diff --git a/.github/scripts/m1_script.sh b/.github/scripts/td_script.sh
similarity index 71%
rename from .github/scripts/m1_script.sh
rename to .github/scripts/td_script.sh
index 6552d8e4622..6da1cad5d79 100644
--- a/.github/scripts/m1_script.sh
+++ b/.github/scripts/td_script.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
 
-export TORCHRL_BUILD_VERSION=0.4.0
+export TORCHRL_BUILD_VERSION=0.5.0
 
 ${CONDA_RUN} pip install git+https://github.com/pytorch/tensordict.git -U
diff --git a/.github/unittest/linux_examples/scripts/run_test.sh b/.github/unittest/linux_examples/scripts/run_test.sh
index f91c050dde0..f8b700c0410 100755
--- a/.github/unittest/linux_examples/scripts/run_test.sh
+++ b/.github/unittest/linux_examples/scripts/run_test.sh
@@ -9,9 +9,19 @@
 #
 #
 
-set -e
+#set -e
 set -v
 
+# Initialize an error flag
+error_occurred=0
+# Function to handle errors
+error_handler() {
+    echo "Error on line $1"
+    error_occurred=1
+}
+# Trap ERR to call the error_handler function with the failing line number
+trap 'error_handler $LINENO' ERR
+
 export PYTORCH_TEST_WITH_SLOW='1'
 python -m torch.utils.collect_env
 # Avoid error: "fatal: unsafe repository"
@@ -24,6 +34,7 @@ lib_dir="${env_dir}/lib"
 # solves ImportError: /lib64/libstdc++.so.6: version `GLIBCXX_3.4.21' not found
 export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$lib_dir
 export MKL_THREADING_LAYER=GNU
+export CUDA_LAUNCH_BLOCKING=1
 
 python .github/unittest/helpers/coverage_run_parallel.py -m pytest test/smoke_test.py -v --durations 200
 #python .github/unittest/helpers/coverage_run_parallel.py -m pytest test/smoke_test_deps.py -v --durations 200
@@ -163,18 +174,6 @@ python .github/unittest/helpers/coverage_run_parallel.py sota-implementations/cr
   env.name=Pendulum-v1 \
   network.device= \
   logger.backend=
-python .github/unittest/helpers/coverage_run_parallel.py sota-implementations/dreamer/dreamer.py \
-  collector.total_frames=200 \
-  collector.init_random_frames=10 \
-  collector.frames_per_batch=200 \
-  env.n_parallel_envs=4 \
-  optimization.optim_steps_per_batch=1 \
-  logger.video=True \
-  logger.backend=csv \
-  replay_buffer.buffer_size=120 \
-  replay_buffer.batch_size=24 \
-  replay_buffer.batch_length=12 \
-  networks.rssm_hidden_dim=17
 python .github/unittest/helpers/coverage_run_parallel.py sota-implementations/td3/td3.py \
   collector.total_frames=48 \
   collector.init_random_frames=10 \
@@ -214,8 +213,8 @@ python .github/unittest/helpers/coverage_run_parallel.py sota-implementations/dr
   collector.frames_per_batch=200 \
   env.n_parallel_envs=1 \
   optimization.optim_steps_per_batch=1 \
-  logger.backend=csv \
   logger.video=True \
+  logger.backend=csv \
   replay_buffer.buffer_size=120 \
   replay_buffer.batch_size=24 \
   replay_buffer.batch_length=12 \
@@ -312,3 +311,11 @@ python .github/unittest/helpers/coverage_run_parallel.py sota-implementations/ba
 
 coverage combine
 coverage xml -i
+
+# Check if any errors occurred during the script execution
+if [ "$error_occurred" -ne 0 ]; then
+    echo "Errors occurred during script execution"
+    exit 1
+else
+    echo "Script executed successfully"
+fi
diff --git a/.github/workflows/build-wheels-linux.yml b/.github/workflows/build-wheels-linux.yml
index 5171a7c3e2a..f51c5ed79b6 100644
--- a/.github/workflows/build-wheels-linux.yml
+++ b/.github/workflows/build-wheels-linux.yml
@@ -45,3 +45,4 @@ jobs:
       package-name: ${{ matrix.package-name }}
       smoke-test-script: ${{ matrix.smoke-test-script }}
       trigger-event: ${{ github.event_name }}
+      env-var-script: .github/scripts/td_script.sh
diff --git a/.github/workflows/build-wheels-m1.yml b/.github/workflows/build-wheels-m1.yml
index 84fe79d09d2..73a365a79f2 100644
--- a/.github/workflows/build-wheels-m1.yml
+++ b/.github/workflows/build-wheels-m1.yml
@@ -46,4 +46,4 @@ jobs:
       runner-type: macos-m1-stable
       smoke-test-script: ${{ matrix.smoke-test-script }}
       trigger-event: ${{ github.event_name }}
-      env-var-script: .github/scripts/m1_script.sh
+      env-var-script: .github/scripts/td_script.sh
diff --git a/.github/workflows/build-wheels-windows.yml b/.github/workflows/build-wheels-windows.yml
index 683f2a93f69..1beef7318f4 100644
--- a/.github/workflows/build-wheels-windows.yml
+++ b/.github/workflows/build-wheels-windows.yml
@@ -46,3 +46,4 @@ jobs:
       package-name: ${{ matrix.package-name }}
       smoke-test-script: ${{ matrix.smoke-test-script }}
       trigger-event: ${{ github.event_name }}
+      env-var-script: .github/scripts/td_script.sh
diff --git a/setup.py b/setup.py
index 0196cb4a8f4..95dc0802a4f 100644
--- a/setup.py
+++ b/setup.py
@@ -172,7 +172,7 @@ def _main(argv):
     if is_nightly:
         tensordict_dep = "tensordict-nightly"
     else:
-        tensordict_dep = "tensordict>=0.4.0"
+        tensordict_dep = "tensordict>=0.5.0"
 
