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13 Commits

Author SHA1 Message Date
Simon Alibert
624efd50c6 Remove _has_gym checks 2024-03-29 18:37:37 +01:00
Simon Alibert
7df64ba9b1 Remove envs dependencies 2024-03-29 17:27:42 +01:00
Simon Alibert
8505952e5a Update CI 2024-03-29 16:53:25 +01:00
Simon Alibert
f17b600198 Add aloha as package 2024-03-29 16:53:00 +01:00
Simon Alibert
8fc1008809 Fix imports 2024-03-29 16:47:18 +01:00
Simon Alibert
3d53e0fe0f Move make_env_task logic to aloha 2024-03-29 15:22:32 +01:00
Simon Alibert
b7b6c9bbf1 Package aloha 2024-03-29 14:45:21 +01:00
Simon Alibert
c41abc9a72 Update CI 2024-03-29 14:05:44 +01:00
Simon Alibert
8260a7010a Add xarm as package 2024-03-29 14:04:44 +01:00
Simon Alibert
3713a3a87b Package xarm 2024-03-29 13:59:09 +01:00
Simon Alibert
dfa6cc777f CI fix 2024-03-29 12:30:07 +01:00
Simon Alibert
c6002bb88f Add pusht as package 2024-03-29 12:03:49 +01:00
Simon Alibert
1d7ff65dc5 Package pusht 2024-03-29 11:29:05 +01:00
85 changed files with 2285 additions and 157 deletions

