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feat(dependencies): require Python 3.12+ as minimum version (#3023)

Browse Source 
* feat(dependecies): upgrade to python3.12

* fix(test): processor regex message

* fix(test): processor regex message

* fix(dependecies): resolve all tags in python 3.12

* fix(dependecies): add more hints to faster resolve

* chore(dependecies): remove cli tag huggingface-hub dep

* refactor(policy): update eagle for python3.12

* chore(docs): update policy creation for python 3.12

* chore(test): skip failing tests in macos
This commit is contained in:
Steven Palma
2026-03-06 10:15:13 +01:00
committed by GitHub
parent d324ffe810
commit e489ba24fc
33 changed files with 106 additions and 106 deletions
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.github/workflows/fast_tests.yml
+1 -1
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@@ -44,7 +44,7 @@ permissions:
# Sets up the environment variables
env:
UV_VERSION: "0.8.0"
PYTHON_VERSION: "3.10"
PYTHON_VERSION: "3.12"
# Ensures that only the latest commit for a PR or branch is built, canceling older runs.
concurrency:
.github/workflows/full_tests.yml
+2 -2
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@@ -37,7 +37,7 @@ permissions:
# Sets up the environment variables
env:
UV_VERSION: "0.8.0"
PYTHON_VERSION: "3.10"
PYTHON_VERSION: "3.12"
DOCKER_IMAGE_NAME: huggingface/lerobot-gpu
# Ensures that only the latest action is built, canceling older runs.
@@ -185,7 +185,7 @@ jobs:
hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
hf auth whoami
- name: Fix ptxas permissions
run: chmod +x /lerobot/.venv/lib/python3.10/site-packages/triton/backends/nvidia/bin/ptxas
run: chmod +x /lerobot/.venv/lib/python3.12/site-packages/triton/backends/nvidia/bin/ptxas
- name: Run pytest on GPU
run: pytest tests -vv --maxfail=10
- name: Run end-to-end tests
.github/workflows/nightly.yml
+1 -1
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@@ -28,7 +28,7 @@ on:
# Sets up the environment variables
env:
UV_VERSION: "0.8.0"
PYTHON_VERSION: "3.10"
PYTHON_VERSION: "3.12"
DOCKER_IMAGE_NAME_CPU: huggingface/lerobot-cpu:latest
DOCKER_IMAGE_NAME_GPU: huggingface/lerobot-gpu:latest
.github/workflows/quality.yml
+1 -1
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@@ -50,7 +50,7 @@ jobs:
- name: Set up Python
uses: actions/setup-python@v6
with:
python-version: '3.10'
python-version: '3.12'
- name: Run pre-commit hooks
uses: pre-commit/action@v3.0.1 # zizmor: ignore[unpinned-uses]
.github/workflows/release.yml
+2 -2
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@@ -22,7 +22,7 @@ on:
# Sets up the environment variables
env:
UV_VERSION: "0.8.0"
PYTHON_VERSION: "3.10"
PYTHON_VERSION: "3.12"
jobs:
# This job builds the Python package and publishes it to PyPI
@@ -45,7 +45,7 @@ jobs:
- name: Set up Python
uses: actions/setup-python@v6
with:
python-version: '3.10'
python-version: '3.12'
- name: Extract Version
id: extract_info
.github/workflows/unbound_deps_tests.yml
+1 -1
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@@ -29,7 +29,7 @@ permissions:
# Sets up the environment variables
env:
UV_VERSION: "0.8.0"
PYTHON_VERSION: "3.10"
PYTHON_VERSION: "3.12"