     if is_nightly:
         version = get_nightly_version()
diff --git a/sota-implementations/a2c/a2c_atari.py b/sota-implementations/a2c/a2c_atari.py
index 775dcfe206d..f8c18147306 100644
--- a/sota-implementations/a2c/a2c_atari.py
+++ b/sota-implementations/a2c/a2c_atari.py
@@ -201,7 +201,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get test rewards
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             if ((i - 1) * frames_in_batch * frame_skip) // test_interval < (
                 i * frames_in_batch * frame_skip
             ) // test_interval:
diff --git a/sota-implementations/a2c/a2c_mujoco.py b/sota-implementations/a2c/a2c_mujoco.py
index 0276039058f..d115174eb9c 100644
--- a/sota-implementations/a2c/a2c_mujoco.py
+++ b/sota-implementations/a2c/a2c_mujoco.py
@@ -186,7 +186,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get test rewards
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             prev_test_frame = ((i - 1) * frames_in_batch) // cfg.logger.test_interval
             cur_test_frame = (i * frames_in_batch) // cfg.logger.test_interval
             final = collected_frames >= collector.total_frames
diff --git a/sota-implementations/cql/cql_offline.py b/sota-implementations/cql/cql_offline.py
index d8185c8091c..5ca70f83b53 100644
--- a/sota-implementations/cql/cql_offline.py
+++ b/sota-implementations/cql/cql_offline.py
@@ -150,7 +150,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
         # evaluation
         if i % evaluation_interval == 0:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_td = eval_env.rollout(
                     max_steps=eval_steps, policy=model[0], auto_cast_to_device=True
                 )
diff --git a/sota-implementations/cql/cql_online.py b/sota-implementations/cql/cql_online.py
index 5f8f81357c8..cf629ed0733 100644
--- a/sota-implementations/cql/cql_online.py
+++ b/sota-implementations/cql/cql_online.py
@@ -204,7 +204,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         cur_test_frame = (i * frames_per_batch) // evaluation_interval
         final = current_frames >= collector.total_frames
         if (i >= 1 and (prev_test_frame < cur_test_frame)) or final:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_start = time.time()
                 eval_rollout = eval_env.rollout(
                     eval_rollout_steps,
diff --git a/sota-implementations/cql/discrete_cql_online.py b/sota-implementations/cql/discrete_cql_online.py
index 4b6f14cd058..d0d6693eb97 100644
--- a/sota-implementations/cql/discrete_cql_online.py
+++ b/sota-implementations/cql/discrete_cql_online.py
@@ -183,7 +183,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
         # Evaluation
         if abs(collected_frames % eval_iter) < frames_per_batch:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_start = time.time()
                 eval_rollout = eval_env.rollout(
                     eval_rollout_steps,
diff --git a/sota-implementations/ddpg/ddpg.py b/sota-implementations/ddpg/ddpg.py
index eb0b88c26f7..a92ee6185c3 100644
--- a/sota-implementations/ddpg/ddpg.py
+++ b/sota-implementations/ddpg/ddpg.py
@@ -185,7 +185,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
         # Evaluation
         if abs(collected_frames % eval_iter) < frames_per_batch:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_start = time.time()
                 eval_rollout = eval_env.rollout(
                     eval_rollout_steps,
diff --git a/sota-implementations/decision_transformer/dt.py b/sota-implementations/decision_transformer/dt.py
index 59dbcafd8c9..9cca9fd8af5 100644
--- a/sota-implementations/decision_transformer/dt.py
+++ b/sota-implementations/decision_transformer/dt.py
@@ -56,7 +56,9 @@ def main(cfg: "DictConfig"):  # noqa: F821
     )
 
     # Create test environment
-    test_env = make_env(cfg.env, obs_loc, obs_std, from_pixels=cfg.logger.video)
+    test_env = make_env(
+        cfg.env, obs_loc, obs_std, from_pixels=cfg.logger.video, device=model_device
+    )
     if cfg.logger.video:
         test_env = test_env.append_transform(
             VideoRecorder(logger, tag="rendered", in_keys=["pixels"])
@@ -114,7 +116,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         to_log = {"train/loss": loss_vals["loss"]}
 
         # Evaluation
-        with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+        with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
             if i % pretrain_log_interval == 0:
                 eval_td = test_env.rollout(
                     max_steps=eval_steps,
diff --git a/sota-implementations/decision_transformer/online_dt.py b/sota-implementations/decision_transformer/online_dt.py
index 5cb297e5c0b..da2241ce9fa 100644
--- a/sota-implementations/decision_transformer/online_dt.py
+++ b/sota-implementations/decision_transformer/online_dt.py
@@ -126,7 +126,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         }
 