102
.github/poetry/cpu/poetry.lock generated vendored
View File

@@ -517,21 +517,11 @@ files = [
{file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"},
]
[[package]]
name = "dm"
version = "1.3"
description = "Dict to Data mapper"
optional = false
python-versions = "*"
files = [
{file = "dm-1.3.tar.gz", hash = "sha256:ce77537bf346b5d8c0dc0b5d679cfc4a946faadcd5315e6c80ef6f3af824130d"},
]
[[package]]
name = "dm-control"
version = "1.0.14"
description = "Continuous control environments and MuJoCo Python bindings."
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "dm_control-1.0.14-py3-none-any.whl", hash = "sha256:883c63244a7ebf598700a97564ed19fffd3479ca79efd090aed881609cdb9fc6"},
@@ -562,7 +552,7 @@ hdf5 = ["h5py"]
name = "dm-env"
version = "1.6"
description = "A Python interface for Reinforcement Learning environments."
optional = false
optional = true
python-versions = ">=3.7"
files = [
{file = "dm-env-1.6.tar.gz", hash = "sha256:a436eb1c654c39e0c986a516cee218bea7140b510fceff63f97eb4fcff3d93de"},
@@ -578,7 +568,7 @@ numpy = "*"
name = "dm-tree"
version = "0.1.8"
description = "Tree is a library for working with nested data structures."
optional = false
optional = true
python-versions = "*"
files = [
{file = "dm-tree-0.1.8.tar.gz", hash = "sha256:0fcaabbb14e7980377439e7140bd05552739ca5e515ecb3119f234acee4b9430"},
@@ -682,7 +672,7 @@ test = ["pytest (>=6)"]
name = "farama-notifications"
version = "0.0.4"
description = "Notifications for all Farama Foundation maintained libraries."
optional = false
optional = true
python-versions = "*"
files = [
{file = "Farama-Notifications-0.0.4.tar.gz", hash = "sha256:13fceff2d14314cf80703c8266462ebf3733c7d165336eee998fc58e545efd18"},
@@ -806,7 +796,7 @@ test = ["black", "coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre
name = "glfw"
version = "2.7.0"
description = "A ctypes-based wrapper for GLFW3."
optional = false
optional = true
python-versions = "*"
files = [
{file = "glfw-2.7.0-py2.py27.py3.py30.py31.py32.py33.py34.py35.py36.py37.py38-none-macosx_10_6_intel.whl", hash = "sha256:bd82849edcceda4e262bd1227afaa74b94f9f0731c1197863cd25c15bfc613fc"},
@@ -893,7 +883,7 @@ protobuf = ["grpcio-tools (>=1.62.1)"]
name = "gymnasium"
version = "0.29.1"
description = "A standard API for reinforcement learning and a diverse set of reference environments (formerly Gym)."
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "gymnasium-0.29.1-py3-none-any.whl", hash = "sha256:61c3384b5575985bb7f85e43213bcb40f36fcdff388cae6bc229304c71f2843e"},
@@ -923,7 +913,7 @@ toy-text = ["pygame (>=2.1.3)", "pygame (>=2.1.3)"]
name = "gymnasium-robotics"
version = "1.2.4"
description = "Robotics environments for the Gymnasium repo."
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "gymnasium-robotics-1.2.4.tar.gz", hash = "sha256:d304192b066f8b800599dfbe3d9d90bba9b761ee884472bdc4d05968a8bc61cb"},
@@ -1155,7 +1145,7 @@ i18n = ["Babel (>=2.7)"]
name = "labmaze"
version = "1.0.6"
description = "LabMaze: DeepMind Lab's text maze generator."
optional = false
optional = true
python-versions = "*"
files = [
{file = "labmaze-1.0.6-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b2ddef976dfd8d992b19cfa6c633f2eba7576d759c2082da534e3f727479a84a"},
@@ -1199,7 +1189,7 @@ setuptools = "!=50.0.0"
name = "lazy-loader"
version = "0.3"
description = "lazy_loader"
optional = false
optional = true
python-versions = ">=3.7"
files = [
{file = "lazy_loader-0.3-py3-none-any.whl", hash = "sha256:1e9e76ee8631e264c62ce10006718e80b2cfc74340d17d1031e0f84af7478554"},
@@ -1244,7 +1234,7 @@ files = [
name = "lxml"
version = "5.1.0"
description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API."
optional = false
optional = true
python-versions = ">=3.6"
files = [
{file = "lxml-5.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:704f5572ff473a5f897745abebc6df40f22d4133c1e0a1f124e4f2bd3330ff7e"},
@@ -1462,7 +1452,7 @@ tests = ["pytest (>=4.6)"]
name = "mujoco"
version = "2.3.7"
description = "MuJoCo Physics Simulator"
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "mujoco-2.3.7-cp310-cp310-macosx_10_16_x86_64.whl", hash = "sha256:e8714a5ff6a1561b364b7b4648d4c0c8d13e751874cf7401c309b9d23fa9598b"},
@@ -1776,7 +1766,7 @@ xml = ["lxml (>=4.9.2)"]
name = "pettingzoo"
version = "1.24.3"
description = "Gymnasium for multi-agent reinforcement learning."
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "pettingzoo-1.24.3-py3-none-any.whl", hash = "sha256:23ed90517d2e8a7098bdaf5e31234b3a7f7b73ca578d70d1ca7b9d0cb0e37982"},
@@ -2144,7 +2134,7 @@ dev = ["aafigure", "matplotlib", "pygame", "pyglet (<2.0.0)", "sphinx", "wheel"]
name = "pyopengl"
version = "3.1.7"
description = "Standard OpenGL bindings for Python"
optional = false
optional = true
python-versions = "*"
files = [
{file = "PyOpenGL-3.1.7-py3-none-any.whl", hash = "sha256:a6ab19cf290df6101aaf7470843a9c46207789855746399d0af92521a0a92b7a"},
@@ -2155,7 +2145,7 @@ files = [
name = "pyparsing"
version = "3.1.2"
description = "pyparsing module - Classes and methods to define and execute parsing grammars"
optional = false
optional = true
python-versions = ">=3.6.8"
files = [
{file = "pyparsing-3.1.2-py3-none-any.whl", hash = "sha256:f9db75911801ed778fe61bb643079ff86601aca99fcae6345aa67292038fb742"},
@@ -2586,7 +2576,7 @@ torch = ["safetensors[numpy]", "torch (>=1.10)"]
name = "scikit-image"
version = "0.22.0"
description = "Image processing in Python"
optional = false
optional = true
python-versions = ">=3.9"
files = [
{file = "scikit_image-0.22.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:74ec5c1d4693506842cc7c9487c89d8fc32aed064e9363def7af08b8f8cbb31d"},
@@ -2634,7 +2624,7 @@ test = ["asv", "matplotlib (>=3.5)", "numpydoc (>=1.5)", "pooch (>=1.6.0)", "pyt
name = "scipy"
version = "1.12.0"
description = "Fundamental algorithms for scientific computing in Python"
optional = false
optional = true
python-versions = ">=3.9"
files = [
{file = "scipy-1.12.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:78e4402e140879387187f7f25d91cc592b3501a2e51dfb320f48dfb73565f10b"},
@@ -2839,7 +2829,7 @@ testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jar
name = "shapely"
version = "2.0.3"
description = "Manipulation and analysis of geometric objects"
optional = false
optional = true
python-versions = ">=3.7"
files = [
{file = "shapely-2.0.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:af7e9abe180b189431b0f490638281b43b84a33a960620e6b2e8d3e3458b61a1"},
@@ -2892,6 +2882,55 @@ numpy = ">=1.14,<2"
docs = ["matplotlib", "numpydoc (==1.1.*)", "sphinx", "sphinx-book-theme", "sphinx-remove-toctrees"]
test = ["pytest", "pytest-cov"]
[[package]]
name = "sim-aloha"
version = "0.1.2"
description = "ALOHA environment for LeRobot"
optional = true
python-versions = "<4.0,>=3.10"
files = [
{file = "sim_aloha-0.1.2-py3-none-any.whl", hash = "sha256:3b13c1ee474481f5d686b57bf1a9ed350e01ca4da7d65f7501446eb74b02653a"},
{file = "sim_aloha-0.1.2.tar.gz", hash = "sha256:44d36bbdb13e98e0c74f4d2a682f38683f4f63951618da28175f89cbb1c6f324"},
]
[package.dependencies]
dm-control = "1.0.14"
[[package]]
name = "sim-pusht"
version = "0.1.0"
description = "PushT environment for LeRobot"
optional = true
python-versions = "<4.0,>=3.10"
files = [
{file = "sim_pusht-0.1.0-py3-none-any.whl", hash = "sha256:1348dcab5ea8460eff2dc97b7d62dd40f2a382df92bfdc69ff5c0224900690b0"},
{file = "sim_pusht-0.1.0.tar.gz", hash = "sha256:d8f6a2207fd781348156206728329aa6338e9785cfc07679c5c48889b34d9b14"},
]
[package.dependencies]
gymnasium = ">=0.29.1,<0.30.0"
opencv-python = ">=4.9.0.80,<5.0.0.0"
pygame = ">=2.5.2,<3.0.0"
pymunk = ">=6.6.0,<7.0.0"
scikit-image = ">=0.22.0,<0.23.0"
shapely = ">=2.0.3,<3.0.0"
[[package]]
name = "sim-xarm"
version = "0.1.0"
description = "xArm environment for LeRobot"
optional = true
python-versions = "<4.0,>=3.10"
files = [
{file = "sim_xarm-0.1.0-py3-none-any.whl", hash = "sha256:2771ca0e8d775dc7d9ccb3360e7fcf42507c5d4791525692e409f53ff5c83eaa"},
{file = "sim_xarm-0.1.0.tar.gz", hash = "sha256:90342394369ab37636a8c41a995ba20f1dac79c50563b1b1e4b38eeffbc5588d"},
]
[package.dependencies]
gymnasium = ">=0.29.1,<0.30.0"
gymnasium-robotics = ">=1.2.4,<2.0.0"
mujoco = ">=2.3.7,<3.0.0"
[[package]]
name = "six"
version = "1.16.0"
@@ -3031,7 +3070,7 @@ tests = ["pytest", "pytest-cov"]
name = "tifffile"
version = "2024.2.12"
description = "Read and write TIFF files"
optional = false
optional = true
python-versions = ">=3.9"
files = [
{file = "tifffile-2024.2.12-py3-none-any.whl", hash = "sha256:870998f82fbc94ff7c3528884c1b0ae54863504ff51dbebea431ac3fa8fb7c21"},
@@ -3327,7 +3366,12 @@ files = [
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
[extras]
aloha = ["sim-aloha"]
pusht = ["sim-pusht"]
xarm = ["sim-xarm"]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "8800bb8b24312d17b765cd2ce2799f49436171dd5fbf1bec3b07f853cfa9befd"
content-hash = "1203f5ffb62ef7146ce79be8353d37f0262ae5e6e63934b76084f50d569b10b9"

