diff --git a/test/test_utils.py b/test/test_utils.py
index 620149daeb6..c2ce2eae6b9 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -12,7 +12,10 @@
 import _utils_internal
 import pytest
 
-from torchrl._utils import get_binary_env_var, implement_for
+import torch
+
+from _utils_internal import get_default_devices
+from torchrl._utils import _rng_decorator, get_binary_env_var, implement_for
 
 from torchrl.envs.libs.gym import gym_backend, GymWrapper, set_gym_backend
 
@@ -358,6 +361,21 @@ class MockGym:
         )  # would break with gymnasium
 
 
+@pytest.mark.parametrize("device", get_default_devices())
+def test_rng_decorator(device):
+    with torch.device(device):
+        torch.manual_seed(10)
+        s0a = torch.randn(3)
+        with _rng_decorator(0):
+            torch.randn(3)
+        s0b = torch.randn(3)
+        torch.manual_seed(10)
+        s1a = torch.randn(3)
+        s1b = torch.randn(3)
+        torch.testing.assert_close(s0a, s1a)
+        torch.testing.assert_close(s0b, s1b)
+
+
 if __name__ == "__main__":
     args, unknown = argparse.ArgumentParser().parse_known_args()
     pytest.main([__file__, "--capture", "no", "--exitfirst"] + unknown)
diff --git a/torchrl/_utils.py b/torchrl/_utils.py
index 9538cecb026..6c52b1d66e7 100644
--- a/torchrl/_utils.py
+++ b/torchrl/_utils.py
@@ -704,3 +704,40 @@ def _replace_last(key: NestedKey, new_ending: str) -> NestedKey:
         return new_ending
     else:
         return key[:-1] + (new_ending,)
+
+
+class _rng_decorator(_DecoratorContextManager):
+    """Temporarily sets the seed and sets back the rng state when exiting."""
+
+    def __init__(self, seed, device=None):
+        self.seed = seed
+        self.device = device
+        self.has_cuda = torch.cuda.is_available()
+
+    def __enter__(self):
+        self._get_state()
+        torch.manual_seed(self.seed)
+
+    def _get_state(self):
+        if self.has_cuda:
+            if self.device is None:
+                self._state = (torch.random.get_rng_state(), torch.cuda.get_rng_state())
+            else:
+                self._state = (
+                    torch.random.get_rng_state(),
+                    torch.cuda.get_rng_state(self.device),
+                )
+
+        else:
+            self.state = torch.random.get_rng_state()
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        if self.has_cuda:
+            torch.random.set_rng_state(self._state[0])
+            if self.device is not None:
+                torch.cuda.set_rng_state(self._state[1], device=self.device)
+            else:
+                torch.cuda.set_rng_state(self._state[1])
+
+        else:
+            torch.random.set_rng_state(self._state)
diff --git a/torchrl/envs/utils.py b/torchrl/envs/utils.py
index 46c923ccfec..71b15d1dfae 100644
--- a/torchrl/envs/utils.py
+++ b/torchrl/envs/utils.py
@@ -31,7 +31,7 @@
     set_interaction_type as set_exploration_type,
 )
 from tensordict.utils import NestedKey
-from torchrl._utils import _replace_last, logger as torchrl_logger
+from torchrl._utils import _replace_last, _rng_decorator, logger as torchrl_logger
 
 from torchrl.data.tensor_specs import (
     CompositeSpec,
@@ -419,7 +419,9 @@ def _per_level_env_check(data0, data1, check_dtype):
                     )
 
 
-def check_env_specs(env, return_contiguous=True, check_dtype=True, seed=0):
+def check_env_specs(
+    env, return_contiguous=True, check_dtype=True, seed: int | None = None
+):
     """Tests an environment specs against the results of short rollout.
 
     This test function should be used as a sanity check for an env wrapped with
@@ -436,7 +438,12 @@ def check_env_specs(env, return_contiguous=True, check_dtype=True, seed=0):
             of inputs/outputs). Defaults to True.
         check_dtype (bool, optional): if False, dtype checks will be skipped.
             Defaults to True.
-        seed (int, optional): for reproducibility, a seed is set.
+        seed (int, optional): for reproducibility, a seed can be set.
+            The seed will be set in pytorch temporarily, then the RNG state will
+            be reverted to what it was before. For the env, we set the seed but since
+            setting the rng state back to what is was isn't a feature of most environment,
+            we leave it to the user to accomplish that.
+            Defaults to ``None``.
 
     Caution: this function resets the env seed. It should be used "offline" to
     check that an env is adequately constructed, but it may affect the seeding
@@ -444,8 +451,14 @@ def check_env_specs(env, return_contiguous=True, check_dtype=True, seed=0):
 
     """
     if seed is not None:
-        torch.manual_seed(seed)
-        env.set_seed(seed)
+        device = (
+            env.device if env.device is not None and env.device.type == "cuda" else None
+        )
+        with _rng_decorator(seed, device=device):
+            env.set_seed(seed)
+            return check_env_specs(
+                env, return_contiguous=return_contiguous, check_dtype=check_dtype
+            )
 
     fake_tensordict = env.fake_tensordict()
     real_tensordict = env.rollout(3, return_contiguous=return_contiguous)