## Installation
### Binaries
We provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://pytorch-geometric.com/whl).
#### PyTorch 1.5.0
To install the binaries for PyTorch 1.5.0, simply run
```pip install torch-scatter==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-1.5.0.html ```
where `${CUDA}` should be replaced by either `cpu`, `cu92`, `cu101` or `cu102` depending on your PyTorch installation.
| | `cpu` | `cu92` | `cu101` | `cu102` | |-------------|-------|--------|---------|---------| | **Linux** | ✅ | ✅ | ✅ | ✅ | | **Windows** | ✅ | ❌ | ✅ | ✅ | | **macOS** | ✅ | | | |
#### PyTorch 1.4.0
To install the binaries for PyTorch 1.4.0, simply run
```pip install torch-scatter==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-1.4.0.html ```
where `${CUDA}` should be replaced by either `cpu`, `cu92`, `cu100` or `cu101` depending on your PyTorch installation.
| | `cpu` | `cu92` | `cu100` | `cu101` | |-------------|-------|--------|---------|---------| | **Linux** | ✅ | ✅ | ✅ | ✅ | | **Windows** | ✅ | ❌ | ❌ | ✅ | | **macOS** | ✅ | | | |
### From source
Ensure that at least PyTorch 1.4.0 is installed and verify that `cuda/bin` and `cuda/include` are in your `$PATH` and `$CPATH` respectively, *e.g.*:
``` $ python -c "import torch; print(torch.__version__)" >>> 1.4.0
$ echo $PATH >>> /usr/local/cuda/bin:...
$ echo $CPATH >>> /usr/local/cuda/include:... ```
Then run:
``` pip install torch-scatter ```
When running in a docker container without nvidia driver, PyTorch needs to evaluate the compute capabilities and may fail. In this case, ensure that the compute capabilities are set via `TORCH_CUDA_ARCH_LIST`, *e.g.*:
``` export TORCH_CUDA_ARCH_LIST = "6.0 6.1 7.2+PTX 7.5+PTX" ```
## Example
```py import torch from torch_scatter import scatter_max
src = torch.tensor([[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]]) index = torch.tensor([[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]])
out, argmax = scatter_max(src, index, dim=-1) ```
``` print(out) tensor([[0, 0, 4, 3, 2, 0], [2, 4, 3, 0, 0, 0]])
print(argmax) tensor([[5, 5, 3, 4, 0, 1] [1, 4, 3, 5, 5, 5]]) ```
## Running tests
``` python setup.py test ```
## C++ API
`torch-scatter` also offers a C++ API that contains C++ equivalent of python models.
``` mkdir build cd build # Add -DWITH_CUDA=on support for the CUDA if needed cmake .. make make install ```