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@@ -1,19 +1,24 @@
[tool.poetry]
name = "lerobot"
version = "0.1.0"
description = "Le robot is learning"
description = "🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch"
authors = [
"Rémi Cadène <re.cadene@gmail.com>",
]
maintainers = [
"Alexander Soare <alexander.soare159@gmail.com>",
"Quentin Gallouédec <quentin.gallouedec@ec-lyon.fr>",
"Simon Alibert <alibert.sim@gmail.com>",
]
repository = "https://github.com/Cadene/lerobot"
readme = "README.md"
license = "MIT"
license = "Apache-2.0"
keywords = ["robotics, deep, reinforcement, learning, pytorch"]
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Topic :: Software Development :: Build Tools",
"License :: OSI Approved :: MIT License",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.10",
]
packages = [{include = "lerobot"}]
@@ -23,7 +28,6 @@ packages = [{include = "lerobot"}]
python = "^3.10"
termcolor = "^2.4.0"
omegaconf = "^2.3.0"
dm-env = "^1.6"
pandas = "^2.2.1"
wandb = "^0.16.3"
moviepy = "^1.0.3"
@@ -34,30 +38,35 @@ einops = "^0.7.0"
pygame = "^2.5.2"
pymunk = "^6.6.0"
zarr = "^2.17.0"
shapely = "^2.0.3"
scikit-image = "^0.22.0"
numba = "^0.59.0"
mpmath = "^1.3.0"
torch = {version = "^2.2.1", source = "torch-cpu"}
tensordict = {git = "https://github.com/pytorch/tensordict"}
torchrl = {git = "https://github.com/pytorch/rl", rev = "13bef426dcfa5887c6e5034a6e9697993fa92c37"}
mujoco = "^2.3.7"
opencv-python = "^4.9.0.80"
diffusers = "^0.26.3"
torchvision = {version = "^0.17.1", source = "torch-cpu"}
h5py = "^3.10.0"
dm = "^1.3"
dm-control = "1.0.14"
robomimic = "0.2.0"
huggingface-hub = "^0.21.4"
gymnasium-robotics = "^1.2.4"
gymnasium = "^0.29.1"
cmake = "^3.29.0.1"
sim-pusht = { version = "^0.1.0", optional = true}
sim-xarm = { version = "^0.1.0", optional = true}
sim-aloha = { version = "^0.1.2", optional = true}
[tool.poetry.extras]
pusht = ["sim-pusht"]
xarm = ["sim-xarm"]
aloha = ["sim-aloha"]
[tool.poetry.group.dev.dependencies]
pre-commit = "^3.6.2"
debugpy = "^1.8.1"
[tool.poetry.group.test.dependencies]
pytest = "^8.1.0"
pytest-cov = "^5.0.0"

View File

@@ -87,7 +87,7 @@ jobs:
TMP: ~/tmp
run: |
mkdir ~/tmp
poetry install --no-interaction --no-root
poetry install --no-interaction --no-root --without dev --all-extras
- name: Save cached venv
if: |
@@ -106,7 +106,7 @@ jobs:
# install project
#----------------------------------------------
- name: Install project
run: poetry install --no-interaction
run: poetry install --no-interaction --without dev --all-extras
#----------------------------------------------
# run tests & coverage

1
envs/sim_aloha/README.md Normal file
View File

@@ -0,0 +1 @@
# ALOHA environment for LeRobot

View File

@@ -0,0 +1,40 @@
from dm_control import mujoco
from dm_control.rl import control
from aloha.constants import ASSETS_DIR, DT
from aloha.tasks.sim import InsertionTask, TransferCubeTask
from aloha.tasks.sim_end_effector import (
InsertionEndEffectorTask,
TransferCubeEndEffectorTask,
)
def make_env_task(task_name):
# time limit is controlled by StepCounter in env factory
time_limit = float("inf")
if "sim_transfer_cube" in task_name:
xml_path = ASSETS_DIR / "bimanual_viperx_transfer_cube.xml"
physics = mujoco.Physics.from_xml_path(str(xml_path))
task = TransferCubeTask(random=False)
elif "sim_insertion" in task_name:
xml_path = ASSETS_DIR / "bimanual_viperx_insertion.xml"
physics = mujoco.Physics.from_xml_path(str(xml_path))
task = InsertionTask(random=False)
elif "sim_end_effector_transfer_cube" in task_name:
raise NotImplementedError()
xml_path = ASSETS_DIR / "bimanual_viperx_end_effector_transfer_cube.xml"
physics = mujoco.Physics.from_xml_path(str(xml_path))
task = TransferCubeEndEffectorTask(random=False)
elif "sim_end_effector_insertion" in task_name:
raise NotImplementedError()
xml_path = ASSETS_DIR / "bimanual_viperx_end_effector_insertion.xml"
physics = mujoco.Physics.from_xml_path(str(xml_path))
task = InsertionEndEffectorTask(random=False)
else:
raise NotImplementedError(task_name)
env = control.Environment(
physics, task, time_limit, control_timestep=DT, n_sub_steps=None, flat_observation=False
)
return env

View File

@@ -1,14 +1,13 @@
import collections
import numpy as np
from dm_control.suite import base
from lerobot.common.envs.aloha.constants import (
from aloha.constants import (
START_ARM_POSE,
normalize_puppet_gripper_position,
normalize_puppet_gripper_velocity,
unnormalize_puppet_gripper_position,
)
from dm_control.suite import base
BOX_POSE = [None] # to be changed from outside

View File

@@ -1,16 +1,15 @@
import collections
import numpy as np
from dm_control.suite import base
from lerobot.common.envs.aloha.constants import (
from aloha.constants import (
PUPPET_GRIPPER_POSITION_CLOSE,
START_ARM_POSE,
normalize_puppet_gripper_position,
normalize_puppet_gripper_velocity,
unnormalize_puppet_gripper_position,
)
from lerobot.common.envs.aloha.utils import sample_box_pose, sample_insertion_pose
from aloha.utils import sample_box_pose, sample_insertion_pose
from dm_control.suite import base
"""
Environment for simulated robot bi-manual manipulation, with end-effector control.