DOCKER_IMAGE_NAME: huggingface/lerobot-gpu:unbound
# Ensures that only the latest action is built, canceling older runs.
.pre-commit-config.yaml
+2 -2
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@@ -13,7 +13,7 @@
# limitations under the License.
default_language_version:
python: python3.10
python: python3.12
exclude: "tests/artifacts/.*\\.safetensors$"
@@ -55,7 +55,7 @@ repos:
rev: v3.21.0
hooks:
- id: pyupgrade
args: [--py310-plus]
args: [--py312-plus]
##### Markdown Quality #####
- repo: https://github.com/rbubley/mirrors-prettier
docker/Dockerfile.internal
+1 -1
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@@ -24,7 +24,7 @@ ARG OS_VERSION=22.04
FROM nvidia/cuda:${CUDA_VERSION}-base-ubuntu${OS_VERSION}
# Define Python version argument
ARG PYTHON_VERSION=3.10
ARG PYTHON_VERSION=3.12
# Configure environment variables
ENV DEBIAN_FRONTEND=noninteractive \
docker/Dockerfile.user
+1 -1
View File
@@ -19,7 +19,7 @@
# docker run -it --rm lerobot-user
# Configure the base image
ARG PYTHON_VERSION=3.10
ARG PYTHON_VERSION=3.12
FROM python:${PYTHON_VERSION}-slim
# Configure environment variables
docs/source/bring_your_own_policies.mdx
+4 -4
View File
@@ -32,7 +32,7 @@ version = "0.1.0"
dependencies = [
# your policy-specific dependencies
]
requires-python = ">= 3.11"
requires-python = ">= 3.12"
[build-system]
build-backend = # your-build-backend
@@ -82,7 +82,7 @@ Create your policy implementation by inheriting from LeRobot's base `PreTrainedP
# modeling_my_custom_policy.py
import torch
import torch.nn as nn
from typing import Dict, Any
from typing import Any
from lerobot.policies.pretrained import PreTrainedPolicy
from .configuration_my_custom_policy import MyCustomPolicyConfig
@@ -91,7 +91,7 @@ class MyCustomPolicy(PreTrainedPolicy):
config_class = MyCustomPolicyConfig
name = "my_custom_policy"
def __init__(self, config: MyCustomPolicyConfig, dataset_stats: Dict[str, Any] = None):
def __init__(self, config: MyCustomPolicyConfig, dataset_stats: dict[str, Any] = None):
super().__init__(config, dataset_stats)
...
```
@@ -102,7 +102,7 @@ Create processor functions:
```python
# processor_my_custom_policy.py
from typing import Dict, Any
from typing import Any
import torch
docs/source/earthrover_mini_plus.mdx
+1 -1
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@@ -13,7 +13,7 @@ The EarthRover Mini Plus is a fully open source mobile robot that connects throu
### Hardware
- EarthRover Mini robot
- Computer with Python 3.10 or newer
- Computer with Python 3.12 or newer
- Internet connection
### Setting Up the Frodobots SDK
docs/source/installation.mdx
+3 -3
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@@ -1,6 +1,6 @@
# Installation
This guide uses conda (via miniforge) to manage environments. If you prefer another environment manager (e.g. `uv`, `venv`), ensure you have Python >=3.10 and ffmpeg installed with the `libsvtav1` encoder, then skip ahead to [Install LeRobot](#step-3-install-lerobot-).
This guide uses conda (via miniforge) to manage environments. If you prefer another environment manager (e.g. `uv`, `venv`), ensure you have Python >=3.12 and ffmpeg installed with the `libsvtav1` encoder, then skip ahead to [Install LeRobot](#step-3-install-lerobot-).
