SpeedTuning/pyproject.toml at main · DaivdYuan/SpeedTuning · GitHub

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[build-system]
requires = ["setuptools>=68", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "speedtuning-sim"
version = "0.1.0"
description = "Simulation tasks and speed-policy infrastructure for SpeedTuning"
readme = "README.md"
requires-python = ">=3.10,<3.11"
license = "MIT"
license-files = ["LICENSE", "NOTICE.md", "detr/LICENSE"]
authors = [{name = "David D. Yuan"}]
keywords = ["robotics", "reinforcement-learning", "mujoco", "action-chunking"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Science/Research",
    "Operating System :: POSIX :: Linux",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]
dependencies = [
    "dm-control==1.0.9",
    "mujoco==2.3.3",
    "numpy>=1.23,<2",
    "pyquaternion==0.9.9",
]

[project.optional-dependencies]
learned = [
    "einops>=0.6,<0.9",
    "packaging>=23,<26",
    "torch==2.5.1",
    "torchvision==0.20.1",
]
rl = ["torch==2.5.1"]
test = ["pytest>=8,<9"]
video = ["imageio>=2.31,<3", "imageio-ffmpeg>=0.4.9,<0.7"]
evaluation = ["matplotlib>=3.7,<4"]

[project.urls]
Paper = "https://doi.org/10.1109/ICRA55743.2025.11128753"
Preprint = "https://arxiv.org/abs/2608.09138"
"Project Page" = "https://daivdyuan.github.io/speed-tuning/"
Video = "https://daivdyuan.github.io/speed-tuning/static/videos/icra2025_final.mp4"
Repository = "https://github.com/DaivdYuan/SpeedTuning"
Documentation = "https://github.com/DaivdYuan/SpeedTuning/blob/main/docs/SCRIPTED_REPRODUCTION.md"
Issues = "https://github.com/DaivdYuan/SpeedTuning/issues"

[project.scripts]
speedtuning-sim = "scripts.run_sim:main"
speedtuning-check-chunks = "scripts.check_chunked_policy:main"
speedtuning-rainbow-poc = "scripts.rainbow_poc:main"
speedtuning-train-speed = "scripts.train_speed_policy:main"
speedtuning-eval-speed = "scripts.eval_speed_policy:main"
speedtuning-sweep = "scripts.sweep_speed_policy:main"

[tool.setuptools]
include-package-data = true
py-modules = [
    "act_integration",
    "chunked_policy",
    "constants",
    "ee_sim_env",
    "experiment_config",
    "policy",
    "policy_loader",
    "policy_speed_env",
    "scripted_policy",
    "sim_env",
    "sim_tasks",
    "speed_policy",
    "speed_evaluation",
    "speed_observation",
    "speed_training",
]

[tool.setuptools.packages.find]
include = ["assets", "configs*", "detr*", "rl*", "scripts*"]

[tool.setuptools.package-data]
assets = ["*.xml", "*.stl", "*.obj"]
configs = ["*.json", "*.md", "ablations/*.json"]

[tool.pytest.ini_options]
pythonpath = ["."]
testpaths = ["tests"]
markers = [
    "learned: requires the optional PyTorch/torchvision learned-policy stack",
    "rl: requires the optional PyTorch Rainbow DQN stack",
]