766
envs/sim_aloha/poetry.lock generated Normal file
View File

@@ -0,0 +1,766 @@
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
[[package]]
name = "absl-py"
version = "2.1.0"
description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
optional = false
python-versions = ">=3.7"
files = [
{file = "absl-py-2.1.0.tar.gz", hash = "sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff"},
{file = "absl_py-2.1.0-py3-none-any.whl", hash = "sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308"},
]
[[package]]
name = "certifi"
version = "2024.2.2"
description = "Python package for providing Mozilla's CA Bundle."
optional = false
python-versions = ">=3.6"
files = [
{file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
{file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
]
[[package]]
name = "charset-normalizer"
version = "3.3.2"
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
optional = false
python-versions = ">=3.7.0"
files = [
{file = "charset-normalizer-3.3.2.tar.gz", hash = "sha256:f30c3cb33b24454a82faecaf01b19c18562b1e89558fb6c56de4d9118a032fd5"},
{file = "charset_normalizer-3.3.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:25baf083bf6f6b341f4121c2f3c548875ee6f5339300e08be3f2b2ba1721cdd3"},
{file = "charset_normalizer-3.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:06435b539f889b1f6f4ac1758871aae42dc3a8c0e24ac9e60c2384973ad73027"},
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content-hash = "07c474dba5df862978c1e7f32a95edf4636ed9ba459c6f3e8c013ad1007a2884"

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[tool.poetry]
name = "sim_aloha"
version = "0.1.2"
description = "ALOHA environment for LeRobot"
authors = [
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maintainers = [
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"Quentin Gallouédec <quentin.gallouedec@ec-lyon.fr>",
"Simon Alibert <alibert.sim@gmail.com>",
]
readme = "README.md"
license = "Apache-2.0"
classifiers=[
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"Intended Audience :: Developers",
"Topic :: Software Development :: Build Tools",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.10",
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[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

1
envs/sim_pusht/README.md Normal file
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# PushT environment for LeRobot

675
envs/sim_pusht/poetry.lock generated Normal file
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@@ -11,7 +11,7 @@ import skimage.transform as st
from gymnasium import spaces
from pymunk.vec2d import Vec2d
from lerobot.common.envs.pusht.pymunk_override import DrawOptions
from pusht.pymunk_override import DrawOptions
def pymunk_to_shapely(body, shapes):

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@@ -1,7 +1,7 @@
import numpy as np
from gymnasium import spaces
from lerobot.common.envs.pusht.pusht_env import PushTEnv
from pusht.pusht_env import PushTEnv
class PushTImageEnv(PushTEnv):

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@@ -0,0 +1,37 @@
[tool.poetry]
name = "sim_pusht"
version = "0.1.0"
description = "PushT environment for LeRobot"
authors = [
"Rémi Cadène <re.cadene@gmail.com>",
]
maintainers = [
"Alexander Soare <alexander.soare159@gmail.com>",
"Quentin Gallouédec <quentin.gallouedec@ec-lyon.fr>",
"Simon Alibert <alibert.sim@gmail.com>",
]
readme = "README.md"
license = "Apache-2.0"
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Topic :: Software Development :: Build Tools",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.10",
]
packages = [{include = "pusht"}]
[tool.poetry.dependencies]
python = "^3.10"
gymnasium = "^0.29.1"
opencv-python = "^4.9.0.80"
pygame = "^2.5.2"
pymunk = "^6.6.0"
shapely = "^2.0.3"
scikit-image = "^0.22.0"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

1
envs/sim_xarm/README.md Normal file
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@@ -0,0 +1 @@
# xArm environment for LeRobot

448
envs/sim_xarm/poetry.lock generated Normal file
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@@ -0,0 +1,448 @@
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]
[package.extras]
docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-removed-in", "sphinxext-opengraph"]
fpx = ["olefile"]
mic = ["olefile"]
tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
typing = ["typing-extensions"]
xmp = ["defusedxml"]
[[package]]
name = "pyopengl"
version = "3.1.7"
description = "Standard OpenGL bindings for Python"
optional = false
python-versions = "*"
files = [
{file = "PyOpenGL-3.1.7-py3-none-any.whl", hash = "sha256:a6ab19cf290df6101aaf7470843a9c46207789855746399d0af92521a0a92b7a"},
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]
[[package]]
name = "typing-extensions"
version = "4.10.0"
description = "Backported and Experimental Type Hints for Python 3.8+"
optional = false
python-versions = ">=3.8"
files = [
{file = "typing_extensions-4.10.0-py3-none-any.whl", hash = "sha256:69b1a937c3a517342112fb4c6df7e72fc39a38e7891a5730ed4985b5214b5475"},
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]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "165d82035aade2abad497b32e156ec18d8ebc6c57a36376c3351b593c6889f22"

View File

@@ -0,0 +1,34 @@
[tool.poetry]
name = "sim_xarm"
version = "0.1.0"
description = "xArm environment for LeRobot"
authors = [
"Rémi Cadène <re.cadene@gmail.com>",
]
maintainers = [
"Alexander Soare <alexander.soare159@gmail.com>",
"Quentin Gallouédec <quentin.gallouedec@ec-lyon.fr>",
"Simon Alibert <alibert.sim@gmail.com>",
]
readme = "README.md"
license = "Apache-2.0"
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Topic :: Software Development :: Build Tools",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.10",
]
packages = [{include = "xarm"}]
[tool.poetry.dependencies]
python = "^3.10"
mujoco = "^2.3.7"
gymnasium = "^0.29.1"
gymnasium-robotics = "^1.2.4"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