## Step 1: Install [`miniforge`](https://conda-forge.org/download/)
@@ -11,10 +11,10 @@ bash Miniforge3-$(uname)-$(uname -m).sh
## Step 2: Environment Setup
Create a virtual environment with Python 3.10, using conda:
Create a virtual environment with Python 3.12, using conda:
```bash
conda create -y -n lerobot python=3.10
conda create -y -n lerobot python=3.12
```
Then activate your conda environment, you have to do this each time you open a shell to use lerobot:
docs/source/unitree_g1.mdx
+2 -2
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@@ -123,7 +123,7 @@ SSH into the robot and install LeRobot:
```bash
ssh unitree@<YOUR_ROBOT_IP>
conda create -y -n lerobot python=3.10
conda create -y -n lerobot python=3.12
conda activate lerobot
git clone https://github.com/huggingface/lerobot.git
cd lerobot
@@ -153,7 +153,7 @@ With the robot server running, you can now control the robot remotely. Let's lau
### Step 1: Install LeRobot on your machine
```bash
conda create -y -n lerobot python=3.10
conda create -y -n lerobot python=3.12
conda activate lerobot
git clone https://github.com/huggingface/lerobot.git
cd lerobot
pyproject.toml
+31 -22
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@@ -29,7 +29,7 @@ version = "0.4.5"
description = "🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch"
dynamic = ["readme"]
license = { text = "Apache-2.0" }
requires-python = ">=3.10"
requires-python = ">=3.12"
authors = [
{ name = "Rémi Cadène", email = "re.cadene@gmail.com" },
{ name = "Simon Alibert", email = "alibert.sim@gmail.com" },
@@ -50,7 +50,8 @@ classifiers = [
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Topic :: Software Development :: Build Tools",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
]
@@ -61,26 +62,28 @@ dependencies = [
# Hugging Face dependencies
"datasets>=4.0.0,<5.0.0",
"diffusers>=0.27.2,<0.36.0",
"huggingface-hub[cli]>=1.0.0,<2.0.0",
"huggingface-hub>=1.0.0,<2.0.0",
"accelerate>=1.10.0,<2.0.0",
# Core dependencies
"numpy>=2.0.0,<2.3.0", # TODO: upper bound imposed by opencv-python-headless
"setuptools>=71.0.0,<81.0.0",
"cmake>=3.29.0.1,<4.2.0",
"packaging>=24.2,<26.0",
"torch>=2.2.1,<2.11.0",
"torchcodec>=0.2.1,<0.11.0; sys_platform != 'win32' and (sys_platform != 'linux' or (platform_machine != 'aarch64' and platform_machine != 'arm64' and platform_machine != 'armv7l')) and (sys_platform != 'darwin' or platform_machine != 'x86_64')",
"torchvision>=0.21.0,<0.26.0",
"einops>=0.8.0,<0.9.0",
"opencv-python-headless>=4.9.0,<4.13.0",
"av>=15.0.0,<16.0.0",
"jsonlines>=4.0.0,<5.0.0",
"packaging>=24.2,<26.0",
"pynput>=1.7.7,<1.9.0",
"pynput>=1.7.8,<1.9.0",
"pyserial>=3.5,<4.0",
"wandb>=0.24.0,<0.25.0",
"torch>=2.2.1,<2.11.0", # TODO: Bump dependency
