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Author SHA1 Message Date
dependabot[bot] fef1f0ca98 chore(deps): bump pytest in the uv group across 1 directory
Bumps the uv group with 1 update in the / directory: [pytest](https://github.com/pytest-dev/pytest).


Updates `pytest` from 8.4.2 to 9.0.3
- [Release notes](https://github.com/pytest-dev/pytest/releases)
- [Changelog](https://github.com/pytest-dev/pytest/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/pytest-dev/pytest/compare/8.4.2...9.0.3)

---
updated-dependencies:
- dependency-name: pytest
  dependency-version: 9.0.3
  dependency-type: direct:production
  dependency-group: uv
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-07-24 15:16:56 +00:00
Steven Palma ac5c7b8600 chore(deps): bump diffusers to >=0.38.0,<0.40.0 (#4145)
* fix(deps): bump diffusers cap to <0.39.0 (security)

Diffusers 0.35.x is affected by GHSA-98h9-4798-4q5v (HIGH, CVSS 8.8):
'trust_remote_code bypass via custom_pipeline and local custom components'.
Fixed in diffusers 0.38.0.

Current cap 'diffusers<0.36.0' blocks downstream consumers (e.g.
strands-labs/robots) from picking up the security fix.

The lerobot diffusers surface area is narrow and stable across 0.36-0.38:
- diffusers.schedulers.scheduling_ddim.DDIMScheduler
- diffusers.schedulers.scheduling_ddpm.DDPMScheduler
- diffusers.optimization.get_scheduler
- diffusers.ConfigMixin / ModelMixin / register_to_config
- diffusers.models.attention.{Attention,FeedForward}
- diffusers.models.embeddings.*

None of these were removed, renamed, or had breaking changes in 0.36, 0.37,
or 0.38 release notes. Bumping the cap to <0.39.0 unblocks the security
fix while keeping a major-version safety bound.

* chore(dependecies): bump diffusers

* chore(deps): update uv.lock

---------

Co-authored-by: Cagatay Cali <cagataycali@users.noreply.github.com>
2026-07-24 17:13:53 +02:00
Steven Palma a6befef0ba chore(dependencies): update uv.lock (#3963) 2026-07-24 16:30:36 +02:00
Steven Palma 53843007ea feat(robot): Make SO follower P coefficient configurable (#4142)
* Make SO follower P coefficient configurable

* chore(test): minimize tests

* feat(robots): expose PID coeff in SO arms

---------

Co-authored-by: taivu1998 <46636857+taivu1998@users.noreply.github.com>
2026-07-24 16:03:04 +02:00
Maxime Ellerbach d3bed0feee chore(agents): adding additional infos to AGENTS.md and bring-your-own-policies.mdx (#3904)
* chore(agents): adding additional infos to AGENTS.md

* adding `lerobot-train` requirement inside PR checklist

* prefer using code already implemented from transformers / diffusers instead of re-implementing in tree

