Files
lerobot/tests/utils/test_process.py
T
Khalil Meftah e963e5a0c4 RL stack refactoring (#3075)
* refactor: RL stack refactoring — RLAlgorithm, RLTrainer, DataMixer, and SAC restructuring

* chore: clarify torch.compile disabled note in SACAlgorithm

* fix(teleop): keyboard EE teleop not registering special keys and losing intervention state

Fixes #2345

Co-authored-by: jpizarrom <jpizarrom@gmail.com>

* fix: remove leftover normalization calls from reward classifier predict_reward

Fixes #2355

* fix: add thread synchronization to ReplayBuffer to prevent race condition between add() and sample()

* refactor: update SACAlgorithm to pass action_dim to _init_critics and fix encoder reference

* perf: remove redundant CPU→GPU→CPU transition move in learner

* Fix: add kwargs in reward classifier __init__()

* fix: include IS_INTERVENTION in complementary_info sent to learner for offline replay buffer

* fix: add try/finally to control_loop to ensure image writer cleanup on exit

* fix: use string key for IS_INTERVENTION in complementary_info to avoid torch.load serialization error

* fix: skip tests that require grpc if not available

* fix(tests): ensure tensor stats comparison accounts for reshaping in normalization tests

* fix(tests): skip tests that require grpc if not available

* refactor(rl): expose public API in rl/__init__ and use relative imports in sub-packages

* fix(config): update vision encoder model name to lerobot/resnet10

* fix(sac): clarify torch.compile status

* refactor(rl): update shutdown_event type hints from 'any' to 'Any' for consistency and clarity

* refactor(sac): simplify optimizer return structure

* perf(rl): use async iterators in OnlineOfflineMixer.get_iterator

* refactor(sac): decouple algorithm hyperparameters from policy config

* update losses names in tests

* fix docstring

* remove unused type alias

* fix test for flat dict structure

* refactor(policies): rename policies/sac → policies/gaussian_actor

* refactor(rl/sac): consolidate hyperparameter ownership and clean up discrete critic

* perf(observation_processor): add CUDA support for image processing

* fix(rl): correctly wire HIL-SERL gripper penalty through processor pipeline

(cherry picked from commit 9c2af818ff)

* fix(rl): add time limit processor to environment pipeline

(cherry picked from commit cd105f65cb)

* fix(rl): clarify discrete gripper action mapping in GripperVelocityToJoint for SO100

(cherry picked from commit 494f469a2b)

* fix(rl): update neutral gripper action

(cherry picked from commit 9c9064e5be)

* fix(rl): merge environment and action-processor info in transition processing

(cherry picked from commit 30e1886b64)

* fix(rl): mirror gym_manipulator in actor

(cherry picked from commit d2a046dfc5)

* fix(rl): postprocess action in actor

(cherry picked from commit c2556439e5)

* fix(rl): improve action processing for discrete and continuous actions

(cherry picked from commit f887ab3f6a)

* fix(rl): enhance intervention handling in actor and learner

(cherry picked from commit ef8bfffbd7)

* Revert "perf(observation_processor): add CUDA support for image processing"

This reverts commit 38b88c414c.

* refactor(rl): make algorithm a nested config so all SAC hyperparameters are JSON-addressable

* refactor(rl): add make_algorithm_config function for RLAlgorithmConfig instantiation

* refactor(rl): add type property to RLAlgorithmConfig for better clarity

* refactor(rl): make RLAlgorithmConfig an abstract base class for better extensibility

* refactor(tests): remove grpc import checks from test files for cleaner code

* fix(tests): gate RL tests on the `datasets` extra

* refactor: simplify docstrings for clarity and conciseness across multiple files

* fix(rl): update gripper position key and handle action absence during reset

* fix(rl): record pre-step observation so (obs, action, next.reward) align in gym_manipulator dataset

* refactor: clean up import statements

* chore: address reviewer comments

* chore: improve visual stats reshaping logic and update docstring for clarity

* refactor: enforce mandatory config_class and name attributes in RLAlgorithm

* refactor: implement NotImplementedError for abstract methods in RLAlgorithm and DataMixer

* refactor: replace build_algorithm with make_algorithm for SACAlgorithmConfig and update related tests

* refactor: add require_package calls for grpcio and gym-hil in relevant modules

* refactor(rl): move grpcio guards to runtime entry points

* feat(rl): consolidate HIL-SERL checkpoint into HF-style components

Make `RLAlgorithmConfig` and `RLAlgorithm` `HubMixin`s, add abstract
`state_dict()` / `load_state_dict()` for critic ensemble, target nets
and `log_alpha`, and persist them as a sibling `algorithm/` component
next to `pretrained_model/`. Replace the pickled `training_state.pt`
with an enriched `training_step.json` carrying `step` and
`interaction_step`, so resume restores actor + critics + target nets +
temperature + optimizers + RNG + counters from HF-standard files.