View File

@@ -4,11 +4,11 @@ import gymnasium as gym
import numpy as np
from gymnasium.wrappers import TimeLimit
from lerobot.common.envs.simxarm.simxarm.tasks.base import Base as Base
from lerobot.common.envs.simxarm.simxarm.tasks.lift import Lift
from lerobot.common.envs.simxarm.simxarm.tasks.peg_in_box import PegInBox
from lerobot.common.envs.simxarm.simxarm.tasks.push import Push
from lerobot.common.envs.simxarm.simxarm.tasks.reach import Reach
from xarm.tasks.base import Base as Base
from xarm.tasks.lift import Lift
from xarm.tasks.peg_in_box import PegInBox
from xarm.tasks.push import Push
from xarm.tasks.reach import Reach
TASKS = OrderedDict(
(

View File

View File

@@ -4,7 +4,7 @@ import mujoco
import numpy as np
from gymnasium_robotics.envs import robot_env
from lerobot.common.envs.simxarm.simxarm.tasks import mocap
from xarm.tasks import mocap
class Base(robot_env.MujocoRobotEnv):

View File

@@ -1,6 +1,6 @@
import numpy as np
from lerobot.common.envs.simxarm.simxarm import Base
from xarm import Base
class Lift(Base):

View File

@@ -1,6 +1,6 @@
import numpy as np
from lerobot.common.envs.simxarm.simxarm import Base
from xarm import Base
class PegInBox(Base):

View File

@@ -1,6 +1,6 @@
import numpy as np
from lerobot.common.envs.simxarm.simxarm import Base
from xarm import Base
class Push(Base):

View File

@@ -1,6 +1,6 @@
import numpy as np
from lerobot.common.envs.simxarm.simxarm import Base
from xarm import Base
class Reach(Base):

View File

@@ -15,8 +15,8 @@ from torchrl.data.replay_buffers.writers import Writer
from lerobot.common.datasets.abstract import AbstractDataset
from lerobot.common.datasets.utils import download_and_extract_zip
from lerobot.common.envs.pusht.pusht_env import pymunk_to_shapely
from lerobot.common.policies.diffusion.replay_buffer import ReplayBuffer as DiffusionPolicyReplayBuffer
from pusht.pusht_env import pymunk_to_shapely
# as define in env
SUCCESS_THRESHOLD = 0.95 # 95% coverage,

View File

@@ -6,8 +6,6 @@ from typing import Optional
import einops
import numpy as np
import torch
from dm_control import mujoco
from dm_control.rl import control
from tensordict import TensorDict
from torchrl.data.tensor_specs import (
BoundedTensorSpec,
@@ -17,21 +15,9 @@ from torchrl.data.tensor_specs import (
)
from lerobot.common.envs.abstract import AbstractEnv
from lerobot.common.envs.aloha.constants import (
ACTIONS,
ASSETS_DIR,
DT,
JOINTS,
)
from lerobot.common.envs.aloha.tasks.sim import BOX_POSE, InsertionTask, TransferCubeTask
from lerobot.common.envs.aloha.tasks.sim_end_effector import (
InsertionEndEffectorTask,
TransferCubeEndEffectorTask,
)
from lerobot.common.envs.aloha.utils import sample_box_pose, sample_insertion_pose
from lerobot.common.utils import set_global_seed
_has_gym = importlib.util.find_spec("gymnasium") is not None
_has_aloha = importlib.util.find_spec("aloha") is not None
class AlohaEnv(AbstractEnv):
@@ -64,49 +50,23 @@ class AlohaEnv(AbstractEnv):
)
def _make_env(self):
if not _has_gym:
raise ImportError("Cannot import gymnasium.")
if not self.from_pixels:
raise NotImplementedError()
self._env = self._make_env_task(self.task)
if not _has_aloha:
raise ImportError(
"Cannot import aloha env. Please install it with `python -m pip install 'lerobot[aloha]'`"
)
from aloha.env import make_env_task
self._env = make_env_task(self.task)
def render(self, mode="rgb_array", width=640, height=480):
# TODO(rcadene): render and visualizer several cameras (e.g. angle, front_close)
image = self._env.physics.render(height=height, width=width, camera_id="top")
return image
def _make_env_task(self, task_name):
# time limit is controlled by StepCounter in env factory
time_limit = float("inf")
if "sim_transfer_cube" in task_name:
xml_path = ASSETS_DIR / "bimanual_viperx_transfer_cube.xml"
physics = mujoco.Physics.from_xml_path(str(xml_path))
task = TransferCubeTask(random=False)
elif "sim_insertion" in task_name:
xml_path = ASSETS_DIR / "bimanual_viperx_insertion.xml"
physics = mujoco.Physics.from_xml_path(str(xml_path))
task = InsertionTask(random=False)
elif "sim_end_effector_transfer_cube" in task_name:
raise NotImplementedError()
xml_path = ASSETS_DIR / "bimanual_viperx_end_effector_transfer_cube.xml"
physics = mujoco.Physics.from_xml_path(str(xml_path))
task = TransferCubeEndEffectorTask(random=False)
elif "sim_end_effector_insertion" in task_name:
raise NotImplementedError()
xml_path = ASSETS_DIR / "bimanual_viperx_end_effector_insertion.xml"
physics = mujoco.Physics.from_xml_path(str(xml_path))
task = InsertionEndEffectorTask(random=False)
else:
raise NotImplementedError(task_name)
env = control.Environment(
physics, task, time_limit, control_timestep=DT, n_sub_steps=None, flat_observation=False
)
return env
def _format_raw_obs(self, raw_obs):
if self.from_pixels:
image = torch.from_numpy(raw_obs["images"]["top"].copy())
@@ -124,6 +84,9 @@ class AlohaEnv(AbstractEnv):
return obs
def _reset(self, tensordict: Optional[TensorDict] = None):
from aloha.tasks.sim import BOX_POSE
from aloha.utils import sample_box_pose, sample_insertion_pose
if tensordict is not None and not AlohaEnv._reset_warning_issued:
logging.warning(f"{self.__class__.__name__}._reset ignores the provided tensordict.")
AlohaEnv._reset_warning_issued = True
@@ -200,9 +163,14 @@ class AlohaEnv(AbstractEnv):
return td
def _make_spec(self):
obs = {}
from omegaconf import OmegaConf
from aloha.constants import (
ACTIONS,
JOINTS,
)
obs = {}
if self.from_pixels:
if isinstance(self.image_size, int):
image_shape = (3, self.image_size, self.image_size)

