pyproject.toml

[project]
authors = [{name = "Ethycs", email = "Ethycs@users.noreply.github.com"}]
name = "structure_net"
requires-python = ">= 3.11"
version = "0.1.0"
dependencies = ["jax[cuda12]>=0.6.0,<0.7"]

[build-system]
build-backend = "hatchling.build"
requires = ["hatchling"]

[tool.hatch.build.targets.wheel]
packages = ["src/structure_net", "src/neural_architecture_lab"]

[tool.pixi.workspace]
channels = ["conda-forge"]
platforms = ["linux-64"]

[tool.pixi.dependencies]
python = "3.11.*"
matplotlib = "*"
numpy = "*"
pytest = "*"
tqdm = "*"
pip = "*"
ipykernel = ">=6.29.5,<7"
scipy = ">=1.16.0,<2"
scikit-learn = ">=1.7.2,<2"
pandas = ">=2.3.0,<3"
wandb = ">=0.21.0,<0.22"
seaborn = ">=0.13.2,<0.14"
pydantic = ">=2.0.0,<3"
jsonschema = ">=4.0.0,<5"
pytest-asyncio = ">=1.0.0,<2"
chromadb = ">=0.4.0,<0.5"
h5py = ">=3.14.0,<4"
jaxlib = ">=0.6.0,<0.7"
notebook = ">=7.4.4,<8"

[tool.pixi.pypi-dependencies]
structure_net = { path = ".", editable = true }

[tool.pixi.tasks]
install-torch = "pip install torch torchvision --index-url https://download.pytorch.org/whl/cu128"
test-cuda = "python -c \"import torch; print(f'PyTorch: {torch.__version__}'); print(f'CUDA available: {torch.cuda.is_available()}'); print(f'CUDA version: {torch.version.cuda}')\""
cuda-selfcheck = """
python -c "import importlib.metadata as imd, subprocess, os; \
p=imd.distribution('nvidia-cusparse-cu12').locate_file('nvidia/cusparse/lib/libcusparse.so.12'); \
out=subprocess.check_output(['ldd', str(p)], text=True); \
line=next((l for l in out.splitlines() if 'libnvJitLink.so.12' in l), ''); \
print('libcusparse:', p); \
print('nvJitLink resolve:', line); \
print('LD_LIBRARY_PATH:', os.environ.get('LD_LIBRARY_PATH',''))"
"""