State-of-the-art Machine Learning for real-world robotics
+ + +--- -**State-of-the-art machine learning for real-world robotics** 🤗 LeRobot aims to provide models, datasets, and tools for real-world robotics in PyTorch. The goal is to lower the barrier for entry to robotics so that everyone can contribute and benefit from sharing datasets and pretrained models. @@ -44,26 +60,21 @@ ## Installation -Create a virtual environment with Python 3.10, e.g. using `conda`: +Download our source code: +```bash +git clone https://github.com/huggingface/lerobot.git +cd lerobot +``` + +Create a virtual environment with Python 3.10 and activate it, e.g. with [`miniconda`](https://docs.anaconda.com/free/miniconda/index.html): ```bash conda create -y -n lerobot python=3.10 conda activate lerobot ``` -[Install `poetry`](https://python-poetry.org/docs/#installation) (if you don't have it already) +Then, install 🤗 LeRobot: ```bash -curl -sSL https://install.python-poetry.org | python - -``` - -Install dependencies -```bash -poetry install -``` - -If you encounter a disk space error, try to change your tmp dir to a location where you have enough disk space, e.g. -```bash -mkdir ~/tmp -export TMPDIR='~/tmp' +python -m pip install . ``` To use [Weights and Biases](https://docs.wandb.ai/quickstart) for experiments tracking, log in with @@ -174,11 +185,11 @@ hydra.run.dir=outputs/train/aloha_act Feel free to open issues and PRs, and to coordinate your efforts with the community on our [Discord Channel](https://discord.gg/VjFz58wn3R). For specific inquiries, reach out to [Remi Cadene](remi.cadene@huggingface.co). -**TODO** +### TODO If you are not sure how to contribute or want to know the next features we working on, look on this project page: [LeRobot TODO](https://github.com/orgs/huggingface/projects/46) -**Follow our style** +### Follow our style ```bash # install if needed @@ -187,25 +198,33 @@ pre-commit install pre-commit ``` -**Add dependencies** +### Add dependencies -Instead of `pip install some-package`, we use `poetry` to track the versions of our dependencies: +Instead of using `pip` directly, we use `poetry` for development purposes to easily track our dependencies. +If you don't have it already, follow the [instructions](https://python-poetry.org/docs/#installation) to install it. + +Install the project with: +```bash +poetry install +``` + +Then, the equivalent of `pip install some-package`, would just be: ```bash poetry add some-package ``` -**NOTE:** Currently, to ensure the CI works properly, any new package must also be added in the CPU-only environment dedicated CI. To do this, you should create a separate environment and add the new package there as well. For example: +**NOTE:** Currently, to ensure the CI works properly, any new package must also be added in the CPU-only environment dedicated to the CI. To do this, you should create a separate environment and add the new package there as well. For example: ```bash -# add the new package to your main poetry env +# Add the new package to your main poetry env poetry add some-package -# add the same package to the CPU-only env dedicated to CI +# Add the same package to the CPU-only env dedicated to CI conda create -y -n lerobot-ci python=3.10 conda activate lerobot-ci cd .github/poetry/cpu poetry add some-package ``` -**Run tests locally** +### Run tests locally Install [git lfs](https://git-lfs.com/) to retrieve test artifacts (if you don't have it already). @@ -236,7 +255,7 @@ Run tests DATA_DIR="tests/data" pytest -sx tests ``` -**Add a new dataset** +### Add a new dataset To add a dataset to the hub, first login and use a token generated from [huggingface settings](https://huggingface.co/settings/tokens) with write access: ```bash @@ -297,7 +316,7 @@ Finally, you might want to mock the dataset if you need to update the unit tests python tests/scripts/mock_dataset.py --in-data-dir data/$DATASET --out-data-dir tests/data/$DATASET ``` -**Add a pretrained policy** +### Add a pretrained policy Once you have trained a policy you may upload it to the HuggingFace hub. @@ -333,7 +352,7 @@ huggingface-cli upload $HUB_ID to_upload See `eval.py` for an example of how a user may use your policy. -**Improve your code with profiling** +### Improve your code with profiling An example of a code snippet to profile the evaluation of a policy: ```python diff --git a/lerobot/common/envs/aloha/env.py b/lerobot/common/envs/aloha/env.py index 357a96ecb..8f9076505 100644 --- a/lerobot/common/envs/aloha/env.py +++ b/lerobot/common/envs/aloha/env.py @@ -206,7 +206,7 @@ class AlohaEnv(AbstractEnv): if self.from_pixels: if isinstance(self.image_size, int): image_shape = (3, self.image_size, self.image_size) - elif OmegaConf.is_list(self.image_size): + elif OmegaConf.is_list(self.image_size) or isinstance(self.image_size, list): assert len(self.image_size) == 3 # c h w assert self.image_size[0] == 3 # c is RGB 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= "sha256:4f0764a1219df53214206bf1feea4633c3b558a2925c8b59f144f682861ce652"}, +] + +[package.dependencies] +coverage = {version = ">=5.2.1", extras = ["toml"]} +pytest = ">=4.6" + +[package.extras] +testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"] + [[package]] name = "python-dateutil" version = "2.9.0.post0" @@ -3475,4 +3589,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "99addbfc02bcd35a308f4ecc5b4285c9c5054118f4aadea27650d8bf355d9616" +content-hash = "174c7d42f8039eedd2c447a4e6cae5169782cbd94346b5606572a0010194ca05" diff --git a/pyproject.toml b/pyproject.toml index 29cec3b7d..972c1b611 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -51,12 +51,14 @@ 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" [tool.poetry.group.dev.dependencies] pre-commit = "^3.6.2" debugpy = "^1.8.1" pytest = "^8.1.0" +pytest-cov = "^5.0.0" [tool.ruff] diff --git a/tests/test_envs.py b/tests/test_envs.py index 2bd5e65c2..eb3746db4 100644 --- a/tests/test_envs.py +++ b/tests/test_envs.py @@ -4,6 +4,7 @@ import torch from torchrl.envs.utils import check_env_specs, step_mdp from lerobot.common.datasets.factory import make_offline_buffer +from lerobot.common.envs.aloha.env import AlohaEnv from lerobot.common.envs.factory import make_env from lerobot.common.envs.pusht.env import PushtEnv from lerobot.common.envs.simxarm.env import SimxarmEnv @@ -39,6 +40,26 @@ def print_spec_rollout(env): print("data from rollout:", simple_rollout(100)) +@pytest.mark.parametrize( + "task,from_pixels,pixels_only", + [ + ("sim_insertion", True, False), + ("sim_insertion", True, True), + ("sim_transfer_cube", True, False), + ("sim_transfer_cube", True, True), + ], +) +def test_aloha(task, from_pixels, pixels_only): + env = AlohaEnv( + task, + from_pixels=from_pixels, + pixels_only=pixels_only, + image_size=[3, 480, 640] if from_pixels else None, + ) + # print_spec_rollout(env) + check_env_specs(env) + + @pytest.mark.parametrize( "task,from_pixels,pixels_only", [