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# PyTorch Scatter [![Build Status][build-image]][build-url] [![Code Coverage][coverage-image]][coverage-url]

<p align="center">
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**[Documentation](http://rusty1s.github.io/pytorch_scatter)**

This package consists of a small extension library of highly optimised sparse update (scatter) operations for the use in [PyTorch](http://pytorch.org/), which are missing in the main package.
Scatter-operations can be roughly described as reduce-operations based on a given "group-index" tensor.
The package consists of the following operations:

* [**Scatter Add**](https://rusty1s.github.io/pytorch_scatter/functions/add.html)
* [**Scatter Sub**](https://rusty1s.github.io/pytorch_scatter/functions/sub.html)
* [**Scatter Mul**](https://rusty1s.github.io/pytorch_scatter/functions/mul.html)
* [**Scatter Div**](https://rusty1s.github.io/pytorch_scatter/functions/div.html)
* [**Scatter Mean**](https://rusty1s.github.io/pytorch_scatter/functions/mean.html)
* [**Scatter Min**](https://rusty1s.github.io/pytorch_scatter/functions/min.html)
* [**Scatter Max**](https://rusty1s.github.io/pytorch_scatter/functions/max.html)

All included operations work on varying data types, are implemented both for CPU and GPU and include a backwards implementation.

## Installation

```
python setup.py install
```

## Example

```py
from torch_scatter import scatter_max

input = torch.Tensor([[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]])
index = torch.LongTensor([[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]])

max, argmax = scatter_max(index, input, dim=1)
```

```
print(max)
 0  0  4  3  2  0
 2  4  3  0  0  0
[torch.FloatTensor of size 2x6]

print(argmax)
-1 -1  3  4  0  1
 1  4  3 -1 -1 -1
[torch.LongTensor of size 2x6]
```

## Running tests

```
python setup.py test
```