Awesome
pyg-lib
Installation
We provide pre-built Python wheels for all major OS/PyTorch/CUDA combinations from Python 3.9 till 3.12, 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 1.12.0
, 1.13.0
, 2.0.0
, 2.1.0
, 2.2.0
, 2.3.0
, or 2.4.0
${CUDA}
should be replaced by either cpu
, cu102
, cu113
, cu116
, cu117
, cu118
, or cu121
The following combinations are supported:
PyTorch 2.4 | cpu | cu113 | cu116 | cu117 | cu118 | cu121 | cu124 |
---|
Linux | ✅ | | | | ✅ | ✅ | ✅ |
Windows | ✅ | | | | ✅ | ✅ | ✅ |
macOS | ✅ | | | | | | |
PyTorch 2.3 | cpu | cu113 | cu116 | cu117 | cu118 | cu121 | cu124 |
---|
Linux | ✅ | | | | ✅ | ✅ | |
Windows | ✅ | | | | ✅ | ✅ | |
macOS | ✅ | | | | | | |
PyTorch 2.2 | cpu | cu113 | cu116 | cu117 | cu118 | cu121 | cu124 |
---|
Linux | ✅ | | | | ✅ | ✅ | |
Windows | ✅ | | | | ✅ | ✅ | |
macOS | ✅ | | | | | | |
c
PyTorch 2.1 | cpu | cu113 | cu116 | cu117 | cu118 | cu121 | cu124 |
---|
Linux | ✅ | | | | ✅ | ✅ | |
Windows | ✅ | | | | ✅ | ✅ | |
macOS | ✅ | | | | | | |
PyTorch 2.0 | cpu | cu113 | cu116 | cu117 | cu118 | cu121 | cu124 |
---|
Linux | ✅ | | | ✅ | ✅ | ✅ | |
Windows | ✅ | | | ✅ | ✅ | | |
macOS | ✅ | | | | | | |
PyTorch 1.13 | cpu | cu113 | cu116 | cu117 | cu118 | cu121 | cu124 |
---|
Linux | ✅ | | ✅ | ✅ | | | |
Windows | ✅ | | ✅ | ✅ | | | |
macOS | ✅ | | | | | | |
c
PyTorch 1.12 | cpu | cu113 | cu116 | cu117 | cu118 | cu121 | cu124 |
---|
Linux | ✅ | ✅ | ✅ | | | | |
Windows | ✅ | ✅ | ✅ | | | | |
macOS | ✅ | | | | | | |
Form nightly
Nightly wheels are provided for Linux from Python 3.9 till 3.12:
pip install pyg-lib -f https://data.pyg.org/whl/nightly/torch-${TORCH}+${CUDA}.html
From master
pip install ninja wheel
pip install git+https://github.com/pyg-team/pyg-lib.git