diff --git a/torchrl/envs/common.py b/torchrl/envs/common.py
index 9565959ec4a..c2cca0a5c23 100644
--- a/torchrl/envs/common.py
+++ b/torchrl/envs/common.py
@@ -470,7 +470,7 @@ def reset(
     def numel(self) -> int:
         return prod(self.batch_size)
 
-    def set_seed(self, seed: int, static_seed: bool = False) -> int:
+    def set_seed(self, seed: Optional[int] = None, static_seed: bool = False) -> Optional[int]:
         """Sets the seed of the environment and returns the next seed to be used (which is the input seed if a single environment is present).
 
         Args:
@@ -491,6 +491,7 @@ def set_seed(self, seed: int, static_seed: bool = False) -> int:
             seed = new_seed
         return seed
 
+    @abc.abstractmethod
     def _set_seed(self, seed: Optional[int]):
         raise NotImplementedError
 
@@ -787,6 +788,7 @@ def __getattr__(self, attr: str) -> Any:
             f"env not set in {self.__class__.__name__}, cannot access {attr}"
         )
 
+    @abc.abstractmethod
     def _init_env(self) -> Optional[int]:
         """Runs all the necessary steps such that the environment is ready to use.
 
@@ -821,22 +823,7 @@ def close(self) -> None:
         except AttributeError:
             pass
 
-    def set_seed(
-        self, seed: Optional[int] = None, static_seed: bool = False
-    ) -> Optional[int]:
-        if seed is not None:
-            torch.manual_seed(seed)
-        self._set_seed(seed)
-        if seed is not None and not static_seed:
-            new_seed = seed_generator(seed)
-            seed = new_seed
-        return seed
-
-    @abc.abstractmethod
-    def _set_seed(self, seed: Optional[int]):
-        raise NotImplementedError
-
-
+        
 def make_tensordict(
     env: _EnvWrapper,
     policy: Optional[Callable[[TensorDictBase, ...], TensorDictBase]] = None,