chore(examples): homogenize style across example files (#1955)

* chore(examples): homogenize style across example files

* chore(examples): homogenize style across example files eval + replay

* chore(examples): homogenize headers

examples/lekiwi/evaluate.py

@@ -1,7 +1,24 @@
+# !/usr/bin/env python
+
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 from lerobot.datasets.lerobot_dataset import LeRobotDataset
 from lerobot.datasets.utils import hw_to_dataset_features
 from lerobot.policies.act.modeling_act import ACTPolicy
 from lerobot.policies.factory import make_pre_post_processors
+from lerobot.processor import make_default_processors
 from lerobot.record import record_loop
 from lerobot.robots.lekiwi import LeKiwiClient, LeKiwiClientConfig
 from lerobot.utils.control_utils import init_keyboard_listener
@@ -15,10 +32,12 @@ TASK_DESCRIPTION = "My task description"
 HF_MODEL_ID = "<hf_username>/<model_repo_id>"
 HF_DATASET_ID = "<hf_username>/<eval_dataset_repo_id>"
 
-# Create the robot and teleoperator configurations
+# Create the robot configuration & robot
 robot_config = LeKiwiClientConfig(remote_ip="172.18.134.136", id="lekiwi")
+
 robot = LeKiwiClient(robot_config)
 
+# Create policy
 policy = ACTPolicy.from_pretrained(HF_MODEL_ID)
 
 # Configure the dataset features
@@ -36,41 +55,50 @@ dataset = LeRobotDataset.create(
     image_writer_threads=4,
 )
 
-# To connect you already should have this script running on LeKiwi: `python -m lerobot.robots.lekiwi.lekiwi_host --robot.id=my_awesome_kiwi`
-robot.connect()
-
-_init_rerun(session_name="recording")
-
-listener, events = init_keyboard_listener()
-
-if not robot.is_connected:
-    raise ValueError("Robot is not connected!")
-
+# Build Policy Processors
 preprocessor, postprocessor = make_pre_post_processors(
     policy_cfg=policy,
     pretrained_path=HF_MODEL_ID,
     dataset_stats=dataset.meta.stats,
 )
 
+# Connect the robot
+# To connect you already should have this script running on LeKiwi: `python -m lerobot.robots.lekiwi.lekiwi_host --robot.id=my_awesome_kiwi`
+robot.connect()
+
+# TODO(Steven): Update this example to use pipelines
+teleop_action_processor, robot_action_processor, robot_observation_processor = make_default_processors()
+
+# Initialize the keyboard listener and rerun visualization
+listener, events = init_keyboard_listener()
+_init_rerun(session_name="lekiwi_evaluate")
+
+if not robot.is_connected:
+    raise ValueError("Robot is not connected!")
+
+print("Starting evaluate loop...")
 recorded_episodes = 0
 while recorded_episodes < NUM_EPISODES and not events["stop_recording"]:
     log_say(f"Running inference, recording eval episode {recorded_episodes} of {NUM_EPISODES}")
 
-    # Run the policy inference loop
+    # Main record loop
     record_loop(
         robot=robot,
         events=events,
         fps=FPS,
         policy=policy,
-        preprocessor=preprocessor,
+        preprocessor=preprocessor,  # Pass the pre and post policy processors
         postprocessor=postprocessor,
         dataset=dataset,
         control_time_s=EPISODE_TIME_SEC,
         single_task=TASK_DESCRIPTION,
         display_data=True,
+        teleop_action_processor=teleop_action_processor,
+        robot_action_processor=robot_action_processor,
+        robot_observation_processor=robot_observation_processor,
     )
 
-    # Logic for reset env
+    # Reset the environment if not stopping or re-recording
     if not events["stop_recording"] and (
         (recorded_episodes < NUM_EPISODES - 1) or events["rerecord_episode"]
     ):
@@ -82,6 +110,9 @@ while recorded_episodes < NUM_EPISODES and not events["stop_recording"]:
             control_time_s=EPISODE_TIME_SEC,
             single_task=TASK_DESCRIPTION,
             display_data=True,
+            teleop_action_processor=teleop_action_processor,
+            robot_action_processor=robot_action_processor,
+            robot_observation_processor=robot_observation_processor,
         )
 
     if events["rerecord_episode"]:
@@ -91,11 +122,12 @@ while recorded_episodes < NUM_EPISODES and not events["stop_recording"]:
         dataset.clear_episode_buffer()
         continue
 
+    # Save episode
     dataset.save_episode()
     recorded_episodes += 1
 
-# Upload to hub and clean up
-dataset.push_to_hub()
-
+# Clean up
+log_say("Stop recording")
 robot.disconnect()
 listener.stop()
+dataset.push_to_hub()