         # Evaluation
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             inference_policy.eval()
             if i % pretrain_log_interval == 0:
                 eval_td = test_env.rollout(
diff --git a/sota-implementations/decision_transformer/utils.py b/sota-implementations/decision_transformer/utils.py
index 7c9500aa4e7..409833c75fa 100644
--- a/sota-implementations/decision_transformer/utils.py
+++ b/sota-implementations/decision_transformer/utils.py
@@ -57,7 +57,7 @@
 # -----------------
 
 
-def make_base_env(env_cfg, from_pixels=False):
+def make_base_env(env_cfg, from_pixels=False, device=None):
     set_gym_backend(env_cfg.backend).set()
 
     env_library = LIBS[env_cfg.library]
@@ -73,7 +73,7 @@ def make_base_env(env_cfg, from_pixels=False):
     if env_library is DMControlEnv:
         env_task = env_cfg.task
         env_kwargs.update({"task_name": env_task})
-    env = env_library(**env_kwargs)
+    env = env_library(**env_kwargs, device=device)
     return env
 
 
@@ -134,7 +134,9 @@ def make_transformed_env(base_env, env_cfg, obs_loc, obs_std, train=False):
     return transformed_env
 
 
-def make_parallel_env(env_cfg, obs_loc, obs_std, train=False, from_pixels=False):
+def make_parallel_env(
+    env_cfg, obs_loc, obs_std, train=False, from_pixels=False, device=None
+):
     if train:
         num_envs = env_cfg.num_train_envs
     else:
@@ -142,10 +144,12 @@ def make_parallel_env(env_cfg, obs_loc, obs_std, train=False, from_pixels=False)
 
     def make_env():
         with set_gym_backend(env_cfg.backend):
-            return make_base_env(env_cfg, from_pixels=from_pixels)
+            return make_base_env(env_cfg, from_pixels=from_pixels, device="cpu")
 
     env = make_transformed_env(
-        ParallelEnv(num_envs, EnvCreator(make_env), serial_for_single=True),
+        ParallelEnv(
+            num_envs, EnvCreator(make_env), serial_for_single=True, device=device
+        ),
         env_cfg,
         obs_loc,
         obs_std,
@@ -154,11 +158,15 @@ def make_env():
     return env
 
 
-def make_env(env_cfg, obs_loc, obs_std, train=False, from_pixels=False):
-    env = make_parallel_env(
-        env_cfg, obs_loc, obs_std, train=train, from_pixels=from_pixels
+def make_env(env_cfg, obs_loc, obs_std, train=False, from_pixels=False, device=None):
+    return make_parallel_env(
+        env_cfg,
+        obs_loc,
+        obs_std,
+        train=train,
+        from_pixels=from_pixels,
+        device=device,
     )
-    return env
 
 
 # ====================================================================
diff --git a/sota-implementations/discrete_sac/discrete_sac.py b/sota-implementations/discrete_sac/discrete_sac.py
index 6e100f92dc3..386f743c7d3 100644
--- a/sota-implementations/discrete_sac/discrete_sac.py
+++ b/sota-implementations/discrete_sac/discrete_sac.py
@@ -204,7 +204,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         cur_test_frame = (i * frames_per_batch) // eval_iter
         final = current_frames >= collector.total_frames
         if (i >= 1 and (prev_test_frame < cur_test_frame)) or final:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_start = time.time()
                 eval_rollout = eval_env.rollout(
                     eval_rollout_steps,
diff --git a/sota-implementations/dqn/dqn_atari.py b/sota-implementations/dqn/dqn_atari.py
index 90f93551d4d..906273ee2f5 100644
--- a/sota-implementations/dqn/dqn_atari.py
+++ b/sota-implementations/dqn/dqn_atari.py
@@ -199,7 +199,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get and log evaluation rewards and eval time
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             prev_test_frame = ((i - 1) * frames_per_batch) // test_interval
             cur_test_frame = (i * frames_per_batch) // test_interval
             final = current_frames >= collector.total_frames
diff --git a/sota-implementations/dqn/dqn_cartpole.py b/sota-implementations/dqn/dqn_cartpole.py
index ac3f17a9203..173f88f7028 100644
--- a/sota-implementations/dqn/dqn_cartpole.py
+++ b/sota-implementations/dqn/dqn_cartpole.py
@@ -180,7 +180,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get and log evaluation rewards and eval time
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             prev_test_frame = ((i - 1) * frames_per_batch) // test_interval
             cur_test_frame = (i * frames_per_batch) // test_interval
             final = current_frames >= collector.total_frames
diff --git a/sota-implementations/dreamer/config.yaml b/sota-implementations/dreamer/config.yaml
index ab101e8486a..604e1ac546a 100644
--- a/sota-implementations/dreamer/config.yaml
+++ b/sota-implementations/dreamer/config.yaml
@@ -9,17 +9,13 @@ env:
   image_size : 64
   horizon: 500
   n_parallel_envs: 8
-  device:
-    _target_: dreamer_utils._default_device
-    device: null
+  device: cpu
 
 collector:
   total_frames: 5_000_000
   init_random_frames: 3000
   frames_per_batch: 1000
   device:
-    _target_: dreamer_utils._default_device
-    device: null
 
