remove internal rendering hooks

lerobot/common/envs/abstract.py

@@ -27,7 +27,6 @@ class AbstractEnv(EnvBase):
         self.image_size = image_size
         self.num_prev_obs = num_prev_obs
         self.num_prev_action = num_prev_action
-        self._rendering_hooks = []
 
         if pixels_only:
             assert from_pixels
@@ -45,16 +44,6 @@ class AbstractEnv(EnvBase):
             raise NotImplementedError()
             # self._prev_action_queue = deque(maxlen=self.num_prev_action)
 
-    def register_rendering_hook(self, func):
-        self._rendering_hooks.append(func)
-
-    def call_rendering_hooks(self):
-        for func in self._rendering_hooks:
-            func(self)
-
-    def reset_rendering_hooks(self):
-        self._rendering_hooks = []
-
     @abc.abstractmethod
     def render(self, mode="rgb_array", width=640, height=480):
         raise NotImplementedError()

lerobot/common/envs/aloha/env.py

@@ -164,7 +164,6 @@ class AlohaEnv(AbstractEnv):
             batch_size=[],
         )
 
-        self.call_rendering_hooks()
         return td
 
     def _step(self, tensordict: TensorDict):
@@ -189,8 +188,6 @@ class AlohaEnv(AbstractEnv):
                 stacked_obs["state"] = torch.stack(list(self._prev_obs_state_queue))
             obs = stacked_obs
 
-        self.call_rendering_hooks()
-
         td = TensorDict(
             {
                 "observation": TensorDict(obs, batch_size=[]),

lerobot/common/envs/pusht/env.py

@@ -116,7 +116,6 @@ class PushtEnv(AbstractEnv):
             batch_size=[],
         )
 
-        self.call_rendering_hooks()
         return td
 
     def _step(self, tensordict: TensorDict):
@@ -139,8 +138,6 @@ class PushtEnv(AbstractEnv):
                 stacked_obs["state"] = torch.stack(list(self._prev_obs_state_queue))
             obs = stacked_obs
 
-        self.call_rendering_hooks()
-
         td = TensorDict(
             {
                 "observation": TensorDict(obs, batch_size=[]),

lerobot/common/envs/simxarm.py

@@ -118,7 +118,6 @@ class SimxarmEnv(AbstractEnv):
         else:
             raise NotImplementedError()
 
-        self.call_rendering_hooks()
         return td
 
     def _step(self, tensordict: TensorDict):
@@ -152,8 +151,6 @@ class SimxarmEnv(AbstractEnv):
                     stacked_obs["state"] = torch.stack(list(self._prev_obs_state_queue))
                 obs = stacked_obs
 
-            self.call_rendering_hooks()
-
         td = TensorDict(
             {
                 "observation": self._format_raw_obs(raw_obs),

lerobot/scripts/eval.py

@@ -101,8 +101,6 @@ def eval_policy(
             if return_first_video and i == 0:
                 first_video = batch_stacked_frames[0].transpose(0, 3, 1, 2)
 
-    env.reset_rendering_hooks()
-
     for thread in threads:
         thread.join()