---------

Signed-off-by: Maxime Ellerbach <maxime.ellerbach@huggingface.co>
2026-07-24 14:58:43 +02:00
13 changed files with 951 additions and 931 deletions
+2 -1
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@@ -51,6 +51,7 @@ pre-commit run --all-files # Lint + format (ruff, typo
## Notes
- **Mypy is gradual**: strict only for `lerobot.envs`, `lerobot.configs`, `lerobot.optim`, `lerobot.model`, `lerobot.cameras`, `lerobot.motors`, `lerobot.transport`. Add type annotations when modifying these modules.
- **Optional dependencies**: many policies, envs, and robots are behind extras (e.g., `lerobot[aloha]`). New imports for optional packages must be guarded or lazy. See `pyproject.toml [project.optional-dependencies]`.
- **Imports**: prefer top-level imports; relative (`from .sibling import X`) across sibling files within a module, absolute (`from lerobot.module import X`) across modules.
- **Optional dependencies**: many policies, envs, and robots are behind extras (e.g., `lerobot[aloha]`, see `pyproject.toml`). Guard optional imports with `TYPE_CHECKING or _foo_available` at module top + a `require_package(...)` check at use time. Reuse the `_foo_available` flags in `utils/import_utils.py`; don't call `is_package_available`.
- **Video decoding**: datasets can store observations as video files. `LeRobotDataset` handles frame extraction, but tests need ffmpeg installed.
- **Prioritize use of `uv run`** to execute Python commands (not raw `python` or `pip`).
+6 -1
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@@ -165,6 +165,8 @@ Batches are flat dictionaries keyed by the constants in [`lerobot.utils.constant
LeRobot uses `PolicyProcessorPipeline`s to normalize inputs and de-normalize outputs around your policy. For a concrete reference, see [`processor_act.py`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/act/processor_act.py) or [`processor_diffusion.py`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/diffusion/processor_diffusion.py).
Pay close attention here: processors are the most common reproducibility pain point. A mismatch in normalization mode (`IDENTITY` vs `MEAN_STD` vs `MIN_MAX` vs `QUANTILES`/`QUANTILE10`) or in which features get normalized will train and eval without erroring, yet silently wreck results. Make sure the modes match how the checkpoint was trained, that the required stats exist (e.g. `QUANTILES` needs `q01`/`q99`), and that the pre- and post-processors stay consistent.
```python
# processor_my_policy.py
from typing import Any
@@ -304,7 +306,9 @@ Mirror an existing policy that's structurally similar to yours; the diff is smal
### Heavy / optional dependencies
Most policies need a heavy backbone (transformers, diffusers, a specific VLM SDK). The convention is **two-step gating**: a `TYPE_CHECKING`-guarded import at module top, and a `require_package` runtime check in the constructor. [`modeling_diffusion.py`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/diffusion/modeling_diffusion.py) is the canonical reference:
Most policies need a heavy backbone (transformers, diffusers, a specific VLM SDK). Wherever one exists, prefer loading it e.g from `transformers` or `diffusers` rather than re-implementing the architecture in-tree.
The convention is **two-step gating**: a `TYPE_CHECKING`-guarded import at module top, and a `require_package` runtime check in the constructor. [`modeling_diffusion.py`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/diffusion/modeling_diffusion.py) is the canonical reference:
```python
from typing import TYPE_CHECKING
@@ -374,6 +378,7 @@ The general expectations are in [`CONTRIBUTING.md`](https://github.com/huggingfa
- [ ] Optional deps live behind a `[project.optional-dependencies]` extra and the `TYPE_CHECKING + require_package` guard.
- [ ] `tests/policies/` updated; backward-compat artifact committed & policy-specific tests.
- [ ] `src/lerobot/policies/<name>/README.md` symlinked into `docs/source/policy_<name>_README.md`; user-facing `docs/source/<name>.mdx` written and added to `_toctree.yml`.
- [ ] `lerobot-train --policy.type my_policy ...` runs end-to-end for at least a few steps + save a checkpoint that can be loaded and run by `lerobot-eval` or `lerobot-rollout`.
- [ ] `templates/lerobot_modelcard_template.md` has a description entry and a `policy_docs` link for your policy.
- [ ] The models table in the root `README.md` lists your policy in the right category, linking to your doc page.