View File

@@ -17,18 +17,18 @@ def make_env(cfg, transform=None):
}
if cfg.env.name == "simxarm":
from lerobot.common.envs.simxarm.env import SimxarmEnv
from lerobot.common.envs.xarm import SimxarmEnv
kwargs["task"] = cfg.env.task
clsfunc = SimxarmEnv
elif cfg.env.name == "pusht":
from lerobot.common.envs.pusht.env import PushtEnv
from lerobot.common.envs.pusht import PushtEnv
# assert kwargs["seed"] > 200, "Seed 0-200 are used for the demonstration dataset, so we don't want to seed the eval env with this range."
clsfunc = PushtEnv
elif cfg.env.name == "aloha":
from lerobot.common.envs.aloha.env import AlohaEnv
from lerobot.common.envs.aloha import AlohaEnv
kwargs["task"] = cfg.env.task
clsfunc = AlohaEnv

View File

@@ -18,7 +18,7 @@ from torchrl.envs.libs.gym import _gym_to_torchrl_spec_transform
from lerobot.common.envs.abstract import AbstractEnv
from lerobot.common.utils import set_global_seed
_has_gym = importlib.util.find_spec("gymnasium") is not None
_has_pusht = importlib.util.find_spec("pusht") is not None
class PushtEnv(AbstractEnv):
@@ -51,15 +51,17 @@ class PushtEnv(AbstractEnv):
)
def _make_env(self):
if not _has_gym:
raise ImportError("Cannot import gymnasium.")
# TODO(rcadene) (PushTEnv is similar to PushTImageEnv, but without the image rendering, it's faster to iterate on)
# from lerobot.common.envs.pusht.pusht_env import PushTEnv
if not self.from_pixels:
raise NotImplementedError("Use PushTEnv, instead of PushTImageEnv")
from lerobot.common.envs.pusht.pusht_image_env import PushTImageEnv
if not _has_pusht:
raise ImportError(
"Cannot import pusht env. Please install it with `python -m pip install 'lerobot[pusht]'`"
)
from pusht.pusht_image_env import PushTImageEnv
self._env = PushTImageEnv(render_size=self.image_size)

View File

@@ -21,6 +21,7 @@ from lerobot.common.utils import set_global_seed
MAX_NUM_ACTIONS = 4
_has_gym = importlib.util.find_spec("gymnasium") is not None
_has_xarm = importlib.util.find_spec("xarm") is not None
class SimxarmEnv(AbstractEnv):
@@ -52,12 +53,16 @@ class SimxarmEnv(AbstractEnv):
)
def _make_env(self):
if not _has_xarm:
raise ImportError(
"Cannot import xarm env. Please install it with `python -m pip install 'lerobot[xarm]'`"
)
if not _has_gym:
raise ImportError("Cannot import gymnasium.")
import gymnasium
from lerobot.common.envs.simxarm.simxarm import TASKS
from xarm import TASKS
if self.task not in TASKS:
raise ValueError(f"Unknown task {self.task}. Must be one of {list(TASKS.keys())}")

