Installation Guide

Overview

rdf2vecgpu is distributed on PyPI. Install with pip for the quickest setup. GPU acceleration is optional and depends on your system’s PyTorch/CUDA setup.

Prerequisites

  • Python 3.12 or newer

  • Linux, or Windows

  • NVIDIA GPU with a compatible CUDA driver 12.x (Linux/Windows)

Note for macOS users:

CUDA-based GPU acceleration is not available on macOS in most cases. The package will not be able to run.

Quick install (PyPI)

Create and activate a virtual environment (recommended), then install:

# macOS / Linux
python3 -m venv .venv
source .venv/bin/activate

# Upgrade packaging tools
python -m pip install -U pip setuptools wheel

# Install rdf2vecgpu from PyPI
python -m pip install -U rdf2vecgpu

Optional extras

rdf2vecgpu ships several optional dependency groups. Install the ones you need:

# Experiment tracking backends
python -m pip install -U "rdf2vecgpu[mlflow]"
python -m pip install -U "rdf2vecgpu[wandb]"

# Test dependencies
python -m pip install -U "rdf2vecgpu[test]"

When working from source with uv, the equivalent commands are:

uv sync --extra mlflow
uv sync --extra wandb
uv sync --extra test

GPU acceleration

To use the package with GPU acceleration, install the relevant CUDA 12.x drivers, then install rdf2vecgpu:

  1. Install PyTorch following the official selector for your OS/CUDA: https://pytorch.org/get-started/locally/

  2. Verify PyTorch CUDA:

import torch
print("CUDA available:", torch.cuda.is_available())

  1. Install rdf2vecgpu (if not already installed):

python -m pip install -U rdf2vecgpu

Notes: - On Linux/Windows, ensure your NVIDIA driver and CUDA runtime match the PyTorch build.

Conda (optional)

If you prefer Conda for environment management:

conda create -n rdf2vecgpu python=3.12 -y
conda activate rdf2vecgpu
python -m pip install -U pip
python -m pip install -U rdf2vecgpu

Install from source (this repository)

If you are working with the sources in this repo:

# From the project root
python -m venv .venv
source .venv/bin/activate

python -m pip install -U pip setuptools wheel
python -m pip install -e .

# Optional: install test/dev tools if provided by the project
# python -m pip install -e ".[dev]"

Verify your installation

Run a quick import check:

try:
    import rdf2vecgpu
    try:
        import torch
        cuda = torch.cuda.is_available()
    except Exception:
        cuda = False
    print("rdf2vecgpu imported OK")
    print("CUDA available:", cuda)
    v = getattr(rdf2vecgpu, "__version__", "unknown")
    print("rdf2vecgpu version:", v)
except Exception as e:
    print("Import failed:", e)
    raise

Troubleshooting

  • No matching distribution found / pip cannot find a wheel: - Upgrade pip: python -m pip install -U pip - Ensure your Python version is supported (Python 3.8+). - On some platforms/architectures, building from source may require build tools.

  • CUDA or GPU not detected: - Verify your PyTorch install: python -c "import torch; print(torch.cuda.is_available())" - Install a CUDA-enabled PyTorch build matching your driver/runtime. - macOS does not support CUDA; use CPU.

  • Permission errors on Linux: - Use a virtual environment, or add --user to pip installs.

  • Still stuck? - Check the package page on PyPI: https://pypi.org/project/rdf2vecgpu/ - Consult your CUDA/PyTorch installation - Open an issue on Github issue page