- [ ] At least one reproducible benchmark eval in the policy MDX with a published checkpoint (sim benchmark, or real-robot dataset + checkpoint).
+2 -2
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@@ -155,7 +155,7 @@ accelerate-dep = ["accelerate>=1.14.0,<2.0.0"]
can-dep = ["python-can>=4.2.0,<5.0.0"]
peft-dep = ["peft>=0.18.0,<1.0.0"]
scipy-dep = ["scipy>=1.14.0,<2.0.0"]
diffusers-dep = ["diffusers>=0.27.2,<0.36.0"]
diffusers-dep = ["diffusers>=0.38.0,<0.40.0"]
qwen-vl-utils-dep = ["qwen-vl-utils>=0.0.11,<0.1.0"]
matplotlib-dep = ["matplotlib>=3.10.3,<4.0.0", "contourpy>=1.3.0,<2.0.0"] # NOTE: Explicitly listing contourpy helps the resolver converge faster.
pyserial-dep = ["pyserial>=3.5,<4.0"]
@@ -261,7 +261,7 @@ annotations = [
# Development
dev = ["pre-commit>=3.7.0,<5.0.0", "debugpy>=1.8.1,<1.9.0", "lerobot[grpcio-dep]", "grpcio-tools>=1.73.1,<2.0.0", "mypy>=1.19.1", "ruff>=0.14.1", "lerobot[notebook]"]
notebook = ["jupyter>=1.0.0,<2.0.0", "ipykernel>=6.0.0,<7.0.0"]
test = ["pytest>=8.1.0,<9.0.0", "pytest-timeout>=2.4.0,<3.0.0", "pytest-cov>=5.0.0,<8.0.0", "mock-serial>=0.0.1,<0.1.0 ; sys_platform != 'win32'"]
test = ["pytest>=8.1.0,<10.0.0", "pytest-timeout>=2.4.0,<3.0.0", "pytest-cov>=5.0.0,<8.0.0", "mock-serial>=0.0.1,<0.1.0 ; sys_platform != 'win32'"]
video_benchmark = ["scikit-image>=0.23.2,<0.26.0", "pandas>=2.2.2,<2.4.0"]
# Simulation
@@ -37,19 +37,13 @@ def is_image_feature(key: str) -> bool:
@dataclass
class ConcurrencyConfig:
"""Configuration for the concurrency of the actor and learner.
Possible values are:
- "threads": Use threads for the actor and learner.
- "processes": Use processes for the actor and learner.
``multiprocessing_context`` selects the process-wide start method when
processes are used. Set it to ``None`` to preserve Python's default or a
method already selected by the embedding application.
"""
actor: str = "threads"
learner: str = "threads"
multiprocessing_context: str | None = "spawn"
@dataclass
+4 -2
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@@ -91,7 +91,7 @@ from lerobot.robots import so_follower # noqa: F401
from lerobot.teleoperators import gamepad, so_leader # noqa: F401
from lerobot.teleoperators.utils import TeleopEvents
from lerobot.utils.device_utils import get_safe_torch_device
from lerobot.utils.process import ProcessSignalHandler, ensure_multiprocessing_start_method
from lerobot.utils.process import ProcessSignalHandler
from lerobot.utils.random_utils import set_seed
from lerobot.utils.robot_utils import precise_sleep
from lerobot.utils.transition import (
@@ -124,7 +124,9 @@ def actor_cli(cfg: TrainRLServerPipelineConfig):
cfg.validate()
display_pid = False
if not use_threads(cfg):
ensure_multiprocessing_start_method(cfg.policy.concurrency.multiprocessing_context)
import torch.multiprocessing as mp
mp.set_start_method("spawn")
display_pid = True
# Create logs directory to ensure it exists
+4 -2
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@@ -102,7 +102,7 @@ from lerobot.utils.constants import (
)
from lerobot.utils.device_utils import get_safe_torch_device
from lerobot.utils.io_utils import load_json, write_json
from lerobot.utils.process import ProcessSignalHandler, ensure_multiprocessing_start_method
from lerobot.utils.process import ProcessSignalHandler
from lerobot.utils.random_utils import set_seed
from lerobot.utils.utils import (
format_big_number,
@@ -123,7 +123,9 @@ def train_cli(cfg: TrainRLServerPipelineConfig):
# Fail fast with a friendly error if the optional ``hilserl`` extra is missing.
require_package("grpcio", extra="hilserl", import_name="grpc")
if not use_threads(cfg):
ensure_multiprocessing_start_method(cfg.policy.concurrency.multiprocessing_context)
import torch.multiprocessing as mp
mp.set_start_method("spawn")
# Use the job_name from the config
train(
@@ -58,6 +58,9 @@ class BiSOFollower(BimanualMixin, Robot):
port=config.left_arm_config.port,
disable_torque_on_disconnect=config.left_arm_config.disable_torque_on_disconnect,
max_relative_target=config.left_arm_config.max_relative_target,
position_p_coefficient=config.left_arm_config.position_p_coefficient,
position_i_coefficient=config.left_arm_config.position_i_coefficient,
position_d_coefficient=config.left_arm_config.position_d_coefficient,
use_degrees=config.left_arm_config.use_degrees,
cameras=left_arm_cameras,
)
@@ -68,6 +71,9 @@ class BiSOFollower(BimanualMixin, Robot):