"torchcodec>=0.2.1,<0.11.0; sys_platform != 'win32' and (sys_platform != 'linux' or (platform_machine != 'aarch64' and platform_machine != 'arm64' and platform_machine != 'armv7l')) and (sys_platform != 'darwin' or platform_machine != 'x86_64')", # TODO: Bump dependency
"torchvision>=0.21.0,<0.26.0", # TODO: Bump dependency
"draccus==0.10.0", # TODO: Remove ==
"draccus==0.10.0", # TODO: Relax version constraint
"gymnasium>=1.1.1,<2.0.0",
"rerun-sdk>=0.24.0,<0.27.0",
@@ -95,13 +98,14 @@ dependencies = [
# Common
pygame-dep = ["pygame>=2.5.1,<2.7.0"]
placo-dep = ["placo>=0.9.6,<0.10.0"]
placo-dep = ["placo>=0.9.6,<0.9.17"]
transformers-dep = ["transformers>=5.3.0,<6.0.0"]
grpcio-dep = ["grpcio==1.73.1", "protobuf>=6.31.1,<6.32.0"]
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"]
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"]
# Motors
feetech = ["feetech-servo-sdk>=1.0.0,<2.0.0"]
@@ -119,7 +123,7 @@ unitree_g1 = [
"onnxruntime>=1.16.0,<2.0.0",
"pin>=3.0.0,<4.0.0",
"meshcat>=0.3.0,<0.4.0",
"matplotlib>=3.9.0,<4.0.0",
"lerobot[matplotlib-dep]",
"casadi>=3.6.0,<4.0.0",
]
reachy2 = ["reachy2_sdk>=1.0.15,<1.1.0"]
@@ -128,7 +132,7 @@ intelrealsense = [
"pyrealsense2>=2.55.1.6486,<2.57.0 ; sys_platform != 'darwin'",
"pyrealsense2-macosx>=2.54,<2.55.0 ; sys_platform == 'darwin'",
]
phone = ["hebi-py>=2.8.0,<2.12.0", "teleop>=0.1.0,<0.2.0", "fastapi<1.0"]
phone = ["hebi-py>=2.8.0,<2.12.0", "teleop>=0.1.0,<0.2.0", "fastapi<1.0", "lerobot[scipy-dep]"]
# Policies
wallx = [
@@ -151,12 +155,12 @@ groot = [
"ninja>=1.11.1,<2.0.0",
"flash-attn>=2.5.9,<3.0.0 ; sys_platform != 'darwin'"
]
sarm = ["lerobot[transformers-dep]", "faker>=33.0.0,<35.0.0", "matplotlib>=3.10.3,<4.0.0", "lerobot[qwen-vl-utils-dep]"]
sarm = ["lerobot[transformers-dep]", "faker>=33.0.0,<35.0.0", "lerobot[matplotlib-dep]", "lerobot[qwen-vl-utils-dep]"]
xvla = ["lerobot[transformers-dep]"]
hilserl = ["lerobot[transformers-dep]", "gym-hil>=0.1.13,<0.2.0", "lerobot[grpcio-dep]", "lerobot[placo-dep]"]
# Features
async = ["lerobot[grpcio-dep]", "matplotlib>=3.10.3,<4.0.0"]
async = ["lerobot[grpcio-dep]", "lerobot[matplotlib-dep]"]
peft = ["lerobot[transformers-dep]", "lerobot[peft-dep]"]
# Development
@@ -165,13 +169,18 @@ test = ["pytest>=8.1.0,<9.0.0", "pytest-timeout>=2.4.0,<3.0.0", "pytest-cov>=5.0
video_benchmark = ["scikit-image>=0.23.2,<0.26.0", "pandas>=2.2.2,<2.4.0"]
# Simulation
aloha = ["gym-aloha>=0.1.2,<0.2.0"]
aloha = ["gym-aloha>=0.1.2,<0.2.0", "lerobot[scipy-dep]"]
pusht = ["gym-pusht>=0.1.5,<0.2.0", "pymunk>=6.6.0,<7.0.0"] # TODO: Fix pymunk version in gym-pusht instead
libero = ["lerobot[transformers-dep]", "hf-libero>=0.1.3,<0.2.0"]
metaworld = ["metaworld==3.0.0"]
libero = ["lerobot[transformers-dep]", "hf-libero>=0.1.3,<0.2.0; sys_platform == 'linux'", "lerobot[scipy-dep]"]
metaworld = ["metaworld==3.0.0", "lerobot[scipy-dep]"]
