diff --git a/torchrl/data/replay_buffers/replay_buffers.py b/torchrl/data/replay_buffers/replay_buffers.py
index 7c3a2a950a4..fafc120fe94 100644
--- a/torchrl/data/replay_buffers/replay_buffers.py
+++ b/torchrl/data/replay_buffers/replay_buffers.py
@@ -804,12 +804,13 @@ def __getstate__(self) -> Dict[str, Any]:
         return state
 
     def __setstate__(self, state: Dict[str, Any]):
+        rngstate = None
         if "_rng" in state:
-            rng = state["_rng"]
-            if rng is not None:
-                rng = torch.Generator(device=rng.device)
-                rng.set_state(rng["rng_state"])
-                state["_rng"] = rng
+            rngstate = state["_rng"]
+            if rngstate is not None:
+                rng = torch.Generator(device=rngstate.device)
+                rng.set_state(rngstate["rng_state"])
+
         if "_replay_lock_placeholder" in state:
             state.pop("_replay_lock_placeholder")
             _replay_lock = threading.RLock()
@@ -819,6 +820,8 @@ def __setstate__(self, state: Dict[str, Any]):
             _futures_lock = threading.RLock()
             state["_futures_lock"] = _futures_lock
         self.__dict__.update(state)
+        if rngstate is not None:
+            self.set_rng(rng)
 
     @property
     def sampler(self):
diff --git a/torchrl/data/replay_buffers/samplers.py b/torchrl/data/replay_buffers/samplers.py
index c34c964c808..8e9cf2d695b 100644
--- a/torchrl/data/replay_buffers/samplers.py
+++ b/torchrl/data/replay_buffers/samplers.py
@@ -108,6 +108,11 @@ def loads(self, path):
     def __repr__(self):
         return f"{self.__class__.__name__}()"
 
+    def __getstate__(self):
+        state = copy(self.__dict__)
+        state["_rng"] = None
+        return state
+
 
 class RandomSampler(Sampler):
     """A uniformly random sampler for composable replay buffers.
@@ -395,8 +400,7 @@ def __getstate__(self):
             raise RuntimeError(
                 f"Samplers of type {type(self)} cannot be shared between processes."
             )
-        state = copy(self.__dict__)
-        return state
+        return super().__getstate__()
 
     def _init(self):
         if self.dtype in (torch.float, torch.FloatType, torch.float32):
@@ -938,7 +942,7 @@ def __getstate__(self):
                 f"one process will NOT erase the cache on another process's sampler, "
                 f"which will cause synchronization issues."
             )
-        state = copy(self.__dict__)
+        state = super().__getstate__()
         state["_cache"] = {}
         return state
 
@@ -1812,6 +1816,7 @@ def __repr__(self):
     def __getstate__(self):
         state = SliceSampler.__getstate__(self)
         state.update(PrioritizedSampler.__getstate__(self))
+        return state
 
     def mark_update(
         self, index: Union[int, torch.Tensor], *, storage: Storage | None = None
diff --git a/torchrl/data/replay_buffers/storages.py b/torchrl/data/replay_buffers/storages.py
index 7c73ba4ed67..04cc63e231d 100644
--- a/torchrl/data/replay_buffers/storages.py
+++ b/torchrl/data/replay_buffers/storages.py
@@ -186,6 +186,11 @@ def load(self, *args, **kwargs):
         """Alias for :meth:`~.loads`."""
         return self.loads(*args, **kwargs)
 
+    def __getstate__(self):
+        state = copy(self.__dict__)
+        state["_rng"] = None
+        return state
+
 
 class ListStorage(Storage):
     """A storage stored in a list.
@@ -300,7 +305,7 @@ def __getstate__(self):
             raise RuntimeError(
                 f"Cannot share a storage of type {type(self)} between processes."
             )
-        state = copy(self.__dict__)
+        state = super().__getstate__()
         return state
 
     def __repr__(self):
@@ -525,7 +530,7 @@ def flatten(self):
         )
 
     def __getstate__(self):
-        state = copy(self.__dict__)
+        state = super().__getstate__()
         if get_spawning_popen() is None:
             length = self._len
             del state["_len_value"]
diff --git a/torchrl/data/replay_buffers/writers.py b/torchrl/data/replay_buffers/writers.py
index e94117153b6..066658993b1 100644
--- a/torchrl/data/replay_buffers/writers.py
+++ b/torchrl/data/replay_buffers/writers.py
@@ -104,6 +104,11 @@ def _replicate_index(self, index):
     def __repr__(self):
         return f"{self.__class__.__name__}()"
 
+    def __getstate__(self):
+        state = copy(self.__dict__)
+        state["_rng"] = None
+        return state
+
 
 class ImmutableDatasetWriter(Writer):
     """A blocking writer for immutable datasets."""
@@ -218,7 +223,7 @@ def _cursor(self, value):
         _cursor_value.value = value
 
     def __getstate__(self):
-        state = copy(self.__dict__)
+        state = super().__getstate__()
         if get_spawning_popen() is None:
             cursor = self._cursor
             del state["_cursor_value"]
@@ -514,7 +519,7 @@ def __getstate__(self):
             raise RuntimeError(
                 f"Writers of type {type(self)} cannot be shared between processes."
             )
-        state = copy(self.__dict__)
+        state = super().__getstate__()
         return state
 
     def dumps(self, path):