diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 8137cc44e..59ca7f1ae 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -19,13 +19,9 @@ jobs: uses: actions/setup-python@v5 with: python-version: "3.11" + - name: Set up uv + uses: astral-sh/setup-uv@v3 - uses: pre-commit/action@v3.0.1 - name: Install dependencies run: | - python -m pip install --upgrade pip - pip install poetry - poetry install --with dev - - name: Test with pytest - run: | - source $(poetry env info --path)/bin/activate - pytest -v + uv sync --dev \ No newline at end of file diff --git a/README.md b/README.md index 954f66146..cd15c8283 100644 --- a/README.md +++ b/README.md @@ -11,7 +11,7 @@ A collection of algorithms and experiment tools for safe sim to real transfer an ## Requirements - Python == 3.11.6 -- `venv` or `Poetry` +- [`uv`](https://docs.astral.sh/uv/) (recommended) or the built-in `venv` ## Installation @@ -25,15 +25,70 @@ source venv/bin/activate pip install -e . ```` -### Using Poetry +### Using uv + +Install uv if it is not already available: + +```bash +curl -LsSf https://astral.sh/uv/install.sh | sh +``` + +Create a project environment and install dependencies: ```bash git clone https://github.com/yardenas/safe-learning cd safe-learning -poetry install -poetry shell +uv sync +uv run python --version # sanity check, optional ``` +### Installing `madrona_mjx` (optional, required for Madrona backend) + +Some benchmarks (e.g., the MJX-based pick-and-place tasks) require the custom +[`madrona_mjx`](https://github.com/shacklettbp/madrona_mjx) fork. Build and +install it inside the UV environment you created above: + +1. From the parent directory of `safe-sim2real`, clone the repository and check + out the tested commit: + + ```bash + git clone https://github.com/shacklettbp/madrona_mjx.git + cd madrona_mjx + git checkout c34f3cf6d95148dba50ffeb981aea033b8a4d225 + git submodule update --init --recursive + ``` + +2. Configure and build (disable Vulkan if you do not have it available): + + ```bash + mkdir -p build + cd build + cmake -DLOAD_VULKAN=OFF .. + cmake --build . -j + cd .. + ``` + +3. While having your environment activated, install the Python bindings into your UV environment: + + ```bash + uv pip install -e . + ``` + +Refer to the upstream repository for platform-specific prerequisites (CUDA, +Vulkan, compiler versions). Re-run `uv pip install -e .` whenever you rebuild the +library. + +**Troubleshooting tips** + +- If you see CUDA OOMs immediately after the build, try `export + MADRONA_DISABLE_CUDA_HEAP_SIZE=1` before launching training. +- Populate the kernel caches to avoid recompilation on every run: + + ```bash + export MADRONA_MWGPU_KERNEL_CACHE=/path/to/cache/mwgpu + export MADRONA_BVH_KERNEL_CACHE=/path/to/cache/bvh + ``` + ## Usage Our code uses [Hydra](https://hydra.cc/) to configure experiments. Each experiment is defined as a `yaml` file in `ss2r/configs/experiments`. For example, to train a Unitree Go1 policy with a constraint on joint limit: @@ -65,4 +120,3 @@ If you find our repository useful in your work, please consider citing: * **Project Webpage**: * **Paper**: * **Contact**: - diff --git a/euler_guide.md b/euler_guide.md index 83fceaec0..37e6665a1 100644 --- a/euler_guide.md +++ b/euler_guide.md @@ -5,9 +5,9 @@ ## Installing Madrona-MJX on Euler 1. Make sure that the steps above have been completed on the current terminal. -2. Go to the parent directory of the safe-sim2real repository: `cd ..` -3. Activate the poetry environment: `eval $(poetry env activate)` -4. Move out of `safe-sim2real` to your home folder. +2. Go to the parent directory of the safe-learning repository: `cd ..` +3. Activate the environment: `source .venv/bin/activate` +4. Move out of `safe-learning` to your home folder. 5. `git clone https://github.com/shacklettbp/madrona_mjx.git && git checkout c34f3cf6d95148dba50ffeb981aea033b8a4d225` 6. `cd madrona_mjx` 7. `git submodule update --init --recursive` @@ -15,6 +15,6 @@ 9. Point to cuda CMAKE witout loading cuda `export CMAKE_PREFIX_PATH="/cluster/software/stacks/2024-06/spack/opt/spack/linux-ubuntu22.04-x86_64_v3/gcc-12.2.0/cuda-12.1.1-5znnrjb5x5xr26nojxp3yhh6v77il7ie/:${CMAKE_PREFIX_PATH}"` 10. `mkdir build && cd build && cmake -DLOAD_VULKAN=OFF .. && cd ..