 optimization:
   train_every: 1000
@@ -41,8 +37,6 @@ optimization:
 networks:
   exploration_noise: 0.3
   device:
-    _target_: dreamer_utils._default_device
-    device: null
   state_dim: 30
   rssm_hidden_dim: 200
   hidden_dim: 400
diff --git a/sota-implementations/dreamer/dreamer.py b/sota-implementations/dreamer/dreamer.py
index e7b346b2b22..e521b9df386 100644
--- a/sota-implementations/dreamer/dreamer.py
+++ b/sota-implementations/dreamer/dreamer.py
@@ -10,6 +10,7 @@
 import torch.cuda
 import tqdm
 from dreamer_utils import (
+    _default_device,
     dump_video,
     log_metrics,
     make_collector,
@@ -17,7 +18,6 @@
     make_environments,
     make_replay_buffer,
 )
-from hydra.utils import instantiate
 
 # mixed precision training
 from torch.cuda.amp import GradScaler
@@ -38,7 +38,7 @@
 def main(cfg: "DictConfig"):  # noqa: F821
     # cfg = correct_for_frame_skip(cfg)
 
-    device = torch.device(instantiate(cfg.networks.device))
+    device = _default_device(cfg.networks.device)
 
     # Create logger
     exp_name = generate_exp_name("Dreamer", cfg.logger.exp_name)
@@ -284,7 +284,7 @@ def compile_rssms(module):
         # Evaluation
         if (i % eval_iter) == 0:
             # Real env
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_rollout = test_env.rollout(
                     eval_rollout_steps,
                     policy,
@@ -298,7 +298,9 @@ def compile_rssms(module):
                     log_metrics(logger, eval_metrics, collected_frames)
             # Simulated env
             if model_based_env_eval is not None:
-                with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+                with set_exploration_type(
+                    ExplorationType.DETERMINISTIC
+                ), torch.no_grad():
                     eval_rollout = model_based_env_eval.rollout(
                         eval_rollout_steps,
                         policy,
diff --git a/sota-implementations/dreamer/dreamer_utils.py b/sota-implementations/dreamer/dreamer_utils.py
index ff14871b011..73baa310821 100644
--- a/sota-implementations/dreamer/dreamer_utils.py
+++ b/sota-implementations/dreamer/dreamer_utils.py
@@ -9,7 +9,6 @@
 import torch
 
 import torch.nn as nn
-from hydra.utils import instantiate
 from tensordict import NestedKey
 from tensordict.nn import (
     InteractionType,
@@ -88,6 +87,7 @@ def _make_env(cfg, device, from_pixels=False):
             cfg.env.task,
             from_pixels=cfg.env.from_pixels or from_pixels,
             pixels_only=cfg.env.from_pixels,
+            device=device,
         )
     else:
         raise NotImplementedError(f"Unknown lib {lib}.")
@@ -98,7 +98,6 @@ def _make_env(cfg, device, from_pixels=False):
     env = env.append_transform(
         TensorDictPrimer(random=False, default_value=0, **default_dict)
     )
-    assert env is not None
     return env
 
 
@@ -129,7 +128,7 @@ def transform_env(cfg, env):
 