92
poetry.lock generated
View File

@@ -521,7 +521,7 @@ files = [
name = "dm-control"
version = "1.0.14"
description = "Continuous control environments and MuJoCo Python bindings."
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "dm_control-1.0.14-py3-none-any.whl", hash = "sha256:883c63244a7ebf598700a97564ed19fffd3479ca79efd090aed881609cdb9fc6"},
@@ -552,7 +552,7 @@ hdf5 = ["h5py"]
name = "dm-env"
version = "1.6"
description = "A Python interface for Reinforcement Learning environments."
optional = false
optional = true
python-versions = ">=3.7"
files = [
{file = "dm-env-1.6.tar.gz", hash = "sha256:a436eb1c654c39e0c986a516cee218bea7140b510fceff63f97eb4fcff3d93de"},
@@ -568,7 +568,7 @@ numpy = "*"
name = "dm-tree"
version = "0.1.8"
description = "Tree is a library for working with nested data structures."
optional = false
optional = true
python-versions = "*"
files = [
{file = "dm-tree-0.1.8.tar.gz", hash = "sha256:0fcaabbb14e7980377439e7140bd05552739ca5e515ecb3119f234acee4b9430"},
@@ -672,7 +672,7 @@ test = ["pytest (>=6)"]
name = "farama-notifications"
version = "0.0.4"
description = "Notifications for all Farama Foundation maintained libraries."
optional = false
optional = true
python-versions = "*"
files = [
{file = "Farama-Notifications-0.0.4.tar.gz", hash = "sha256:13fceff2d14314cf80703c8266462ebf3733c7d165336eee998fc58e545efd18"},
@@ -796,7 +796,7 @@ test = ["black", "coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre
name = "glfw"
version = "2.7.0"
description = "A ctypes-based wrapper for GLFW3."
optional = false
optional = true
python-versions = "*"
files = [
{file = "glfw-2.7.0-py2.py27.py3.py30.py31.py32.py33.py34.py35.py36.py37.py38-none-macosx_10_6_intel.whl", hash = "sha256:bd82849edcceda4e262bd1227afaa74b94f9f0731c1197863cd25c15bfc613fc"},
@@ -883,7 +883,7 @@ protobuf = ["grpcio-tools (>=1.62.1)"]
name = "gymnasium"
version = "0.29.1"
description = "A standard API for reinforcement learning and a diverse set of reference environments (formerly Gym)."
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "gymnasium-0.29.1-py3-none-any.whl", hash = "sha256:61c3384b5575985bb7f85e43213bcb40f36fcdff388cae6bc229304c71f2843e"},
@@ -913,7 +913,7 @@ toy-text = ["pygame (>=2.1.3)", "pygame (>=2.1.3)"]
name = "gymnasium-robotics"
version = "1.2.4"
description = "Robotics environments for the Gymnasium repo."
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "gymnasium-robotics-1.2.4.tar.gz", hash = "sha256:d304192b066f8b800599dfbe3d9d90bba9b761ee884472bdc4d05968a8bc61cb"},
@@ -1218,7 +1218,7 @@ i18n = ["Babel (>=2.7)"]
name = "labmaze"
version = "1.0.6"
description = "LabMaze: DeepMind Lab's text maze generator."
optional = false
optional = true
python-versions = "*"
files = [
{file = "labmaze-1.0.6-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b2ddef976dfd8d992b19cfa6c633f2eba7576d759c2082da534e3f727479a84a"},
@@ -1262,7 +1262,7 @@ setuptools = "!=50.0.0"
name = "lazy-loader"
version = "0.3"
description = "lazy_loader"
optional = false
optional = true
python-versions = ">=3.7"
files = [
{file = "lazy_loader-0.3-py3-none-any.whl", hash = "sha256:1e9e76ee8631e264c62ce10006718e80b2cfc74340d17d1031e0f84af7478554"},
@@ -1307,7 +1307,7 @@ files = [
name = "lxml"
version = "5.1.0"
description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API."
optional = false
optional = true
python-versions = ">=3.6"
files = [
{file = "lxml-5.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:704f5572ff473a5f897745abebc6df40f22d4133c1e0a1f124e4f2bd3330ff7e"},
@@ -1525,7 +1525,7 @@ tests = ["pytest (>=4.6)"]
name = "mujoco"
version = "2.3.7"
description = "MuJoCo Physics Simulator"
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "mujoco-2.3.7-cp310-cp310-macosx_10_16_x86_64.whl", hash = "sha256:e8714a5ff6a1561b364b7b4648d4c0c8d13e751874cf7401c309b9d23fa9598b"},
@@ -1980,7 +1980,7 @@ xml = ["lxml (>=4.9.2)"]
name = "pettingzoo"
version = "1.24.3"
description = "Gymnasium for multi-agent reinforcement learning."
optional = false
optional = true
python-versions = ">=3.8"
files = [
{file = "pettingzoo-1.24.3-py3-none-any.whl", hash = "sha256:23ed90517d2e8a7098bdaf5e31234b3a7f7b73ca578d70d1ca7b9d0cb0e37982"},
@@ -2348,7 +2348,7 @@ dev = ["aafigure", "matplotlib", "pygame", "pyglet (<2.0.0)", "sphinx", "wheel"]
name = "pyopengl"
version = "3.1.7"
description = "Standard OpenGL bindings for Python"
optional = false
optional = true
python-versions = "*"
files = [
{file = "PyOpenGL-3.1.7-py3-none-any.whl", hash = "sha256:a6ab19cf290df6101aaf7470843a9c46207789855746399d0af92521a0a92b7a"},
@@ -2359,7 +2359,7 @@ files = [
name = "pyparsing"
version = "3.1.2"
description = "pyparsing module - Classes and methods to define and execute parsing grammars"
optional = false
optional = true
python-versions = ">=3.6.8"
files = [
{file = "pyparsing-3.1.2-py3-none-any.whl", hash = "sha256:f9db75911801ed778fe61bb643079ff86601aca99fcae6345aa67292038fb742"},
@@ -2790,7 +2790,7 @@ torch = ["safetensors[numpy]", "torch (>=1.10)"]
name = "scikit-image"
version = "0.22.0"
description = "Image processing in Python"
optional = false
optional = true
python-versions = ">=3.9"
files = [
{file = "scikit_image-0.22.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:74ec5c1d4693506842cc7c9487c89d8fc32aed064e9363def7af08b8f8cbb31d"},
@@ -2838,7 +2838,7 @@ test = ["asv", "matplotlib (>=3.5)", "numpydoc (>=1.5)", "pooch (>=1.6.0)", "pyt
name = "scipy"
version = "1.12.0"
description = "Fundamental algorithms for scientific computing in Python"
optional = false
optional = true
python-versions = ">=3.9"
files = [
{file = "scipy-1.12.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:78e4402e140879387187f7f25d91cc592b3501a2e51dfb320f48dfb73565f10b"},
@@ -3043,7 +3043,7 @@ testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jar
name = "shapely"
version = "2.0.3"
description = "Manipulation and analysis of geometric objects"
optional = false
optional = true
python-versions = ">=3.7"
files = [
{file = "shapely-2.0.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:af7e9abe180b189431b0f490638281b43b84a33a960620e6b2e8d3e3458b61a1"},
@@ -3096,6 +3096,55 @@ numpy = ">=1.14,<2"
docs = ["matplotlib", "numpydoc (==1.1.*)", "sphinx", "sphinx-book-theme", "sphinx-remove-toctrees"]
test = ["pytest", "pytest-cov"]
[[package]]
name = "sim-aloha"
version = "0.1.2"
description = "ALOHA environment for LeRobot"
optional = true
python-versions = "<4.0,>=3.10"
files = [
{file = "sim_aloha-0.1.2-py3-none-any.whl", hash = "sha256:3b13c1ee474481f5d686b57bf1a9ed350e01ca4da7d65f7501446eb74b02653a"},
{file = "sim_aloha-0.1.2.tar.gz", hash = "sha256:44d36bbdb13e98e0c74f4d2a682f38683f4f63951618da28175f89cbb1c6f324"},
]
[package.dependencies]
dm-control = "1.0.14"
[[package]]
name = "sim-pusht"
version = "0.1.0"
description = "PushT environment for LeRobot"
optional = true
python-versions = "<4.0,>=3.10"
files = [
{file = "sim_pusht-0.1.0-py3-none-any.whl", hash = "sha256:1348dcab5ea8460eff2dc97b7d62dd40f2a382df92bfdc69ff5c0224900690b0"},
{file = "sim_pusht-0.1.0.tar.gz", hash = "sha256:d8f6a2207fd781348156206728329aa6338e9785cfc07679c5c48889b34d9b14"},
]
[package.dependencies]
gymnasium = ">=0.29.1,<0.30.0"
opencv-python = ">=4.9.0.80,<5.0.0.0"
pygame = ">=2.5.2,<3.0.0"
pymunk = ">=6.6.0,<7.0.0"
scikit-image = ">=0.22.0,<0.23.0"
shapely = ">=2.0.3,<3.0.0"
[[package]]
name = "sim-xarm"
version = "0.1.0"
description = "xArm environment for LeRobot"
optional = true
python-versions = "<4.0,>=3.10"
files = [
{file = "sim_xarm-0.1.0-py3-none-any.whl", hash = "sha256:2771ca0e8d775dc7d9ccb3360e7fcf42507c5d4791525692e409f53ff5c83eaa"},
{file = "sim_xarm-0.1.0.tar.gz", hash = "sha256:90342394369ab37636a8c41a995ba20f1dac79c50563b1b1e4b38eeffbc5588d"},
]
[package.dependencies]
gymnasium = ">=0.29.1,<0.30.0"
gymnasium-robotics = ">=1.2.4,<2.0.0"
mujoco = ">=2.3.7,<3.0.0"
[[package]]
name = "six"
version = "1.16.0"
@@ -3235,7 +3284,7 @@ tests = ["pytest", "pytest-cov"]
name = "tifffile"
version = "2024.2.12"
description = "Read and write TIFF files"
optional = false
optional = true
python-versions = ">=3.9"
files = [
{file = "tifffile-2024.2.12-py3-none-any.whl", hash = "sha256:870998f82fbc94ff7c3528884c1b0ae54863504ff51dbebea431ac3fa8fb7c21"},
@@ -3586,7 +3635,12 @@ files = [
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
[extras]
aloha = ["sim-aloha"]
pusht = ["sim-pusht"]
xarm = ["sim-xarm"]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "174c7d42f8039eedd2c447a4e6cae5169782cbd94346b5606572a0010194ca05"
content-hash = "1a27121cca3d38e1bafba74157e3bb68cc57a420bb7a6d6e8edbec0fb90368d6"

