[Quality] Remove global seeding in set_seed (#2195)

Author: Vincent Moens

test/test_transforms.py

@@ -9225,6 +9225,7 @@ def test_transform_compose(self):
     )
     def test_transform_env(self, out_key):
         base_env = self.envclass()
+        torch.manual_seed(0)
         actor = self._make_actor()
         # we need to patch the env and create a sample_log_prob spec to make check_env_specs happy
         env = TransformedEnv(
@@ -9234,6 +9235,7 @@ def test_transform_env(self, out_key):
                 KLRewardTransform(actor, out_keys=out_key),
             ),
         )
+        torch.manual_seed(0)
         actor = self._make_actor()
         td1 = env.rollout(3, actor)
         tdparams = TensorDict(dict(actor.named_parameters()), []).unflatten_keys(".")

torchrl/envs/batched_envs.py

@@ -1877,8 +1877,7 @@ def look_for_cuda(tensor, has_cuda=has_cuda):
         if cmd == "seed":
             if not initialized:
                 raise RuntimeError("call 'init' before closing")
-            # torch.manual_seed(data)
-            # np.random.seed(data)
+            torch.manual_seed(data[0])
             new_seed = env.set_seed(data[0], static_seed=data[1])
             child_pipe.send(("seeded", new_seed))
 

torchrl/envs/common.py

@@ -2218,17 +2218,16 @@ def set_seed(
         """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:
-            seed (int): seed to be set
+            seed (int): seed to be set. The seed is set only locally in the environment. To handle the global seed,
+                see :func:`~torch.manual_seed`.
             static_seed (bool, optional): if ``True``, the seed is not incremented.
                 Defaults to False
 
         Returns:
             integer representing the "next seed": i.e. the seed that should be
-            used for another environment if created concomittently to this environment.
+            used for another environment if created concomitantly to this environment.
 
         """
-        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)