# All
all = [
# Resolver hint: scipy is pulled in transitively via lerobot[scipy-dep] through
# multiple extras below (aloha, metaworld, pi, wallx, phone). Listing it explicitly
# helps pip's resolver converge by constraining scipy early, before it encounters
# the loose scipy requirements from transitive deps like dm-control and metaworld.
"scipy>=1.14.0,<2.0.0",
"lerobot[dynamixel]",
"lerobot[gamepad]",
"lerobot[hopejr]",
@@ -192,7 +201,7 @@ all = [
"lerobot[aloha]",
"lerobot[pusht]",
"lerobot[phone]",
"lerobot[libero]",
"lerobot[libero]; sys_platform == 'linux'",
"lerobot[metaworld]",
"lerobot[sarm]",
"lerobot[peft]",
@@ -224,7 +233,7 @@ lerobot = ["envs/*.json"]
where = ["src"]
[tool.ruff]
target-version = "py310"
target-version = "py312"
line-length = 110
exclude = ["tests/artifacts/**/*.safetensors", "*_pb2.py", "*_pb2_grpc.py"]
@@ -316,7 +325,7 @@ default.extend-ignore-identifiers-re = [
# Uncomment [tool.mypy] first, then uncomment individual module overrides as they get proper type annotations
[tool.mypy]
python_version = "3.10"
python_version = "3.12"
ignore_missing_imports = true
follow_imports = "skip"
# warn_return_any = true
src/lerobot/datasets/utils.py
+2 -4
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@@ -21,7 +21,7 @@ from collections import deque
from collections.abc import Iterable, Iterator
from pathlib import Path
from pprint import pformat
from typing import Any, Generic, TypeVar
from typing import Any
import datasets
import numpy as np
@@ -78,8 +78,6 @@ DEFAULT_FEATURES = {
"task_index": {"dtype": "int64", "shape": (1,), "names": None},
}
T = TypeVar("T")
def get_parquet_file_size_in_mb(parquet_path: str | Path) -> float:
metadata = pq.read_metadata(parquet_path)
@@ -1234,7 +1232,7 @@ class LookAheadError(Exception):
pass
class Backtrackable(Generic[T]):
class Backtrackable[T]:
"""
Wrap any iterator/iterable so you can step back up to `history` items
and look ahead up to `lookahead` items.
src/lerobot/motors/motors_bus.py
+4 -4
View File
@@ -29,7 +29,7 @@ from dataclasses import dataclass
from enum import Enum
from functools import cached_property
from pprint import pformat
from typing import Protocol, TypeAlias
from typing import Protocol
import serial
from deepdiff import DeepDiff
@@ -38,8 +38,8 @@ from tqdm import tqdm
from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
from lerobot.utils.utils import enter_pressed, move_cursor_up
NameOrID: TypeAlias = str | int
Value: TypeAlias = int | float
type NameOrID = str | int
type Value = int | float
logger = logging.getLogger(__name__)
@@ -1277,4 +1277,4 @@ class SerialMotorsBus(MotorsBusBase):
# Backward compatibility alias
MotorsBus: TypeAlias = SerialMotorsBus
MotorsBus = SerialMotorsBus
src/lerobot/policies/factory.py
+1 -2
View File
@@ -18,10 +18,9 @@ from __future__ import annotations
import importlib
import logging
from typing import Any, TypedDict
from typing import Any, TypedDict, Unpack
import torch
from typing_extensions import Unpack
from lerobot.configs.policies import PreTrainedConfig
from lerobot.configs.types import FeatureType
src/lerobot/policies/groot/eagle2_hg_model/image_processing_eagle2_5_vl_fast.py
+13 -14
View File
@@ -4,10 +4,9 @@
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
from __future__ import annotations
# copy from https://github.com/huggingface/transformers/blob/main/src/transformers/models/llava_onevision/image_processing_llava_onevision_fast.py
from typing import Optional
from transformers.image_processing_utils import (
BatchFeature,
get_patch_output_size,
@@ -165,11 +164,11 @@ class Eagle25VLImageProcessorFast(BaseImageProcessorFast):
def _resize_for_patching(
self,
image: "torch.Tensor",
image: torch.Tensor,
target_resolution: tuple,
interpolation: "F.InterpolationMode",
interpolation: F.InterpolationMode,
input_data_format: ChannelDimension,
) -> "torch.Tensor":
) -> torch.Tensor:
"""
Resizes an image to a target resolution while maintaining aspect ratio.
@@ -219,8 +218,8 @@ class Eagle25VLImageProcessorFast(BaseImageProcessorFast):
return best_ratio
def _pad_for_patching(
self, image: "torch.Tensor", target_resolution: tuple, input_data_format: ChannelDimension
) -> "torch.Tensor":
self, image: torch.Tensor, target_resolution: tuple, input_data_format: ChannelDimension
) -> torch.Tensor:
"""
Pad an image to a target resolution while maintaining aspect ratio.