View File

@@ -1,19 +1,24 @@
[tool.poetry]
name = "lerobot"
version = "0.1.0"
description = "Le robot is learning"
description = "🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch"
authors = [
"Rémi Cadène <re.cadene@gmail.com>",
]
maintainers = [
"Alexander Soare <alexander.soare159@gmail.com>",
"Quentin Gallouédec <quentin.gallouedec@ec-lyon.fr>",
"Simon Alibert <alibert.sim@gmail.com>",
]
repository = "https://github.com/Cadene/lerobot"
readme = "README.md"
license = "MIT"
license = "Apache-2.0"
keywords = ["robotics, deep, reinforcement, learning, pytorch"]
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Topic :: Software Development :: Build Tools",
"License :: OSI Approved :: MIT License",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.10",
]
packages = [{include = "lerobot"}]
@@ -23,7 +28,6 @@ packages = [{include = "lerobot"}]
python = "^3.10"
termcolor = "^2.4.0"
omegaconf = "^2.3.0"
dm-env = "^1.6"
pandas = "^2.2.1"
wandb = "^0.16.3"
moviepy = "^1.0.3"
@@ -34,29 +38,35 @@ einops = "^0.7.0"
pygame = "^2.5.2"
pymunk = "^6.6.0"
zarr = "^2.17.0"
shapely = "^2.0.3"
scikit-image = "^0.22.0"
numba = "^0.59.0"
mpmath = "^1.3.0"
torch = "^2.2.1"
tensordict = {git = "https://github.com/pytorch/tensordict"}
torchrl = {git = "https://github.com/pytorch/rl", rev = "13bef426dcfa5887c6e5034a6e9697993fa92c37"}
mujoco = "^2.3.7"
opencv-python = "^4.9.0.80"
diffusers = "^0.26.3"
torchvision = "^0.17.1"
h5py = "^3.10.0"
dm-control = "1.0.14"
huggingface-hub = {extras = ["hf-transfer"], version = "^0.21.4"}
robomimic = "0.2.0"
gymnasium-robotics = "^1.2.4"
gymnasium = "^0.29.1"
cmake = "^3.29.0.1"
sim-pusht = { version = "^0.1.0", optional = true}
sim-xarm = { version = "^0.1.0", optional = true}
sim-aloha = { version = "^0.1.2", optional = true}
[tool.poetry.extras]
pusht = ["sim-pusht"]
xarm = ["sim-xarm"]
aloha = ["sim-aloha"]
[tool.poetry.group.dev.dependencies]
pre-commit = "^3.6.2"
debugpy = "^1.8.1"
[tool.poetry.group.test.dependencies]
pytest = "^8.1.0"
pytest-cov = "^5.0.0"
@@ -93,6 +103,9 @@ exclude = [
select = ["E4", "E7", "E9", "F", "I", "N", "B", "C4", "SIM"]
ignore-init-module-imports = true
[tool.ruff.lint.isort]
known-first-party = ["pusht", "xarm", "aloha"]
[tool.poetry-dynamic-versioning]
enable = true

View File

@@ -15,9 +15,9 @@ Note:
import pytest
import lerobot
from lerobot.common.envs.aloha.env import AlohaEnv
from lerobot.common.envs.pusht.env import PushtEnv
from lerobot.common.envs.simxarm.env import SimxarmEnv
from lerobot.common.envs.aloha import AlohaEnv
from lerobot.common.envs.pusht import PushtEnv
from lerobot.common.envs.xarm import SimxarmEnv
from lerobot.common.datasets.simxarm import SimxarmDataset
from lerobot.common.datasets.aloha import AlohaDataset

View File

@@ -5,9 +5,9 @@ from torchrl.envs.utils import check_env_specs, step_mdp
from lerobot.common.datasets.factory import make_offline_buffer
from lerobot.common.envs.factory import make_env
from lerobot.common.envs.pusht.env import PushtEnv
from lerobot.common.envs.simxarm.env import SimxarmEnv
from lerobot.common.envs.aloha.env import AlohaEnv
from lerobot.common.envs.pusht import PushtEnv
from lerobot.common.envs.xarm import SimxarmEnv
from lerobot.common.envs.aloha import AlohaEnv
from .utils import DEVICE, init_config