Kh4L/pyg-lib Low-Level Graph Neural Network Operators for PyG
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We provide pre-built Python wheels for all major OS/PyTorch/CUDA combinations from Python 3.9 till 3.13, see here .
Note that currently, Windows wheels are not supported (we are working on fixing this as soon as possible).
To install the wheels, simply run
pip install pyg-lib -f https://data.pyg.org/whl/torch-${TORCH}+${CUDA}.html
where
${TORCH} should be replaced by either 1.13.0, 2.0.0, 2.1.0, 2.2.0, 2.3.0, 2.4.0, 2.5.0, or 2.6.0
${CUDA} should be replaced by either cpu, cu102, cu117, cu118, cu121, cu124, or cu126
The following combinations are supported:
PyTorch 2.6
cpu
cu117
cu118
cu121
cu124
cu126
Linux
✅
✅
✅
✅
Windows
✅
✅
✅
✅
macOS
✅
PyTorch 2.5
cpu
cu117
cu118
cu121
cu124
cu126
Linux
✅
✅
✅
✅
Windows
✅
✅
✅
✅
macOS
✅
PyTorch 2.4
cpu
cu117
cu118
cu121
cu124
cu126
Linux
✅
✅
✅
✅
Windows
✅
✅
✅
✅
macOS
✅
PyTorch 2.3
cpu
cu117
cu118
cu121
cu124
cu126
Linux
✅
✅
✅
Windows
✅
✅
✅
macOS
✅
PyTorch 2.2
cpu
cu117
cu118
cu121
cu124
cu126
Linux
✅
✅
✅
Windows
✅
✅
✅
macOS
✅
PyTorch 2.1
cpu
cu117
cu118
cu121
cu124
cu126
Linux
✅
✅
✅
Windows
✅
✅
✅
macOS
✅
PyTorch 2.0
cpu
cu117
cu118
cu121
cu124
cu126
Linux
✅
✅
✅
✅
Windows
✅
✅
✅
macOS
✅
PyTorch 1.13
cpu
cu117
cu118
cu121
cu124
cu126
Linux
✅
✅
Windows
✅
✅
macOS
✅
Nightly wheels are provided for Linux from Python 3.9 till 3.12:
pip install pyg-lib -f https://data.pyg.org/whl/nightly/torch-${TORCH}+${CUDA}.html
pip install ninja wheel
pip install --no-build-isolation git+https://github.com/pyg-team/pyg-lib.git