chore: replace hard-coded action values with constants throughout all the source code (#2055)

* chore: replace hard-coded 'action' values with constants throughout all the source code

* chore(tests): replace hard-coded action values with constants throughout all the test code
This commit is contained in:
Steven Palma
2025-09-26 13:33:18 +02:00
committed by GitHub
parent 9627765ce2
commit d2782cf66b
47 changed files with 269 additions and 255 deletions

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@@ -44,6 +44,7 @@ from lerobot.robots import ( # noqa: F401
so100_follower,
so101_follower,
)
from lerobot.utils.constants import ACTION
from lerobot.utils.robot_utils import busy_wait
from lerobot.utils.utils import (
init_logging,
@@ -78,16 +79,16 @@ def replay(cfg: ReplayConfig):
robot = make_robot_from_config(cfg.robot)
dataset = LeRobotDataset(cfg.dataset.repo_id, root=cfg.dataset.root, episodes=[cfg.dataset.episode])
actions = dataset.hf_dataset.select_columns("action")
actions = dataset.hf_dataset.select_columns(ACTION)
robot.connect()
log_say("Replaying episode", cfg.play_sounds, blocking=True)
for idx in range(dataset.num_frames):
start_episode_t = time.perf_counter()
action_array = actions[idx]["action"]
action_array = actions[idx][ACTION]
action = {}
for i, name in enumerate(dataset.features["action"]["names"]):
for i, name in enumerate(dataset.features[ACTION]["names"]):
key = f"{name.removeprefix('main_')}.pos"
action[key] = action_array[i].item()

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@@ -21,7 +21,7 @@ from lerobot.policies.factory import make_pre_post_processors
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 OBS_STR
from lerobot.utils.constants import ACTION, OBS_STR
from lerobot.utils.control_utils import init_keyboard_listener
from lerobot.utils.utils import log_say
from lerobot.utils.visualization_utils import init_rerun
@@ -42,7 +42,7 @@ robot = LeKiwiClient(robot_config)
policy = ACTPolicy.from_pretrained(HF_MODEL_ID)
# Configure the dataset features
action_features = hw_to_dataset_features(robot.action_features, "action")
action_features = hw_to_dataset_features(robot.action_features, ACTION)
obs_features = hw_to_dataset_features(robot.observation_features, OBS_STR)
dataset_features = {**action_features, **obs_features}

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@@ -22,7 +22,7 @@ from lerobot.robots.lekiwi.lekiwi_client import LeKiwiClient
from lerobot.scripts.lerobot_record import record_loop
from lerobot.teleoperators.keyboard import KeyboardTeleop, KeyboardTeleopConfig
from lerobot.teleoperators.so100_leader import SO100Leader, SO100LeaderConfig
from lerobot.utils.constants import OBS_STR
from lerobot.utils.constants import ACTION, OBS_STR
from lerobot.utils.control_utils import init_keyboard_listener
from lerobot.utils.utils import log_say
from lerobot.utils.visualization_utils import init_rerun
@@ -48,7 +48,7 @@ keyboard = KeyboardTeleop(keyboard_config)
teleop_action_processor, robot_action_processor, robot_observation_processor = make_default_processors()
# Configure the dataset features
action_features = hw_to_dataset_features(robot.action_features, "action")
action_features = hw_to_dataset_features(robot.action_features, ACTION)
obs_features = hw_to_dataset_features(robot.observation_features, OBS_STR)
dataset_features = {**action_features, **obs_features}

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@@ -19,6 +19,7 @@ import time
from lerobot.datasets.lerobot_dataset import LeRobotDataset
from lerobot.robots.lekiwi.config_lekiwi import LeKiwiClientConfig
from lerobot.robots.lekiwi.lekiwi_client import LeKiwiClient
from lerobot.utils.constants import ACTION
from lerobot.utils.robot_utils import busy_wait
from lerobot.utils.utils import log_say
@@ -34,7 +35,7 @@ robot = LeKiwiClient(robot_config)
dataset = LeRobotDataset("<hf_username>/<dataset_repo_id>", episodes=[EPISODE_IDX])
# Filter dataset to only include frames from the specified episode since episodes are chunked in dataset V3.0
episode_frames = dataset.hf_dataset.filter(lambda x: x["episode_index"] == EPISODE_IDX)
actions = episode_frames.select_columns("action")
actions = episode_frames.select_columns(ACTION)
# Connect to the robot
robot.connect()
@@ -49,7 +50,7 @@ for idx in range(len(episode_frames)):
# Get recorded action from dataset
action = {
name: float(actions[idx]["action"][i]) for i, name in enumerate(dataset.features["action"]["names"])
name: float(actions[idx][ACTION][i]) for i, name in enumerate(dataset.features[ACTION]["names"])
}
# Send action to robot

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@@ -28,6 +28,7 @@ from lerobot.robots.so100_follower.robot_kinematic_processor import (
InverseKinematicsEEToJoints,
)
from lerobot.robots.so100_follower.so100_follower import SO100Follower
from lerobot.utils.constants import ACTION
from lerobot.utils.robot_utils import busy_wait
from lerobot.utils.utils import log_say
@@ -66,7 +67,7 @@ robot_ee_to_joints_processor = RobotProcessorPipeline[tuple[RobotAction, RobotOb
dataset = LeRobotDataset(HF_REPO_ID, episodes=[EPISODE_IDX])
# Filter dataset to only include frames from the specified episode since episodes are chunked in dataset V3.0
episode_frames = dataset.hf_dataset.filter(lambda x: x["episode_index"] == EPISODE_IDX)
actions = episode_frames.select_columns("action")
actions = episode_frames.select_columns(ACTION)
# Connect to the robot
robot.connect()
@@ -81,7 +82,7 @@ for idx in range(len(episode_frames)):
# Get recorded action from dataset
ee_action = {
name: float(actions[idx]["action"][i]) for i, name in enumerate(dataset.features["action"]["names"])
name: float(actions[idx][ACTION][i]) for i, name in enumerate(dataset.features[ACTION]["names"])
}
# Get robot observation

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@@ -29,6 +29,7 @@ from lerobot.robots.so100_follower.robot_kinematic_processor import (
InverseKinematicsEEToJoints,
)
from lerobot.robots.so100_follower.so100_follower import SO100Follower
from lerobot.utils.constants import ACTION
from lerobot.utils.robot_utils import busy_wait
from lerobot.utils.utils import log_say
@@ -67,7 +68,7 @@ robot_ee_to_joints_processor = RobotProcessorPipeline[tuple[RobotAction, RobotOb
dataset = LeRobotDataset(HF_REPO_ID, episodes=[EPISODE_IDX])
# Filter dataset to only include frames from the specified episode since episodes are chunked in dataset V3.0
episode_frames = dataset.hf_dataset.filter(lambda x: x["episode_index"] == EPISODE_IDX)
actions = episode_frames.select_columns("action")
actions = episode_frames.select_columns(ACTION)
# Connect to the robot
robot.connect()
@@ -82,7 +83,7 @@ for idx in range(len(episode_frames)):
# Get recorded action from dataset
ee_action = {
name: float(actions[idx]["action"][i]) for i, name in enumerate(dataset.features["action"]["names"])
name: float(actions[idx][ACTION][i]) for i, name in enumerate(dataset.features[ACTION]["names"])
}
# Get robot observation