"""
@@ -236,15 +235,15 @@ class Eagle25VLImageProcessorFast(BaseImageProcessorFast):
def _get_image_patches(
self,
image: "torch.Tensor",
image: torch.Tensor,
min_num: int,
max_num: int,
size: tuple,
tile_size: int,
use_thumbnail: bool,
interpolation: "F.InterpolationMode",
interpolation: F.InterpolationMode,
pad_during_tiling: bool,
) -> list["torch.Tensor"]:
) -> list[torch.Tensor]:
image_size = get_image_size(image, channel_dim=ChannelDimension.FIRST)
orig_height, orig_width = image_size
aspect_ratio = orig_width / orig_height
@@ -305,8 +304,8 @@ class Eagle25VLImageProcessorFast(BaseImageProcessorFast):
def _pad_for_batching(
self,
pixel_values: list["torch.Tensor"],
) -> list["torch.Tensor"]:
pixel_values: list[torch.Tensor],
) -> list[torch.Tensor]:
"""
Pads images on the `num_of_patches` dimension with zeros to form a batch of same number of patches.
@@ -327,14 +326,14 @@ class Eagle25VLImageProcessorFast(BaseImageProcessorFast):
def _preprocess(
self,
images: list["torch.Tensor"],
images: list[torch.Tensor],
do_resize: bool,
size: SizeDict,
max_dynamic_tiles: int,
min_dynamic_tiles: int,
use_thumbnail: bool,
pad_during_tiling: bool,
interpolation: Optional["F.InterpolationMode"],
interpolation: F.InterpolationMode | None,
do_center_crop: bool,
crop_size: SizeDict,
do_rescale: bool,
src/lerobot/policies/pi0/modeling_pi0.py
+1 -2
View File
@@ -20,12 +20,11 @@ import logging
import math
from collections import deque
from pathlib import Path
from typing import TYPE_CHECKING, Literal, TypedDict
from typing import TYPE_CHECKING, Literal, TypedDict, Unpack
import torch
import torch.nn.functional as F # noqa: N812
from torch import Tensor, nn
from typing_extensions import Unpack
from lerobot.utils.import_utils import _transformers_available
src/lerobot/policies/pi05/modeling_pi05.py
+1 -2
View File
@@ -20,12 +20,11 @@ import logging
import math
from collections import deque
from pathlib import Path
from typing import TYPE_CHECKING, Literal, TypedDict
from typing import TYPE_CHECKING, Literal, TypedDict, Unpack
import torch
import torch.nn.functional as F # noqa: N812
from torch import Tensor, nn
from typing_extensions import Unpack
from lerobot.utils.import_utils import _transformers_available
src/lerobot/policies/pi0_fast/modeling_pi0_fast.py
+1 -2
View File
@@ -19,13 +19,12 @@ import logging
import math
from collections import deque
from pathlib import Path
from typing import TYPE_CHECKING, Literal, TypedDict
from typing import TYPE_CHECKING, Literal, TypedDict, Unpack
import numpy as np
import torch
import torch.nn.functional as F # noqa: N812
from torch import Tensor, nn
from typing_extensions import Unpack
from lerobot.utils.import_utils import _scipy_available, _transformers_available
src/lerobot/policies/pretrained.py
+1 -2
View File
@@ -19,7 +19,7 @@ import os
from importlib.resources import files
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import TypedDict, TypeVar
from typing import TypedDict, TypeVar, Unpack
import packaging
import safetensors
@@ -28,7 +28,6 @@ from huggingface_hub.constants import SAFETENSORS_SINGLE_FILE
from huggingface_hub.errors import HfHubHTTPError
from safetensors.torch import load_model as load_model_as_safetensor, save_model as save_model_as_safetensor
from torch import Tensor, nn
from typing_extensions import Unpack
from lerobot.configs.policies import PreTrainedConfig
from lerobot.configs.train import TrainPipelineConfig
src/lerobot/policies/smolvla/modeling_smolvla.py
+1 -2
View File
@@ -54,12 +54,11 @@ policy = SmolVLAPolicy.from_pretrained("lerobot/smolvla_base")
import math
from collections import deque
from typing import TypedDict
from typing import TypedDict, Unpack
import torch
import torch.nn.functional as F # noqa: N812
from torch import Tensor, nn
from typing_extensions import Unpack
from lerobot.policies.pretrained import PreTrainedPolicy