 def make_environments(cfg, parallel_envs=1, logger=None):
     """Make environments for training and evaluation."""
-    func = functools.partial(_make_env, cfg=cfg, device=cfg.env.device)
+    func = functools.partial(_make_env, cfg=cfg, device=_default_device(cfg.env.device))
     train_env = ParallelEnv(
         parallel_envs,
         EnvCreator(func),
@@ -138,7 +137,10 @@ def make_environments(cfg, parallel_envs=1, logger=None):
     train_env = transform_env(cfg, train_env)
     train_env.set_seed(cfg.env.seed)
     func = functools.partial(
-        _make_env, cfg=cfg, device=cfg.env.device, from_pixels=cfg.logger.video
+        _make_env,
+        cfg=cfg,
+        device=_default_device(cfg.env.device),
+        from_pixels=cfg.logger.video,
     )
     eval_env = ParallelEnv(
         1,
@@ -332,7 +334,7 @@ def make_collector(cfg, train_env, actor_model_explore):
         init_random_frames=cfg.collector.init_random_frames,
         frames_per_batch=cfg.collector.frames_per_batch,
         total_frames=cfg.collector.total_frames,
-        policy_device=instantiate(cfg.collector.device),
+        policy_device=_default_device(cfg.collector.device),
         env_device=train_env.device,
         storing_device="cpu",
     )
@@ -535,7 +537,7 @@ def _dreamer_make_actor_real(
             SafeProbabilisticModule(
                 in_keys=["loc", "scale"],
                 out_keys=[action_key],
-                default_interaction_type=InteractionType.MODE,
+                default_interaction_type=InteractionType.DETERMINISTIC,
                 distribution_class=TanhNormal,
                 distribution_kwargs={"tanh_loc": True},
                 spec=CompositeSpec(
diff --git a/sota-implementations/impala/impala_multi_node_ray.py b/sota-implementations/impala/impala_multi_node_ray.py
index 0482a595ffa..1998c044305 100644
--- a/sota-implementations/impala/impala_multi_node_ray.py
+++ b/sota-implementations/impala/impala_multi_node_ray.py
@@ -247,7 +247,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get test rewards
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             if ((i - 1) * frames_in_batch * frame_skip) // test_interval < (
                 i * frames_in_batch * frame_skip
             ) // test_interval:
diff --git a/sota-implementations/impala/impala_multi_node_submitit.py b/sota-implementations/impala/impala_multi_node_submitit.py
index ce96cf06ce8..fdee4256c42 100644
--- a/sota-implementations/impala/impala_multi_node_submitit.py
+++ b/sota-implementations/impala/impala_multi_node_submitit.py
@@ -239,7 +239,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get test rewards
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             if ((i - 1) * frames_in_batch * frame_skip) // test_interval < (
                 i * frames_in_batch * frame_skip
             ) // test_interval:
diff --git a/sota-implementations/impala/impala_single_node.py b/sota-implementations/impala/impala_single_node.py
index bb0f314197a..cf583909620 100644
--- a/sota-implementations/impala/impala_single_node.py
+++ b/sota-implementations/impala/impala_single_node.py
@@ -217,7 +217,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get test rewards
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             if ((i - 1) * frames_in_batch * frame_skip) // test_interval < (
                 i * frames_in_batch * frame_skip
             ) // test_interval:
diff --git a/sota-implementations/iql/discrete_iql.py b/sota-implementations/iql/discrete_iql.py
index 33513dd3973..ae1894379fd 100644
--- a/sota-implementations/iql/discrete_iql.py
+++ b/sota-implementations/iql/discrete_iql.py
@@ -186,7 +186,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
         # Evaluation
         if abs(collected_frames % eval_iter) < frames_per_batch:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_start = time.time()
                 eval_rollout = eval_env.rollout(
                     eval_rollout_steps,
diff --git a/sota-implementations/iql/iql_offline.py b/sota-implementations/iql/iql_offline.py
index d98724e1371..d1a16fd8192 100644
--- a/sota-implementations/iql/iql_offline.py
+++ b/sota-implementations/iql/iql_offline.py
@@ -130,7 +130,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
         # evaluation
         if i % evaluation_interval == 0:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_td = eval_env.rollout(
                     max_steps=eval_steps, policy=model[0], auto_cast_to_device=True
                 )
diff --git a/sota-implementations/iql/iql_online.py b/sota-implementations/iql/iql_online.py
index b66c6f9dcf2..d50ff806294 100644
--- a/sota-implementations/iql/iql_online.py
+++ b/sota-implementations/iql/iql_online.py
@@ -184,7 +184,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
         # Evaluation
         if abs(collected_frames % eval_iter) < frames_per_batch:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_start = time.time()
                 eval_rollout = eval_env.rollout(
                     eval_rollout_steps,
diff --git a/sota-implementations/multiagent/iql.py b/sota-implementations/multiagent/iql.py
index 81551ebefb7..a4d2b88a9d0 100644
--- a/sota-implementations/multiagent/iql.py
+++ b/sota-implementations/multiagent/iql.py
@@ -206,7 +206,7 @@ def train(cfg: "DictConfig"):  # noqa: F821
             and cfg.logger.backend
         ):
             evaluation_start = time.time()
-            with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+            with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
                 env_test.frames = []
                 rollouts = env_test.rollout(
                     max_steps=cfg.env.max_steps,
diff --git a/sota-implementations/multiagent/maddpg_iddpg.py b/sota-implementations/multiagent/maddpg_iddpg.py
index 9d14ff04b04..bd44bb0a043 100644
--- a/sota-implementations/multiagent/maddpg_iddpg.py
+++ b/sota-implementations/multiagent/maddpg_iddpg.py
@@ -230,7 +230,7 @@ def train(cfg: "DictConfig"):  # noqa: F821
             and cfg.logger.backend
         ):
             evaluation_start = time.time()
-            with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+            with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
                 env_test.frames = []
                 rollouts = env_test.rollout(
                     max_steps=cfg.env.max_steps,
diff --git a/sota-implementations/multiagent/mappo_ippo.py b/sota-implementations/multiagent/mappo_ippo.py
index e752c4d73f2..fa006a7d4a2 100644
--- a/sota-implementations/multiagent/mappo_ippo.py
+++ b/sota-implementations/multiagent/mappo_ippo.py
@@ -236,7 +236,7 @@ def train(cfg: "DictConfig"):  # noqa: F821
             and cfg.logger.backend
         ):
             evaluation_start = time.time()
-            with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+            with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
                 env_test.frames = []
                 rollouts = env_test.rollout(
                     max_steps=cfg.env.max_steps,
diff --git a/sota-implementations/multiagent/qmix_vdn.py b/sota-implementations/multiagent/qmix_vdn.py
index d294a9c783e..4e6a962c556 100644
--- a/sota-implementations/multiagent/qmix_vdn.py
+++ b/sota-implementations/multiagent/qmix_vdn.py
@@ -241,7 +241,7 @@ def train(cfg: "DictConfig"):  # noqa: F821
             and cfg.logger.backend
         ):
             evaluation_start = time.time()
-            with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+            with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
                 env_test.frames = []
                 rollouts = env_test.rollout(
                     max_steps=cfg.env.max_steps,
diff --git a/sota-implementations/multiagent/sac.py b/sota-implementations/multiagent/sac.py
index 30b7e7e98bc..f7b2523010b 100644
--- a/sota-implementations/multiagent/sac.py
+++ b/sota-implementations/multiagent/sac.py
@@ -300,7 +300,7 @@ def train(cfg: "DictConfig"):  # noqa: F821
             and cfg.logger.backend
         ):
             evaluation_start = time.time()
-            with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+            with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
                 env_test.frames = []
                 rollouts = env_test.rollout(
                     max_steps=cfg.env.max_steps,
diff --git a/sota-implementations/ppo/ppo_atari.py b/sota-implementations/ppo/ppo_atari.py
index 908cb7924a3..2b02254032a 100644
--- a/sota-implementations/ppo/ppo_atari.py
+++ b/sota-implementations/ppo/ppo_atari.py
@@ -217,7 +217,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get test rewards
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             if ((i - 1) * frames_in_batch * frame_skip) // test_interval < (
                 i * frames_in_batch * frame_skip
             ) // test_interval:
diff --git a/sota-implementations/ppo/ppo_mujoco.py b/sota-implementations/ppo/ppo_mujoco.py
index e3e74971a49..219ae1b59b6 100644
--- a/sota-implementations/ppo/ppo_mujoco.py
+++ b/sota-implementations/ppo/ppo_mujoco.py
@@ -210,7 +210,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
         )
 