` 11. Compile on a compute node `srun --ntasks=1 --cpus-per-task=20 --gpus=rtx_4090:1 --time=0:30:00 --mem-per-cpu=10240 make -j` -12. Change back to the root of the safe-sim2real repository: `cd .. && cd safe-sim2real` +12. Change back to the root of the safe-learning repository: `cd .. && cd safe-learning` 13. `poetry install --with madrona-mjx` 14. 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-[metadata] -lock-version = "2.1" -python-versions = "^3.11.6,<3.12" -content-hash = "dd20b485d5e73de080333f2f3838fbf186ce275c256424f6421ef90379d9e7f6" diff --git a/pyproject.toml b/pyproject.toml index c7b1b4cde..486884e02 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,73 +1,61 @@ -[tool.poetry] +[project] name = "ss2r" version = "0.1.0" description = "" -authors = ["Yarden "] +authors = [{ name = "Yarden", email = "yarden.as@inf.ethz.ch" }] +requires-python = ">=3.11.6,<4" readme = "README.md" +dependencies = [ + "mujoco==3.3.0", + "mujoco-mjx==3.2.7", + "jax[cuda12]==0.4.34", + "hydra-core>=1.3.2,<2", + "hydra-submitit-launcher>=1.2.0,<2", + "tabulate>=0.9.0,<0.10", + "nvidia-cublas-cu12==12.9.0.13", + "moviepy==1.0.3", + "imageio>=2.37.0,<3", + "brax", + "playground", + "nvidia-cuda-nvrtc-cu12>=12.9.86,<13", + "matplotlib>=3.10.3,<4", +] -[tool.poetry.dependencies] -python = "^3.11.6,<3.12" -mujoco = "3.3.0" -mujoco-mjx = "3.2.7" -jax = {version = "0.4.34", extras = ["cuda12"]} -hydra-core = "^1.3.2" -hydra-submitit-launcher = "^1.2.0" -tabulate = "^0.9.0" -nvidia-cublas-cu12 = "12.9.0.13" -moviepy = "1.0.3" -imageio = "^2.37.0" -# TODO (yarden): update these once they are merged to main -brax = {git = "https://github.com/Andrew-Luo1/brax.git", rev = "bc_checkpointing"} -playground = {git = "https://github.com/Andrew-Luo1/mujoco_playground_new.git"} -nvidia-cuda-nvrtc-cu12 = "^12.9.86" -matplotlib = "^3.10.3" - -[[tool.poetry.source]] -name = "PyPI" -priority = "primary" - -[tool.poetry.group.dev] -optional = true - -[tool.poetry.group.dev.dependencies] -mypy = "^1.7.0" -pre-commit = "^3.5.0" -pytest = "^7.4.3" -pytest-mock = "^3.12.0" -types-tabulate = "^0.9.0.20240106" -seaborn = "^0.13.2" -ipykernel = "^6.29.4" -tueplots = "^0.0.17" -ruff = "^0.9.6" - -[tool.poetry.group.wandb.dependencies] -wandb = "^0.16.4" - -[tool.poetry.group.hydra-submitit] -optional = true - -[tool.poetry.group.hydra-submitit.dependencies] -hydra-submitit-launcher = "^1.2.0" - -[tool.poetry.group.onnx] -optional = true +[dependency-groups] +dev = [ + "mypy>=1.7.0,<2", + "pre-commit>=3.5.0,<4", + "types-tabulate>=0.9.0.20240106,<0.10", + "seaborn>=0.13.2,<0.14", + "ipykernel>=6.29.4,<7", + "tueplots>=0.0.17,<0.0.18", + "ruff>=0.9.6,<0.10", +] +wandb = ["wandb>=0.16.4,<0.17"] +hydra-submitit = ["hydra-submitit-launcher>=1.2.0,<2"] +onnx = [ + "tf2onnx>=1.16.1,<2", + "onnxruntime>=1.20.1,<2", + "keras>=2.13.1", + "pyzmq>=27.0.0,<28", + "tensorflow-cpu==2.17.1", +] -[tool.poetry.group.onnx.dependencies] -tf2onnx = "^1.16.1" -onnxruntime = "^1.20.1" -keras = ">=2.13.1" -pyzmq = "^27.0.0" -tensorflow-cpu = "2.17.1" +[tool.uv] +default-groups = ["dev", "wandb", "onnx"] -[tool.poetry.group.madrona-mjx] -optional = true +[[tool.uv.index]] +name = "PyPI" +url = "https://pypi.org/simple/" +default = true -[tool.poetry.group.madrona-mjx.dependencies] -madrona-mjx = { path = "../madrona_mjx", develop = true } +[tool.uv.sources] +brax = { git = "https://github.com/Andrew-Luo1/brax.git", rev = "bc_checkpointing" } +playground = { git = "https://github.com/Andrew-Luo1/mujoco_playground_new.git" } [build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" +requires = ["hatchling"] +build-backend = "hatchling.build" [tool.ruff] line-length = 88 diff --git a/ss2r/benchmark_suites/mujoco_playground/pick_cartesian/qr.py b/ss2r/benchmark_suites/mujoco_playground/pick_cartesian/qr.py index c7cae0668..4475e7a87 100644 --- a/ss2r/benchmark_suites/mujoco_playground/pick_cartesian/qr.py +++ b/ss2r/benchmark_suites/mujoco_playground/pick_cartesian/qr.py @@ -1,28 +1,18 @@ -from etils import epath +import os -# import cv2 -# import cv2.aruco as aruco -# # Parameters -# marker_ids = [571, 