diff --git a/sota-implementations/dreamer/dreamer.py b/sota-implementations/dreamer/dreamer.py
index f28fac8e675..992abea64e0 100644
--- a/sota-implementations/dreamer/dreamer.py
+++ b/sota-implementations/dreamer/dreamer.py
@@ -217,7 +217,9 @@ def compile_rssms(module):
                 with torch.autocast(
                     device_type=device.type, dtype=torch.bfloat16
                 ) if use_autocast else contextlib.nullcontext():
-                    actor_loss_td, sampled_tensordict = actor_loss(sampled_tensordict)
+                    actor_loss_td, sampled_tensordict = actor_loss(
+                        sampled_tensordict.reshape(-1)
+                    )
 
                 actor_opt.zero_grad()
                 if use_autocast:
diff --git a/test/test_cost.py b/test/test_cost.py
index 3530fff825d..6d8de531d49 100644
--- a/test/test_cost.py
+++ b/test/test_cost.py
@@ -10332,7 +10332,7 @@ def test_dreamer_actor(self, device, imagination_horizon, discount_loss, td_est)
             return
         if td_est is not None:
             loss_module.make_value_estimator(td_est)
-        loss_td, fake_data = loss_module(tensordict)
+        loss_td, fake_data = loss_module(tensordict.reshape(-1))
         assert not fake_data.requires_grad
         assert fake_data.shape == torch.Size([tensordict.numel(), imagination_horizon])
         if discount_loss:
diff --git a/torchrl/objectives/dreamer.py b/torchrl/objectives/dreamer.py
index 30f6dd10699..73df58b7e56 100644
--- a/torchrl/objectives/dreamer.py
+++ b/torchrl/objectives/dreamer.py
@@ -271,7 +271,6 @@ def _forward_value_estimator_keys(self, **kwargs) -> None:
 
     def forward(self, tensordict: TensorDict) -> Tuple[TensorDict, TensorDict]:
         tensordict = tensordict.select("state", self.tensor_keys.belief).detach()
-        tensordict = tensordict.reshape(-1)
 
         with timeit("actor_loss/time-rollout"), hold_out_net(
             self.model_based_env