         # Get test rewards
-        with torch.no_grad(), set_exploration_type(ExplorationType.MODE):
+        with torch.no_grad(), set_exploration_type(ExplorationType.DETERMINISTIC):
             if ((i - 1) * frames_in_batch) // cfg_logger_test_interval < (
                 i * frames_in_batch
             ) // cfg_logger_test_interval:
diff --git a/sota-implementations/sac/sac.py b/sota-implementations/sac/sac.py
index f7a399cda72..9904fe072ab 100644
--- a/sota-implementations/sac/sac.py
+++ b/sota-implementations/sac/sac.py
@@ -197,7 +197,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
         # Evaluation
         if abs(collected_frames % eval_iter) < frames_per_batch:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_start = time.time()
                 eval_rollout = eval_env.rollout(
                     eval_rollout_steps,
diff --git a/sota-implementations/td3/td3.py b/sota-implementations/td3/td3.py
index 97fd039c238..5fbc9b032d7 100644
--- a/sota-implementations/td3/td3.py
+++ b/sota-implementations/td3/td3.py
@@ -195,7 +195,7 @@ def main(cfg: "DictConfig"):  # noqa: F821
 
         # Evaluation
         if abs(collected_frames % eval_iter) < frames_per_batch:
-            with set_exploration_type(ExplorationType.MODE), torch.no_grad():
+            with set_exploration_type(ExplorationType.DETERMINISTIC), torch.no_grad():
                 eval_start = time.time()
                 eval_rollout = eval_env.rollout(
                     eval_rollout_steps,
diff --git a/test/test_env.py b/test/test_env.py
index e6ca38b729c..f8f242f3955 100644
--- a/test/test_env.py
+++ b/test/test_env.py
@@ -2061,6 +2061,7 @@ def main_collector(j, q=None):
             total_frames=N * n_workers * 100,
             storing_device=device,
             device=device,
+            cat_results=-1,
         )
         single_collectors = [
             SyncDataCollector(
diff --git a/torchrl/collectors/collectors.py b/torchrl/collectors/collectors.py
index 50e3dd5cc49..32294a25edd 100644
--- a/torchrl/collectors/collectors.py
+++ b/torchrl/collectors/collectors.py
@@ -2065,18 +2065,18 @@ def _queue_len(self) -> int:
     def iterator(self) -> Iterator[TensorDictBase]:
         cat_results = self.cat_results
         if cat_results is None:
-            cat_results = 0
+            cat_results = "stack"
             warnings.warn(
                 f"`cat_results` was not specified in the constructor of {type(self).__name__}. "
                 f"For MultiSyncDataCollector, `cat_results` indicates how the data should "
-                f"be packed: the preferred option is `cat_results='stack'` which provides "
-                f"the best interoperability across torchrl components. "
+                f"be packed: the preferred option and current default is `cat_results='stack'` "
+                f"which provides the best interoperability across torchrl components. "
                 f"Other accepted values are `cat_results=0` (previous behaviour) and "
                 f"`cat_results=-1` (cat along time dimension). Among these two, the latter "
                 f"should be preferred for consistency across environment configurations. "
-                f"Currently, the default value is `0` (using torch.cat along first dimension)."
-                f"From v0.5 onward, this will default to `'stack'`. "
-                f"To suppress this warning, set stack_results to the desired value.",
+                f"Currently, the default value is `'stack'`."
+                f"From v0.6 onward, this warning will be removed. "
+                f"To suppress this warning, set `cat_results` to the desired value.",
                 category=DeprecationWarning,
             )
 
diff --git a/torchrl/data/tensor_specs.py b/torchrl/data/tensor_specs.py
index 04c24cb8d57..0006213cd27 100644
--- a/torchrl/data/tensor_specs.py
+++ b/torchrl/data/tensor_specs.py
@@ -1143,6 +1143,7 @@ def __eq__(self, other):
         if not isinstance(other, LazyStackedTensorSpec):
             return False
         if self.device != other.device:
+            raise RuntimeError((self, other))
             return False
         if len(self._specs) != len(other._specs):
             return False
diff --git a/torchrl/envs/batched_envs.py b/torchrl/envs/batched_envs.py
index 4241f6613a0..4996e527527 100644
--- a/torchrl/envs/batched_envs.py
+++ b/torchrl/envs/batched_envs.py
@@ -406,17 +406,16 @@ def _find_sync_values(self):
             return _do_nothing, _do_nothing
 
         if worker_device is None:
-            worker_not_main = [False]
+            worker_not_main = False
 