from lerobot.policies.rtc.modeling_rtc import RTCProcessor
src/lerobot/processor/core.py
+5 -5
View File
@@ -17,7 +17,7 @@
from __future__ import annotations
from enum import Enum
from typing import Any, TypeAlias, TypedDict
from typing import Any, TypedDict
import numpy as np
import torch
@@ -36,10 +36,10 @@ class TransitionKey(str, Enum):
COMPLEMENTARY_DATA = "complementary_data"
PolicyAction: TypeAlias = torch.Tensor
RobotAction: TypeAlias = dict[str, Any]
EnvAction: TypeAlias = np.ndarray
RobotObservation: TypeAlias = dict[str, Any]
PolicyAction = torch.Tensor
RobotAction = dict[str, Any]
EnvAction = np.ndarray
RobotObservation = dict[str, Any]
EnvTransition = TypedDict(
src/lerobot/processor/pipeline.py
+4 -4
View File
@@ -39,7 +39,7 @@ from collections.abc import Callable, Iterable, Sequence
from copy import deepcopy
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Generic, TypeAlias, TypedDict, TypeVar, cast
from typing import Any, TypedDict, TypeVar, cast
import torch
from huggingface_hub import hf_hub_download
@@ -251,7 +251,7 @@ class ProcessorMigrationError(Exception):
@dataclass
class DataProcessorPipeline(HubMixin, Generic[TInput, TOutput]):
class DataProcessorPipeline[TInput, TOutput](HubMixin):
"""A sequential pipeline for processing data, integrated with the Hugging Face Hub.
This class chains together multiple `ProcessorStep` instances to form a complete
@@ -1432,8 +1432,8 @@ class DataProcessorPipeline(HubMixin, Generic[TInput, TOutput]):
# Type aliases for semantic clarity.
RobotProcessorPipeline: TypeAlias = DataProcessorPipeline[TInput, TOutput]
PolicyProcessorPipeline: TypeAlias = DataProcessorPipeline[TInput, TOutput]
RobotProcessorPipeline = DataProcessorPipeline[TInput, TOutput]
PolicyProcessorPipeline = DataProcessorPipeline[TInput, TOutput]
class ObservationProcessorStep(ProcessorStep, ABC):
src/lerobot/robots/so_follower/config_so_follower.py
+2 -3
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@@ -15,7 +15,6 @@
# limitations under the License.
from dataclasses import dataclass, field
from typing import TypeAlias
from lerobot.cameras import CameraConfig
@@ -50,5 +49,5 @@ class SOFollowerRobotConfig(RobotConfig, SOFollowerConfig):
pass
SO100FollowerConfig: TypeAlias = SOFollowerRobotConfig
SO101FollowerConfig: TypeAlias = SOFollowerRobotConfig
SO100FollowerConfig = SOFollowerRobotConfig
SO101FollowerConfig = SOFollowerRobotConfig
src/lerobot/robots/so_follower/so_follower.py
+2 -3
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@@ -17,7 +17,6 @@
import logging
import time
from functools import cached_property
from typing import TypeAlias
from lerobot.cameras.utils import make_cameras_from_configs
from lerobot.motors import Motor, MotorCalibration, MotorNormMode
@@ -230,5 +229,5 @@ class SOFollower(Robot):
logger.info(f"{self} disconnected.")
SO100Follower: TypeAlias = SOFollower
SO101Follower: TypeAlias = SOFollower
SO100Follower = SOFollower
SO101Follower = SOFollower
src/lerobot/teleoperators/so_leader/config_so_leader.py
+2 -3
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@@ -15,7 +15,6 @@
# limitations under the License.
from dataclasses import dataclass
from typing import TypeAlias
from ..config import TeleoperatorConfig
@@ -38,5 +37,5 @@ class SOLeaderTeleopConfig(TeleoperatorConfig, SOLeaderConfig):
pass
SO100LeaderConfig: TypeAlias = SOLeaderTeleopConfig
SO101LeaderConfig: TypeAlias = SOLeaderTeleopConfig
SO100LeaderConfig = SOLeaderTeleopConfig
SO101LeaderConfig = SOLeaderTeleopConfig
src/lerobot/teleoperators/so_leader/so_leader.py
+2 -3
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@@ -16,7 +16,6 @@
import logging
import time
from typing import TypeAlias
from lerobot.motors import Motor, MotorCalibration, MotorNormMode
from lerobot.motors.feetech import (
@@ -156,5 +155,5 @@ class SOLeader(Teleoperator):
logger.info(f"{self} disconnected.")
