[BugFix] Consolidate lazy stacks of non-tensors

ghstack-source-id: afb1480
Pull Request resolved: #1222

(cherry picked from commit 0b901a7)

Author: Vincent Moens

tensordict/base.py

@@ -5042,7 +5042,8 @@ def assign(
             cls = type(value)
             if issubclass(cls, torch.Tensor):
                 pass
-            elif _is_non_tensor(cls):
+            # We want to skip NonTensorStacks
+            elif _is_non_tensor(cls) and not issubclass(cls, TensorDictBase):
                 if requires_metadata:
                     metadata_dict["non_tensors"][key] = (
                         value.data,
@@ -5410,7 +5411,8 @@ def _view_and_pad(tensor):
             if non_blocking and device.type != "cuda":
                 # sync if needed
                 self._sync_all()
-            torch.cat(items, out=storage)
+            if items:
+                torch.cat(items, out=storage)
             for v, (k, oldv) in _zip_strict(
                 storage.split(flat_size), list(flat_dict.items())
             ):

test/test_tensordict.py

@@ -11335,6 +11335,17 @@ def test_stack(self, non_tensor_data):
             LazyStackedTensorDict,
         )
 
+    def test_stack_consolidate(self):
+        td = torch.stack(
+            [
+                TensorDict(a="a string", b="b string"),
+                TensorDict(a="another string", b="bnother string"),
+            ]
+        )
+        tdc = td.consolidate()
+        assert (tdc == td).all()
+        assert tdc["a"] == ["a string", "another string"]
+
     def test_assign_non_tensor(self):
         data = TensorDict({}, [1, 10])