return NonTensorData._stack_non_tensor(list_of_tensordicts, dim=dim)
         tc_type = type(list_of_tensordicts[0])
         list_of_tensordicts = [tc._tensordict for tc in list_of_tensordicts]
 

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")