-            def find_all_worker_devices(item, worker_not_main=worker_not_main):
+            def find_all_worker_devices(item):
+                nonlocal worker_not_main
                 if hasattr(item, "device"):
-                    worker_not_main[0] = worker_not_main[0] or (
-                        item.device != self_device
-                    )
+                    worker_not_main = worker_not_main or (item.device != self_device)
 
             for td in self.shared_tensordicts:
                 td.apply(find_all_worker_devices, filter_empty=True)
-            if worker_not_main[0]:
+            if worker_not_main:
                 if torch.cuda.is_available():
                     worker_device = (
                         torch.device("cuda")
@@ -431,6 +430,8 @@ def find_all_worker_devices(item, worker_not_main=worker_not_main):
                     )
                 else:
                     raise RuntimeError("Did not find a valid worker device")
+            else:
+                worker_device = self_device
 
         if (
             worker_device is not None
@@ -460,6 +461,7 @@ def find_all_worker_devices(item, worker_not_main=worker_not_main):
             and self_device.type == "mps"
         ):
             return _mps_sync(self_device), _mps_sync(self_device)
+        return _do_nothing, _do_nothing
 
     def __getstate__(self):
         out = copy(self.__dict__)
diff --git a/torchrl/envs/common.py b/torchrl/envs/common.py
index c965e7dedf3..e30de3534d9 100644
--- a/torchrl/envs/common.py
+++ b/torchrl/envs/common.py
@@ -15,7 +15,6 @@
 import torch
 import torch.nn as nn
 from tensordict import LazyStackedTensorDict, TensorDictBase, unravel_key
-from tensordict.base import NO_DEFAULT
 from tensordict.utils import NestedKey
 from torchrl._utils import (
     _ends_with,
@@ -3020,21 +3019,11 @@ class _EnvWrapper(EnvBase):
     def __init__(
         self,
         *args,
-        device: DEVICE_TYPING = NO_DEFAULT,
+        device: DEVICE_TYPING = None,
         batch_size: Optional[torch.Size] = None,
         allow_done_after_reset: bool = False,
         **kwargs,
     ):
-        if device is NO_DEFAULT:
-            warnings.warn(
-                "Your wrapper was not given a device. Currently, this "
-                "value will default to 'cpu'. From v0.5 it will "
-                "default to `None`. With a device of None, no device casting "
-                "is performed and the resulting tensordicts are deviceless. "
-                "Please set your device accordingly.",
-                category=DeprecationWarning,
-            )
-            device = torch.device("cpu")
         super().__init__(
             device=device,
             batch_size=batch_size,
diff --git a/torchrl/envs/gym_like.py b/torchrl/envs/gym_like.py
index 47f93f09779..c7935272c91 100644
--- a/torchrl/envs/gym_like.py
+++ b/torchrl/envs/gym_like.py
@@ -348,8 +348,7 @@ def _step(self, tensordict: TensorDictBase) -> TensorDictBase:
                 batch_size=tensordict.batch_size,
             )
         if self.device is not None:
-            tensordict_out = tensordict_out.to(self.device, non_blocking=True)
-            self._sync_device()
+            tensordict_out = tensordict_out.to(self.device)
 
         if self.info_dict_reader and (info_dict is not None):
             if not isinstance(info_dict, dict):
@@ -393,8 +392,7 @@ def _reset(
                 if key not in tensordict_out.keys(True, True):
                     tensordict_out[key] = item.zero()
         if self.device is not None:
-            tensordict_out = tensordict_out.to(self.device, non_blocking=True)
-            self._sync_device()
+            tensordict_out = tensordict_out.to(self.device)
         return tensordict_out
 
