chore(utils): remove unused utils legacy functions + rename init_rerun (#2031)

src/lerobot/scripts/lerobot_record.py

@@ -122,7 +122,7 @@ from lerobot.utils.utils import (
     init_logging,
     log_say,
 )
-from lerobot.utils.visualization_utils import _init_rerun, log_rerun_data
+from lerobot.utils.visualization_utils import init_rerun, log_rerun_data
 
 
 @dataclass
@@ -378,7 +378,7 @@ def record(cfg: RecordConfig) -> LeRobotDataset:
     init_logging()
     logging.info(pformat(asdict(cfg)))
     if cfg.display_data:
-        _init_rerun(session_name="recording")
+        init_rerun(session_name="recording")
 
     robot = make_robot_from_config(cfg.robot)
     teleop = make_teleoperator_from_config(cfg.teleop) if cfg.teleop is not None else None

src/lerobot/scripts/lerobot_teleoperate.py

@@ -90,7 +90,7 @@ from lerobot.teleoperators import (  # noqa: F401
 )
 from lerobot.utils.robot_utils import busy_wait
 from lerobot.utils.utils import init_logging, move_cursor_up
-from lerobot.utils.visualization_utils import _init_rerun, log_rerun_data
+from lerobot.utils.visualization_utils import init_rerun, log_rerun_data
 
 
 @dataclass
@@ -185,7 +185,7 @@ def teleoperate(cfg: TeleoperateConfig):
     init_logging()
     logging.info(pformat(asdict(cfg)))
     if cfg.display_data:
-        _init_rerun(session_name="teleoperation")
+        init_rerun(session_name="teleoperation")
 
     teleop = make_teleoperator_from_config(cfg.teleop)
     robot = make_robot_from_config(cfg.robot)

src/lerobot/utils/robot_utils.py

@@ -27,17 +27,3 @@ def busy_wait(seconds):
         # On Linux time.sleep is accurate
         if seconds > 0:
             time.sleep(seconds)
-
-
-def safe_disconnect(func):
-    # TODO(aliberts): Allow to pass custom exceptions
-    # (e.g. ThreadServiceExit, KeyboardInterrupt, SystemExit, UnpluggedError, DynamixelCommError)
-    def wrapper(robot, *args, **kwargs):
-        try:
-            return func(robot, *args, **kwargs)
-        except Exception as e:
-            if robot.is_connected:
-                robot.disconnect()
-            raise e
-
-    return wrapper

src/lerobot/utils/train_utils.py

@@ -13,10 +13,8 @@
 # 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.
-import logging
 from pathlib import Path
 
-from termcolor import colored
 from torch.optim import Optimizer
 from torch.optim.lr_scheduler import LRScheduler
 
@@ -36,10 +34,6 @@ from lerobot.utils.constants import (
 from lerobot.utils.random_utils import load_rng_state, save_rng_state
 
 
-def log_output_dir(out_dir):
-    logging.info(colored("Output dir:", "yellow", attrs=["bold"]) + f" {out_dir}")
-
-
 def get_step_identifier(step: int, total_steps: int) -> str:
     num_digits = max(6, len(str(total_steps)))
     return f"{step:0{num_digits}d}"

src/lerobot/utils/utils.py

@@ -15,14 +15,13 @@
 # limitations under the License.
 import logging
 import os
-import os.path as osp
 import platform
 import select
 import subprocess
 import sys
 import time
 from copy import copy, deepcopy
-from datetime import datetime, timezone
+from datetime import datetime
 from pathlib import Path
 from statistics import mean
 
@@ -30,12 +29,6 @@ import numpy as np
 import torch
 
 
-def none_or_int(value):
-    if value == "None":
-        return None
-    return int(value)
-
-
 def inside_slurm():
     """Check whether the python process was launched through slurm"""
     # TODO(rcadene): return False for interactive mode `--pty bash`
@@ -165,36 +158,6 @@ def format_big_number(num, precision=0):
     return num
 
 
-def _relative_path_between(path1: Path, path2: Path) -> Path:
-    """Returns path1 relative to path2."""
-    path1 = path1.absolute()
-    path2 = path2.absolute()
-    try:
-        return path1.relative_to(path2)
-    except ValueError:  # most likely because path1 is not a subpath of path2
-        common_parts = Path(osp.commonpath([path1, path2])).parts
-        return Path(
-            "/".join([".."] * (len(path2.parts) - len(common_parts)) + list(path1.parts[len(common_parts) :]))
-        )
-
-
-def print_cuda_memory_usage():
-    """Use this function to locate and debug memory leak."""
-    import gc
-
-    gc.collect()
-    # Also clear the cache if you want to fully release the memory
-    torch.cuda.empty_cache()
-    print(f"Current GPU Memory Allocated: {torch.cuda.memory_allocated(0) / 1024**2:.2f} MB")
-    print(f"Maximum GPU Memory Allocated: {torch.cuda.max_memory_allocated(0) / 1024**2:.2f} MB")
-    print(f"Current GPU Memory Reserved: {torch.cuda.memory_reserved(0) / 1024**2:.2f} MB")
-    print(f"Maximum GPU Memory Reserved: {torch.cuda.max_memory_reserved(0) / 1024**2:.2f} MB")
-
-
-def capture_timestamp_utc():
-    return datetime.now(timezone.utc)
-
-
 def say(text: str, blocking: bool = False):
     system = platform.system()
 

src/lerobot/utils/visualization_utils.py

@@ -20,7 +20,7 @@ import numpy as np
 import rerun as rr
 
 
-def _init_rerun(session_name: str = "lerobot_control_loop") -> None:
+def init_rerun(session_name: str = "lerobot_control_loop") -> None:
     """Initializes the Rerun SDK for visualizing the control loop."""
     batch_size = os.getenv("RERUN_FLUSH_NUM_BYTES", "8000")
     os.environ["RERUN_FLUSH_NUM_BYTES"] = batch_size