* refactor(rl): move actor weight-sync wire format from policy to algorithm

* refactor(rl): update type hints for learner and actor functions

* refactor(rl): hoist grpcio guard to module top in actor/learner

* chore(rl): manage import pattern in actor (#3564)

* chore(rl): manage import pattern in actor

* chore(rl): optional grpc imports in learner; quote grpc ServicerContext types

---------

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>

* update uv.lock

* chore(doc): update doc

---------

Co-authored-by: jpizarrom <jpizarrom@gmail.com>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
2026-05-12 15:49:54 +02:00

115 lines
3.8 KiB
Python

#!/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.
import multiprocessing
import os
import signal
import threading
from unittest.mock import patch
import pytest
pytest.importorskip("datasets", reason="datasets is required (install lerobot[dataset])")
from lerobot.utils.process import ProcessSignalHandler # noqa: E402
# Fixture to reset shutdown_event_counter and original signal handlers before and after each test
@pytest.fixture(autouse=True)
def reset_globals_and_handlers():
# Store original signal handlers
original_handlers = {
sig: signal.getsignal(sig)
for sig in [signal.SIGINT, signal.SIGTERM, signal.SIGHUP, signal.SIGQUIT]
if hasattr(signal, sig.name)
}
yield
# Restore original signal handlers
for sig, handler in original_handlers.items():
signal.signal(sig, handler)
def test_setup_process_handlers_event_with_threads():
"""Test that setup_process_handlers returns the correct event type."""
handler = ProcessSignalHandler(use_threads=True)
shutdown_event = handler.shutdown_event
assert isinstance(shutdown_event, threading.Event), "Should be a threading.Event"
assert not shutdown_event.is_set(), "Event should initially be unset"
def test_setup_process_handlers_event_with_processes():
"""Test that setup_process_handlers returns the correct event type."""
handler = ProcessSignalHandler(use_threads=False)
shutdown_event = handler.shutdown_event
assert isinstance(shutdown_event, type(multiprocessing.Event())), "Should be a multiprocessing.Event"
assert not shutdown_event.is_set(), "Event should initially be unset"
@pytest.mark.parametrize("use_threads", [True, False])
@pytest.mark.parametrize(
"sig",
[
signal.SIGINT,
signal.SIGTERM,
# SIGHUP and SIGQUIT are not reliably available on all platforms (e.g. Windows)
pytest.param(
signal.SIGHUP,
marks=pytest.mark.skipif(not hasattr(signal, "SIGHUP"), reason="SIGHUP not available"),
),
pytest.param(
signal.SIGQUIT,
marks=pytest.mark.skipif(not hasattr(signal, "SIGQUIT"), reason="SIGQUIT not available"),
),
],
)
def test_signal_handler_sets_event(use_threads, sig):
"""Test that the signal handler sets the event on receiving a signal."""
handler = ProcessSignalHandler(use_threads=use_threads)
shutdown_event = handler.shutdown_event
assert handler.counter == 0
os.kill(os.getpid(), sig)
# In some environments, the signal might take a moment to be handled.
shutdown_event.wait(timeout=1.0)
assert shutdown_event.is_set(), f"Event should be set after receiving signal {sig}"
# Ensure the internal counter was incremented
assert handler.counter == 1
@pytest.mark.parametrize("use_threads", [True, False])
@patch("sys.exit")
def test_force_shutdown_on_second_signal(mock_sys_exit, use_threads):
"""Test that a second signal triggers a force shutdown."""
handler = ProcessSignalHandler(use_threads=use_threads)
os.kill(os.getpid(), signal.SIGINT)
# Give a moment for the first signal to be processed
import time
time.sleep(0.1)
os.kill(os.getpid(), signal.SIGINT)
time.sleep(0.1)
assert handler.counter == 2
mock_sys_exit.assert_called_once_with(1)