diff --git a/tensordict/tensordict.py b/tensordict/tensordict.py
index a2c1962f7..d41fc6143 100644
--- a/tensordict/tensordict.py
+++ b/tensordict/tensordict.py
@@ -1249,18 +1249,20 @@ def pop(
                 ) from err
         return out
 
-    def apply_(self, fn: Callable) -> TensorDictBase:
+    def apply_(self, fn: Callable, *others) -> TensorDictBase:
         """Applies a callable to all values stored in the tensordict and re-writes them in-place.
 
         Args:
             fn (Callable): function to be applied to the tensors in the
                 tensordict.
+            *others (sequence of TensorDictBase, optional): the other
+                tensordicts to be used.
 
         Returns:
             self or a copy of self with the function applied
 
         """
-        return self.apply(fn, inplace=True)
+        return self.apply(fn, *others, inplace=True)
 
     def apply(
         self,
@@ -5844,6 +5846,38 @@ def entry_class(self, key: NestedKey) -> type:
             return LazyStackedTensorDict
         return data_type
 
+    def apply_(self, fn: Callable, *others):
+        for i, td in enumerate(self.tensordicts):
+            idx = (slice(None),) * self.stack_dim + (i,)
+            td.apply_(fn, *[other[idx] for other in others])
+        return self
+
+    def apply(
+        self,
+        fn: Callable,
+        *others: TensorDictBase,
+        batch_size: Sequence[int] | None = None,
+        device: torch.device | None = None,
+        names: Sequence[str] | None = None,
+        inplace: bool = False,
+        **constructor_kwargs,
+    ) -> TensorDictBase:
+        if inplace:
+            if any(arg for arg in (batch_size, device, names, constructor_kwargs)):
+                raise ValueError(
+                    "Cannot pass other arguments to LazyStackedTensorDict.apply when inplace=True."
+                )
+            return self.apply_(fn, *others)
+        else:
+            return super().apply(
+                fn,
+                *others,
+                batch_size=batch_size,
+                device=device,
+                names=names,
+                **constructor_kwargs,
+            )
+
     def select(
         self, *keys: str, inplace: bool = False, strict: bool = False
     ) -> LazyStackedTensorDict: