diff --git a/torchrl/envs/batched_envs.py b/torchrl/envs/batched_envs.py
index ee87df39ac1..6c53b5ebabe 100644
--- a/torchrl/envs/batched_envs.py
+++ b/torchrl/envs/batched_envs.py
@@ -1392,7 +1392,7 @@ def _step_and_maybe_reset_no_buffers(
         self, tensordict: TensorDictBase
     ) -> Tuple[TensorDictBase, TensorDictBase]:
 
-        for i, _data in enumerate(tensordict.unbind(0)):
+        for i, _data in enumerate(tensordict.consolidate().unbind(0)):
             self.parent_channels[i].send(("step_and_maybe_reset", _data))
 
         results = [None] * self.num_workers
@@ -1489,7 +1489,7 @@ def step_and_maybe_reset(
     def _step_no_buffers(
         self, tensordict: TensorDictBase
     ) -> Tuple[TensorDictBase, TensorDictBase]:
-        for i, data in enumerate(tensordict.unbind(0)):
+        for i, data in enumerate(tensordict.consolidate().unbind(0)):
             self.parent_channels[i].send(("step", data))
         out_tds = []
         for i, channel in enumerate(self.parent_channels):
@@ -1576,7 +1576,7 @@ def _reset_no_buffers(
         needs_resetting,
     ) -> Tuple[TensorDictBase, TensorDictBase]:
         tdunbound = (
-            tensordict.unbind(0)
+            tensordict.consolidate().unbind(0)
             if is_tensor_collection(tensordict)
             else [None] * self.num_workers
         )
@@ -1895,10 +1895,11 @@ def look_for_cuda(tensor, has_cuda=has_cuda):
             i = 0
             next_shared_tensordict = shared_tensordict.get("next")
             root_shared_tensordict = shared_tensordict.exclude("next")
-            if not (shared_tensordict.is_shared() or shared_tensordict.is_memmap()):
-                raise RuntimeError(
-                    "tensordict must be placed in shared memory (share_memory_() or memmap_())"
-                )
+            # TODO: restore this
+            # if not (shared_tensordict.is_shared() or shared_tensordict.is_memmap()):
+            #     raise RuntimeError(
+            #         "tensordict must be placed in shared memory (share_memory_() or memmap_())"
+            #     )
             shared_tensordict = shared_tensordict.clone(False).unlock_()
 
             initialized = True
@@ -2130,7 +2131,7 @@ def _run_worker_pipe_direct(
                 event.record()
                 event.synchronize()
             mp_event.set()
-            child_pipe.send(cur_td)
+            child_pipe.send(cur_td.consolidate())
             del cur_td
 
         elif cmd == "step":
@@ -2142,7 +2143,7 @@ def _run_worker_pipe_direct(
                 event.record()
                 event.synchronize()
             mp_event.set()
-            child_pipe.send(next_td)
+            child_pipe.send(next_td.consolidate())
             del next_td
 
         elif cmd == "step_and_maybe_reset":