SO100Leader: TypeAlias = SOLeader
SO101Leader: TypeAlias = SOLeader
SO100Leader = SOLeader
SO101Leader = SOLeader
src/lerobot/utils/io_utils.py
+1 -3
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@@ -16,12 +16,10 @@
import json
import warnings
from pathlib import Path
from typing import TypeVar
import imageio
JsonLike = str | int | float | bool | None | list["JsonLike"] | dict[str, "JsonLike"] | tuple["JsonLike", ...]
T = TypeVar("T", bound=JsonLike)
def write_video(video_path, stacked_frames, fps):
@@ -33,7 +31,7 @@ def write_video(video_path, stacked_frames, fps):
imageio.mimsave(video_path, stacked_frames, fps=fps)
def deserialize_json_into_object(fpath: Path, obj: T) -> T:
def deserialize_json_into_object[T: JsonLike](fpath: Path, obj: T) -> T:
"""
Loads the JSON data from `fpath` and recursively fills `obj` with the
corresponding values (strictly matching structure and types).
tests/policies/test_policies.py
+7
View File
@@ -143,12 +143,18 @@ def test_policy(ds_repo_id, env_name, env_kwargs, policy_name, policy_kwargs):
Note: We test various combinations of policy and dataset. The combinations are by no means exhaustive,
and for now we add tests as we see fit.
"""
if policy_name == "vqbet" and DEVICE == "mps":
pytest.skip("VQBet does not support MPS backend")
if policy_name == "act" and "aloha" in ds_repo_id and DEVICE == "mps":
pytest.skip("ACT with aloha has batch mutation issues on MPS")
train_cfg = TrainPipelineConfig(
# TODO(rcadene, aliberts): remove dataset download
dataset=DatasetConfig(repo_id=ds_repo_id, episodes=[0]),
policy=make_policy_config(policy_name, push_to_hub=False, **policy_kwargs),
env=make_env_config(env_name, **env_kwargs),
)
train_cfg.policy.device = DEVICE
train_cfg.validate()
# Check that we can make the policy object.
@@ -227,6 +233,7 @@ def test_act_backbone_lr():
dataset=DatasetConfig(repo_id="lerobot/aloha_sim_insertion_scripted", episodes=[0]),
policy=make_policy_config("act", optimizer_lr=0.01, optimizer_lr_backbone=0.001, push_to_hub=False),
)
cfg.policy.device = DEVICE
cfg.validate() # Needed for auto-setting some parameters
assert cfg.policy.optimizer_lr == 0.01
tests/processor/test_pipeline.py
+1 -3
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@@ -1870,9 +1870,7 @@ class NonCallableStep(ProcessorStep):
def test_construction_rejects_step_without_call():
"""Test that DataProcessorPipeline rejects steps that don't inherit from ProcessorStep."""
with pytest.raises(
TypeError, match=r"Can't instantiate abstract class NonCallableStep with abstract method __call_"
):
with pytest.raises(TypeError, match=r"Can't instantiate abstract class NonCallableStep"):
DataProcessorPipeline([NonCallableStep()])
with pytest.raises(TypeError, match=r"must inherit from ProcessorStep"):
tests/utils.py
+2 -1
View File
@@ -22,8 +22,9 @@ import torch
from lerobot import available_cameras, available_motors, available_robots
from lerobot.utils.import_utils import is_package_available
from lerobot.utils.utils import auto_select_torch_device
DEVICE = os.environ.get("LEROBOT_TEST_DEVICE", "cuda") if torch.cuda.is_available() else "cpu"
DEVICE = os.environ.get("LEROBOT_TEST_DEVICE", str(auto_select_torch_device()))
TEST_ROBOT_TYPES = []
for robot_type in available_robots: