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feat(rollout): decouple policy deployment from data recording with new lerobot-rollout CLI (#3413)

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* feat(scripts): lerobot-rollout

* fix(rollout) require dataset in dagger + use duration too

* fix(docs): dagger num_episodes

* test(rollout): fix expectations

* fix(rollout): features check

* fix(rollout): device and task propagation + feature pos + warn fps + move rename_map config

* docs(rollout): edit rename_map instructions

* chore(rollout): multiple minor improvements

* chore(rollout): address coments + minor improvements

* fix(rollout): enable default

* fix(tests): default value RTCConfig

* fix(rollout): robot_observation_processor and notify_observation at policy frequency instead of interpolator rate

Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* fix(rollout): prevent relativeactions with sync inference engine

Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* fix(rollout): rtc reanchor to non normalized state

Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* fix(rollout): fixing the episode length to use hwc (#3469)

also reducing default length to 5 minutes

* feat(rollout): go back to initial position is now a config

* fix(rollout): properly propagating video_files_size_in_mb to lerobot_dataset (#3470)

* chore(rollout): note about dagger correction stage

* chore(docs): update comments and docstring

* fix(test): move rtc relative out of rollout module

* fix(rollout): address the review comments

---------

Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Co-authored-by: Maxime Ellerbach <maxime.ellerbach@huggingface.co>
This commit is contained in:
Steven Palma
2026-04-28 00:57:35 +02:00
committed by GitHub
parent 77352c495c
commit ca87ccd941
62 changed files with 5577 additions and 2847 deletions
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examples/lekiwi/evaluate.py
+62 -31
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@@ -14,17 +14,21 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from lerobot.common.control_utils import init_keyboard_listener
import logging
import time
from lerobot.common.control_utils import init_keyboard_listener, predict_action
from lerobot.datasets import LeRobotDataset
from lerobot.policies import make_pre_post_processors
from lerobot.policies.act import ACTPolicy
from lerobot.policies.utils import make_robot_action
from lerobot.processor import make_default_processors
from lerobot.robots.lekiwi import LeKiwiClient, LeKiwiClientConfig
from lerobot.scripts.lerobot_record import record_loop
from lerobot.utils.constants import ACTION, OBS_STR
from lerobot.utils.feature_utils import hw_to_dataset_features
from lerobot.utils.feature_utils import build_dataset_frame, hw_to_dataset_features
from lerobot.utils.robot_utils import precise_sleep
from lerobot.utils.utils import log_say
from lerobot.utils.visualization_utils import init_rerun
from lerobot.utils.visualization_utils import init_rerun, log_rerun_data
NUM_EPISODES = 2
FPS = 30
@@ -35,6 +39,9 @@ HF_DATASET_ID = "<hf_username>/<eval_dataset_repo_id>"
def main():
# NOTE: For production policy deployment, use `lerobot-rollout` CLI instead.
# This script provides a self-contained example for educational purposes.
# Create the robot configuration & robot
robot_config = LeKiwiClientConfig(remote_ip="172.18.134.136", id="lekiwi")
@@ -83,43 +90,67 @@ def main():
raise ValueError("Robot is not connected!")
print("Starting evaluate loop...")
control_interval = 1 / FPS
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}")
# Main record loop
record_loop(
robot=robot,
events=events,
fps=FPS,
policy=policy,
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,
)
# Inline evaluation loop: predict actions and send to robot
timestamp = 0
start_episode_t = time.perf_counter()
while timestamp < EPISODE_TIME_SEC:
start_loop_t = time.perf_counter()
if events["exit_early"]:
events["exit_early"] = False
break
# Get robot observation
obs = robot.get_observation()
obs_processed = robot_observation_processor(obs)
observation_frame = build_dataset_frame(dataset.features, obs_processed, prefix=OBS_STR)
# Predict action using the policy
action_tensor = predict_action(
observation=observation_frame,
policy=policy,
device=policy.config.device,
preprocessor=preprocessor,
postprocessor=postprocessor,
use_amp=policy.config.device.type == "cuda",
task=TASK_DESCRIPTION,
robot_type=robot.name,
)
# Convert policy output to robot action dict
action_values = make_robot_action(action_tensor, dataset.features)
# Process and send action to robot
robot_action_to_send = robot_action_processor((action_values, obs))
robot.send_action(robot_action_to_send)
# Write to dataset
action_frame = build_dataset_frame(dataset.features, action_values, prefix=ACTION)
frame = {**observation_frame, **action_frame, "task": TASK_DESCRIPTION}
dataset.add_frame(frame)
log_rerun_data(observation=obs_processed, action=action_values)
dt_s = time.perf_counter() - start_loop_t
sleep_time_s = control_interval - dt_s
if sleep_time_s < 0:
logging.warning(
f"Evaluate loop is running slower ({1 / dt_s:.1f} Hz) than the target FPS ({FPS} Hz)."
)
precise_sleep(max(sleep_time_s, 0.0))
timestamp = time.perf_counter() - start_episode_t
# Reset the environment if not stopping or re-recording
if not events["stop_recording"] and (
(recorded_episodes < NUM_EPISODES - 1) or events["rerecord_episode"]
):
log_say("Reset the environment")
record_loop(
robot=robot,
events=events,
fps=FPS,
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,
)
log_say("Waiting for environment reset, press right arrow key when ready...")
if events["rerecord_episode"]:
log_say("Re-record episode")