Automating-Relational-Machine-Learning/pixi.toml at main · amazon-science/Automating-Relational-Machine-Learning · GitHub

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# pixi.toml — All-pip RAPIDS (cu12, 25.10.*) + pip Torch 2.6.0 + PyG wheels

[workspace]
name = "openRFM"
channels = ["conda-forge"]          # minimal conda usage for system libs
platforms = ["linux-64"]

[system-requirements]
cuda = "12"                         # you have a CUDA 12-capable driver/runtime

# Pip/uv resolver setup:
# - Use PyTorch's CUDA 12.4 wheel index for torch==2.6.0+cu124
# - Use NVIDIA's PyPI for RAPIDS cu12 wheels
# - Use PyG wheel page that matches torch 2.6.0+cu124
[pypi-options]
extra-index-urls = [
  "https://download.pytorch.org/whl/cu124",
  "https://pypi.nvidia.com"
]
find-links = [
  { url = "https://data.pyg.org/whl/torch-2.6.0+cu124.html" }
]
# All indexes are trusted (PyPI, PyTorch, NVIDIA) — allow best version from any
index-strategy = "unsafe-best-match"

[dependencies]
# --- Core toolchain / native libs via conda ---
python = "3.12.*"
rust = "*"
uv = "*"
maturin = "*"
patchelf = "*"
graphviz = "*"
pygraphviz = "*"

# (Everything below comes from pip to keep ABI/story consistent)

[pypi-dependencies]
# --- PyTorch (pip) CUDA 12.4 build ---
torch = "==2.6.0+cu124"

# --- RAPIDS cu12 (pip) — 25.10 line ---
cudf-cu12 = "==25.10.*"
dask-cudf-cu12 = "==25.10.*"
cuml-cu12 = "==25.10.*"
cugraph-cu12 = "==25.10.*"
nx-cugraph-cu12 = "==25.10.*"
cuxfilter-cu12 = "==25.10.*"
cucim-cu12 = "==25.10.*"
pylibraft-cu12 = "==25.10.*"
raft-dask-cu12 = "==25.10.*"
cuvs-cu12 = "==25.10.*"
# (rmm is pulled transitively; add `rmm-cu12 ==25.10.*` only if pip complains)

# --- PyTorch Geometric (pip) + CUDA extensions matching Torch 2.6.0+cu124 ---
torch-geometric = "*"
pyg_lib = "*"
torch_scatter = "*"
torch_sparse = "*"
torch_cluster = "*"
torch_spline_conv = "*"

# --- Your existing PyPI deps ---
numpy = "*"
pandas = "*"
tqdm = "*"
pyarrow = "*"
pillow = "*"
pooch = "*"
duckdb = "*"
scikit-learn = "<1.6.0"
typing-extensions = "*"
pytorch-lightning = "*"
hydra-core = "*"
maturin_import_hook = "*"
ml_dtypes = "*"
orjson = "*"
gdown = "*"
polars = "*"
einops = "*"
wandb = "*"
loguru = "*"
sentence-transformers = "*"
strictfire = "*"
pympler = "*"
ipdb = "*"
matplotlib = "*"
seaborn = "*"
datasets = "*"


# --- DFS / feature engineering ---
featuretools = "*"
woodwork = "*"
setuptools = "<75"  # woodwork needs pkg_resources, removed in setuptools 75+
sqlglot = "*"
sql-formatter = "*"

# --- ML models & HPO ---
tabpfn = "*"
lightgbm = "*"
xgboost = "*"
catboost = "*"
optuna = "*"
hyperopt = "*"
anthropic = "*"
boto3 = "*"

# --- Core scientific / data ---
scipy = "*"
pydantic = "*"
sqlalchemy = "*"
torchmetrics = "*"
transformers = "*"
psutil = "*"
python-dotenv = "*"
cupy-cuda12x = "*"

# --- Local editable packages ---
pytorch-frame = { path = "./pytorch-frame", editable = true }
relbench = { path = "./relbench", editable = true }
rustler = { path = "./rustler", editable = true }
contextgnn = { path = "./ContextGNN", editable = true }

[environments]
iclr = { solve-group = "default" }

[tasks]
# Rebuild rustler after making changes to Rust code
rt-build = """
maturin develop --manifest-path rustler/Cargo.toml --release --uv && \
cp rustler/target/release/librustler.so .pixi/envs/default/lib/python3.12/site-packages/rustler/rustler.abi3.so
"""
# Quick rebuild without reinstall (just compiles)
rt-compile = "cargo build --release --manifest-path rustler/Cargo.toml"