From c20bf75ba0bb7a55ecde0f22dcd2bfc4ec64238b Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sun, 10 Aug 2025 05:33:22 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/lerobot/envs/libero.py  | 5 +++--
 src/lerobot/scripts/eval.py | 1 -
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/src/lerobot/envs/libero.py b/src/lerobot/envs/libero.py
index 2c7ee0808..121728abf 100644
--- a/src/lerobot/envs/libero.py
+++ b/src/lerobot/envs/libero.py
@@ -174,7 +174,7 @@ class LiberoEnv(gym.Env):
         self.camera_name = camera_name.split(
             ","
         )  # agentview_image (main) or robot0_eye_in_hand_image (wrist)
-        #TODO: jadechoghari, check mapping
+        # TODO: jadechoghari, check mapping
         self.camera_name_mapping = {
             "agentview_image": OBS_IMAGE,
             "robot0_eye_in_hand_image": OBS_IMAGE_2,
@@ -222,7 +222,7 @@ class LiberoEnv(gym.Env):
                     "agent_pos": spaces.Box(
                         low=-1000.0,
                         high=1000.0,
-                        shape=(8,), #TODO: jadechoghari, check compatible
+                        shape=(8,),  # TODO: jadechoghari, check compatible
                         dtype=np.float64,
                     ),
                 }
@@ -309,6 +309,7 @@ class LiberoEnv(gym.Env):
             print(self.task, self.task_id, done, is_success)
         truncated = False
         return observation, reward, terminated, truncated, info
+
     def step(self, action):
         assert action.ndim == 1
         raw_obs, reward, done, info = self._env.step(action)
diff --git a/src/lerobot/scripts/eval.py b/src/lerobot/scripts/eval.py
index 09ea1da85..a3c7d822c 100644
--- a/src/lerobot/scripts/eval.py
+++ b/src/lerobot/scripts/eval.py
@@ -189,7 +189,6 @@ def rollout(
         running_success_rate = (
             # einops.reduce(torch.stack(all_successes, dim=1), "b n -> b", "any").numpy().mean() #TODO: changed by jade
             einops.reduce(torch.stack(all_successes, dim=1), "b n -> b", "max")
-
         )
         progbar.set_postfix({"running_success_rate": f"{running_success_rate.item() * 100:.1f}%"})
         progbar.update()