581, 591, 601, 611, 621] -# marker_size_pixels = 600 # Size of each marker in pixels -# output_folder = "aruco_markers" -# aruco_dict = aruco.getPredefinedDictionary(aruco.DICT_6X6_1000) -# # Create the output folder if it doesn't exist -# os.makedirs(output_folder, exist_ok=True) -# # Generate and save markers -# for marker_id in marker_ids: -# img = aruco.generateImageMarker(aruco_dict, marker_id, marker_size_pixels) -# filepath = os.path.join(output_folder, f"aruco_{marker_id}.png") -# cv2.imwrite(filepath, img) -# print(f"Saved: {filepath}") -from PIL import Image, ImageOps +import cv2 +import cv2.aruco as aruco -# Load the image +# Parameters marker_ids = [571, 581, 591, 601, 611, 621] +marker_size_pixels = 600 # Size of each marker in pixels +output_folder = "aruco_markers" +aruco_dict = aruco.getPredefinedDictionary(aruco.DICT_6X6_1000) +# Create the output folder if it doesn't exist +os.makedirs(output_folder, exist_ok=True) +# Generate and save markers for marker_id in marker_ids: - path = epath.Path(__file__).parent - image_path = path / "assets" / epath.Path(f"aruco_{marker_id}.png") - img = Image.open(image_path).convert("RGB") - border_size = 75 - img_with_border = ImageOps.expand(img, border=border_size, fill="white") - img_with_border.save(f"aruco_{marker_id}.png") + img = aruco.generateImageMarker(aruco_dict, marker_id, marker_size_pixels) + filepath = os.path.join(output_folder, f"aruco_{marker_id}.png") + cv2.imwrite(filepath, img) + print(f"Saved: {filepath}") diff --git a/tests/__init__.py b/tests/__init__.py deleted file mode 100644 index 0638cd970..000000000 --- a/tests/__init__.py +++ /dev/null @@ -1,16 +0,0 @@ -from hydra import compose, initialize - - -def make_test_config(additional_overrides=None): - if additional_overrides is None: - additional_overrides = [] - with initialize(version_base=None, config_path="../ss2r/configs"): - cfg = compose( - config_name="train_brax", - overrides=[ - "writers=[stderr]", - "+experiment=debug", - ] - + additional_overrides, - ) - return cfg diff --git a/tests/test_rccar.py b/tests/test_rccar.py deleted file mode 100644 index d5cf5e798..000000000 --- a/tests/test_rccar.py +++ /dev/null @@ -1,71 +0,0 @@ -import jax -import jax.numpy as jnp -import numpy as np -import pytest -from brax import envs - -from ss2r import benchmark_suites -from tests import make_test_config - - -def shared_policy(state): - pos = state[0] - vel = state[1] - action = -1.0 * pos - 0.1 * vel - return np.array([action]) - - -def set_brax_initial_state(env, init_state): - q = jax.numpy.asarray([init_state[0], init_state[2]]) - qd = jax.numpy.asarray([init_state[1], init_state[3]]) - pipeline_state = env.pipeline_init(q, qd) - obs = env._get_obs(pipeline_state) - reward, done, cost, steps, truncation = jax.numpy.zeros(5) - info = { - "cost": cost, - "steps": steps, - "truncation": truncation, - "first_pipeline_state": pipeline_state, - "first_obs": obs, - } - return envs.State(pipeline_state, obs, reward, done, {}, info) - - -_ENVS = 256 - - -@pytest.mark.parametrize( - "use_domain_randomization,similar_rate", - [(True, 0.1), (False, 1.0)], - ids=["domain_randomization", "no_domain_randomization"], -) -def test_parameterization(use_domain_randomization, similar_rate): - cfg = make_test_config( - [ - f"training.num_envs={_ENVS}", - "environment=rccar", - "training.train_domain_randomization=" + str(use_domain_randomization), - ] - ) - env, *_ = benchmark_suites.make(cfg) - keys = jnp.stack([jax.random.PRNGKey(0) for _ in range(_ENVS)]) - brax_state = env.reset(rng=keys) - brax_step = jax.jit(env.step) - brax_state = brax_step(brax_state, jnp.ones((_ENVS, env.action_size))) - - def get_obs(state): - if isinstance(state.obs, jax.Array): - return state.obs - return state.obs["state"] - - count = sum( - jnp.allclose(get_obs(brax_state)[j, :], get_obs(brax_state)[i, :]) - for i in range(_ENVS) - for j in range(_ENVS) - if i != j - ) - total = _ENVS * (_ENVS - 1) - assert ( - (count / total <= similar_rate and use_domain_randomization) - or (count / total >= similar_rate and not use_domain_randomization) - ), f"Domain randomization {use_domain_randomization is not None}, expected {similar_rate}"