     @abc.abstractmethod
diff --git a/torchrl/envs/libs/gym.py b/torchrl/envs/libs/gym.py
index 07c48587c14..9195929e31d 100644
--- a/torchrl/envs/libs/gym.py
+++ b/torchrl/envs/libs/gym.py
@@ -27,7 +27,6 @@
     BoundedTensorSpec,
     CompositeSpec,
     DiscreteTensorSpec,
-    LazyStackedTensorSpec,
     MultiDiscreteTensorSpec,
     MultiOneHotDiscreteTensorSpec,
     OneHotDiscreteTensorSpec,
@@ -246,8 +245,8 @@ def _gym_to_torchrl_spec_transform(
         ).expand(batch_size)
     gym_spaces = gym_backend("spaces")
     if isinstance(spec, gym_spaces.tuple.Tuple):
-        result = LazyStackedTensorSpec(
-            *[
+        result = torch.stack(
+            [
                 _gym_to_torchrl_spec_transform(
                     s,
                     device=device,
diff --git a/torchrl/envs/libs/vmas.py b/torchrl/envs/libs/vmas.py
index 8e30fdb2a7e..9751e84a3ac 100644
--- a/torchrl/envs/libs/vmas.py
+++ b/torchrl/envs/libs/vmas.py
@@ -795,7 +795,9 @@ def _build_env(
             env=vmas.make_env(
                 scenario=scenario,
                 num_envs=num_envs,
-                device=self.device,
+                device=self.device
+                if self.device is not None
+                else torch.get_default_device(),
                 continuous_actions=continuous_actions,
                 max_steps=max_steps,
                 seed=seed,
diff --git a/torchrl/envs/transforms/transforms.py b/torchrl/envs/transforms/transforms.py
index eb9cdce923d..70aef03e041 100644
--- a/torchrl/envs/transforms/transforms.py
+++ b/torchrl/envs/transforms/transforms.py
@@ -3411,14 +3411,7 @@ def __init__(
         out_keys_inv: Sequence[NestedKey] | None = None,
     ):
         if in_keys is not None and in_keys_inv is None:
-            warnings.warn(
-                "in_keys have been provided but not in_keys_inv. From v0.5, "
-                "this will result in in_keys_inv being an empty list whereas "
-                "now the input keys are retrieved automatically. "
-                "To silence this warning, pass the (possibly empty) "
-                "list of in_keys_inv.",
-                category=DeprecationWarning,
-            )
+            in_keys_inv = []
 
         self.dtype_in = dtype_in
         self.dtype_out = dtype_out
diff --git a/torchrl/modules/distributions/continuous.py b/torchrl/modules/distributions/continuous.py
index 087cabe4186..38d8d1dfd02 100644
--- a/torchrl/modules/distributions/continuous.py
+++ b/torchrl/modules/distributions/continuous.py
@@ -481,9 +481,10 @@ def root_dist(self):
     @property
     def mode(self):
         warnings.warn(
-            "This computation of the mode is based on the first-order Taylor expansion "
-            "of the transform around the normal mean value, which can be inaccurate. "
+            "This computation of the mode is based on an inaccurate estimation of the mode "
+            "given the base_dist mode. "
             "To use a more stable implementation of the mode, use dist.get_mode() method instead. "
+            "To silence this warning, consider using the DETERMINISTIC exploration_type."
             "This implementation will be removed in v0.6.",
             category=DeprecationWarning,
         )
diff --git a/torchrl/modules/tensordict_module/actors.py b/torchrl/modules/tensordict_module/actors.py
index 17b1ea77ee4..83b6a8d1fb3 100644
--- a/torchrl/modules/tensordict_module/actors.py
+++ b/torchrl/modules/tensordict_module/actors.py
@@ -4,7 +4,6 @@
 # LICENSE file in the root directory of this source tree.
 from __future__ import annotations
 
-import warnings
 from typing import Dict, List, Optional, Sequence, Tuple, Union
 
 import torch
@@ -922,10 +921,9 @@ def __init__(
         out_keys: Optional[Sequence[NestedKey]] = None,
     ):
         if isinstance(action_space, TensorSpec):
-            warnings.warn(
-                "Using specs in action_space will be deprecated in v0.4.0,"
-                " please use the 'spec' argument if you want to provide an action spec",
-                category=DeprecationWarning,
+            raise RuntimeError(
+                "Using specs in action_space is deprecated. "
+                "Please use the 'spec' argument if you want to provide an action spec"
             )
         action_space, _ = _process_action_space_spec(action_space, None)
 
@@ -1136,10 +1134,9 @@ def __init__(
         action_mask_key: Optional[NestedKey] = None,
     ):
         if isinstance(action_space, TensorSpec):
-            warnings.warn(
-                "Using specs in action_space will be deprecated v0.4.0,"
-                " please use the 'spec' argument if you want to provide an action spec",
-                category=DeprecationWarning,
+            raise RuntimeError(
+                "Using specs in action_space is deprecated."
+                "Please use the 'spec' argument if you want to provide an action spec"
             )
         action_space, spec = _process_action_space_spec(action_space, spec)
 
diff --git a/torchrl/record/recorder.py b/torchrl/record/recorder.py
index 2c2f3fb21ac..b7fb8ab4ed2 100644
--- a/torchrl/record/recorder.py
+++ b/torchrl/record/recorder.py
@@ -221,11 +221,11 @@ def _apply_transform(self, observation: torch.Tensor) -> torch.Tensor:
                 observation_trsf = make_grid(
                     obs_flat, nrow=int(math.ceil(math.sqrt(obs_flat.shape[0])))
                 )
-                self.obs.append(observation_trsf.to(torch.uint8))
+                self.obs.append(observation_trsf.to("cpu", torch.uint8))
             elif observation_trsf.ndimension() >= 4:
-                self.obs.extend(observation_trsf.to(torch.uint8).flatten(0, -4))
+                self.obs.extend(observation_trsf.to("cpu", torch.uint8).flatten(0, -4))
             else:
-                self.obs.append(observation_trsf.to(torch.uint8))
+                self.obs.append(observation_trsf.to("cpu", torch.uint8))
         return observation
 
     def forward(self, tensordict: TensorDictBase) -> TensorDictBase:
diff --git a/version.txt b/version.txt
index 1d0ba9ea182..8f0916f768f 100644
--- a/version.txt
+++ b/version.txt
@@ -1 +1 @@
-0.4.0
+0.5.0