port=config.right_arm_config.port,
disable_torque_on_disconnect=config.right_arm_config.disable_torque_on_disconnect,
max_relative_target=config.right_arm_config.max_relative_target,
position_p_coefficient=config.right_arm_config.position_p_coefficient,
position_i_coefficient=config.right_arm_config.position_i_coefficient,
position_d_coefficient=config.right_arm_config.position_d_coefficient,
use_degrees=config.right_arm_config.use_degrees,
cameras=config.right_arm_config.cameras,
)
@@ -41,6 +41,11 @@ class SOFollowerConfig:
# Set to `True` for backward compatibility with previous policies/dataset
use_degrees: bool = True
# Position-mode PID gains written to Feetech STS3215 motors at connect time.
position_p_coefficient: int = 16
position_i_coefficient: int = 0
position_d_coefficient: int = 32
@RobotConfig.register_subclass("so101_follower")
@RobotConfig.register_subclass("so100_follower")
@@ -161,11 +161,9 @@ class SOFollower(Robot):
self.bus.configure_motors()
for motor in self.bus.motors:
self.bus.write("Operating_Mode", motor, OperatingMode.POSITION.value)
# Set P_Coefficient to lower value to avoid shakiness (Default is 32)
self.bus.write("P_Coefficient", motor, 16)
# Set I_Coefficient and D_Coefficient to default value 0 and 32
self.bus.write("I_Coefficient", motor, 0)
self.bus.write("D_Coefficient", motor, 32)
self.bus.write("P_Coefficient", motor, self.config.position_p_coefficient)
self.bus.write("I_Coefficient", motor, self.config.position_i_coefficient)
self.bus.write("D_Coefficient", motor, self.config.position_d_coefficient)
if motor == "gripper":
self.bus.write("Max_Torque_Limit", motor, 500) # 50% of max torque to avoid burnout
-28
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@@ -16,39 +16,11 @@
# limitations under the License.
import logging
import multiprocessing
import os
import signal
import sys
def ensure_multiprocessing_start_method(start_method: str | None) -> None:
"""Set a multiprocessing start method once, or verify the existing method matches.
Passing ``None`` leaves Python's process-wide default untouched. This is useful
when LeRobot is embedded in an application that owns multiprocessing setup.
"""
if start_method is None:
return
available_methods = multiprocessing.get_all_start_methods()
if start_method not in available_methods:
raise ValueError(
f"Multiprocessing start method must be one of {available_methods} on this platform, "
f"got {start_method!r}."
)
current_method = multiprocessing.get_start_method(allow_none=True)
if current_method is None:
multiprocessing.set_start_method(start_method)
elif current_method != start_method:
raise RuntimeError(
f"Multiprocessing start method is already {current_method!r}; cannot change it to "
f"{start_method!r}. Set the configured multiprocessing context to null to keep the "
"application's existing method, or launch LeRobot in a fresh process."
)
class ProcessSignalHandler:
"""Utility class to attach graceful shutdown signal handlers.
@@ -113,7 +113,6 @@ def test_gaussian_actor_config_default_initialization():
# Concurrency configuration
assert config.concurrency.actor == "threads"
assert config.concurrency.learner == "threads"
assert config.concurrency.multiprocessing_context == "spawn"
assert isinstance(config.actor_network_kwargs, ActorNetworkConfig)
assert isinstance(config.policy_kwargs, PolicyConfig)
@@ -153,7 +152,6 @@ def test_concurrency_config():
config = ConcurrencyConfig()
assert config.actor == "threads"
assert config.learner == "threads"
assert config.multiprocessing_context == "spawn"
def test_gaussian_actor_config_custom_initialization():
+19
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@@ -109,3 +109,22 @@ def test_send_action(follower):
goal_pos = {m: (i + 1) * 10 for i, m in enumerate(follower.bus.motors)}
follower.bus.sync_write.assert_called_once_with("Goal_Position", goal_pos)
def test_configure_writes_position_pid_coefficients():
bus_mock = _make_bus_mock()
bus_mock.motors = ["shoulder_pan"]
robot = MagicMock()
robot.bus = bus_mock
robot.config = SO100FollowerConfig(
port="/dev/null",
position_p_coefficient=32,
position_i_coefficient=1,
position_d_coefficient=16,
)
SO100Follower.configure(robot)
bus_mock.write.assert_any_call("P_Coefficient", "shoulder_pan", 32)
bus_mock.write.assert_any_call("I_Coefficient", "shoulder_pan", 1)
bus_mock.write.assert_any_call("D_Coefficient", "shoulder_pan", 16)
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