diff --git a/tianshou/data/collector.py b/tianshou/data/collector.py
index 133667f..cfc4b3d 100644
--- a/tianshou/data/collector.py
+++ b/tianshou/data/collector.py
@@ -255,18 +255,17 @@ class BaseCollector(ABC):
         n_episode: int | None = None,
         random: bool = False,
         render: float | None = None,
-        no_grad: bool = True,
         gym_reset_kwargs: dict[str, Any] | None = None,
     ) -> CollectStats:
         pass
 
+    @torch.no_grad()
     def collect(
         self,
         n_step: int | None = None,
         n_episode: int | None = None,
         random: bool = False,
         render: float | None = None,
-        no_grad: bool = True,
         reset_before_collect: bool = False,
         gym_reset_kwargs: dict[str, Any] | None = None,
     ) -> CollectStats:
@@ -304,7 +303,6 @@ class BaseCollector(ABC):
                 n_episode=n_episode,
                 random=random,
                 render=render,
-                no_grad=no_grad,
                 gym_reset_kwargs=gym_reset_kwargs,
             )
 
@@ -398,7 +396,6 @@ class Collector(BaseCollector):
         self,
         random: bool,
         ready_env_ids_R: np.ndarray,
-        use_grad: bool,
         last_obs_RO: np.ndarray,
         last_info_R: np.ndarray,
         last_hidden_state_RH: np.ndarray | torch.Tensor | Batch | None = None,
@@ -420,11 +417,10 @@ class Collector(BaseCollector):
             info_batch = _HACKY_create_info_batch(last_info_R)
             obs_batch_R = cast(ObsBatchProtocol, Batch(obs=last_obs_RO, info=info_batch))
 
-            with torch.set_grad_enabled(use_grad):
-                act_batch_RA = self.policy(
-                    obs_batch_R,
-                    last_hidden_state_RH,
-                )
+            act_batch_RA = self.policy(
+                obs_batch_R,
+                last_hidden_state_RH,
+            )
 
             act_RA = to_numpy(act_batch_RA.act)
             if self.exploration_noise:
@@ -454,7 +450,6 @@ class Collector(BaseCollector):
         n_episode: int | None = None,
         random: bool = False,
         render: float | None = None,
-        no_grad: bool = True,
         gym_reset_kwargs: dict[str, Any] | None = None,
     ) -> CollectStats:
         # TODO: can't do it init since AsyncCollector is currently a subclass of Collector
@@ -469,8 +464,6 @@ class Collector(BaseCollector):
         elif n_episode is not None:
             ready_env_ids_R = np.arange(min(self.env_num, n_episode))
 
-        use_grad = not no_grad
-
         start_time = time.time()
         if self._pre_collect_obs_RO is None or self._pre_collect_info_R is None:
             raise ValueError(
@@ -513,7 +506,6 @@ class Collector(BaseCollector):
             ) = self._compute_action_policy_hidden(
                 random=random,
                 ready_env_ids_R=ready_env_ids_R,
-                use_grad=use_grad,
                 last_obs_RO=last_obs_RO,
                 last_info_R=last_info_R,
                 last_hidden_state_RH=last_hidden_state_RH,
@@ -762,10 +754,8 @@ class AsyncCollector(Collector):
         n_episode: int | None = None,
         random: bool = False,
         render: float | None = None,
-        no_grad: bool = True,
         gym_reset_kwargs: dict[str, Any] | None = None,
     ) -> CollectStats:
-        use_grad = not no_grad
         start_time = time.time()
 
         step_count = 0
@@ -823,7 +813,6 @@ class AsyncCollector(Collector):
             ) = self._compute_action_policy_hidden(
                 random=random,
                 ready_env_ids_R=ready_env_ids_R,
-                use_grad=use_grad,
                 last_obs_RO=last_obs_RO,
                 last_info_R=last_info_R,
                 last_hidden_state_RH=last_hidden_state_RH,