[pre-commit.ci] auto fixes from pre-commit.com hooks

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src/lerobot/scripts/eval.py

@@ -46,6 +46,7 @@ Note that in both examples, the repo/folder should contain at least `config.json
 You can learn about the CLI options for this script in the `EvalPipelineConfig` in lerobot/configs/eval.py
 """
 
+import concurrent
 import json
 import logging
 import threading
@@ -56,7 +57,7 @@ from copy import deepcopy
 from dataclasses import asdict
 from pathlib import Path
 from pprint import pformat
-import concurrent
+
 import einops
 import gymnasium as gym
 import numpy as np
@@ -178,7 +179,7 @@ def rollout(
 
         with torch.inference_mode():
             action = policy.select_action(observation)
-        observation['observation.images.image']
+        observation["observation.images.image"]
         # Convert to CPU / numpy.
         action = action.to("cpu").numpy()
         assert action.ndim == 2, "Action dimensions should be (batch, action_dim)"
@@ -197,12 +198,11 @@ def rollout(
 
         # Keep track of which environments are done so far.
         # done = terminated | truncated | done
-        #TODO: jadechoghari changed, this is cleaner
+        # TODO: jadechoghari changed, this is cleaner
         done = terminated | truncated | done
         if step + 1 == max_steps:
             done = np.ones_like(done, dtype=bool)
 
-
         all_actions.append(torch.from_numpy(action))
         all_rewards.append(torch.from_numpy(reward))
         all_dones.append(torch.from_numpy(done))
@@ -480,16 +480,22 @@ def _compile_episode_data(
 
     return data_dict
 
+
 def set_global_seed(seed):
     """Set seed for reproducibility."""
     import random
+
     random.seed(seed)
     np.random.seed(seed)
     torch.manual_seed(seed)
     if torch.cuda.is_available():
         torch.cuda.manual_seed_all(seed)
+
+
 def log_output_dir(out_dir):
-    logging.info("Output dir:"+ f" {out_dir}")
+    logging.info("Output dir:" + f" {out_dir}")
+
+
 @parser.wrap()
 def eval(cfg: EvalPipelineConfig):
     logging.info(pformat(asdict(cfg)))