# pytorch_runstats
Running/online statistics for PyTorch.

[![Documentation Status](https://readthedocs.org/projects/pytorch-runstats/badge/?version=latest)](https://pytorch-runstats.readthedocs.io/en/latest/?badge=latest)

`torch_runstats` implements memory-efficient online reductions on tensors. 

Notable features:
 - Arbitrary sample shapes beyond single scalars
 - Reduction over arbitrary dimensions of each sample
 - "Batched"/"binned" reduction into multiple running tallies using a per-sample bin index. 
  This can be useful, for example, in accumulating statistics over samples by some kind of "type" index or for accumulating statistics per-graph in a `pytorch_geometric`-like [batching scheme](https://pytorch-geometric.readthedocs.io/en/latest/notes/batching.html). (This feature is similar to [`torch_scatter`](https://pytorch-scatter.readthedocs.io/en/latest/functions/scatter.html).)
 - Option to ignore NaN values with correct sample counting.

**Note:** the implementations currently heavily uses in-place operations for peformance and memory efficiency. This probably doesn't play nice with the autograd engine — this is currently likely the wrong library for accumulating running statistics you want to backward through. (See [TorchMetrics](https://torchmetrics.readthedocs.io/en/latest/) for a possible alternative.)

For more information, please see [the docs](https://pytorch-runstats.readthedocs.io/en/latest/).

## Install

`torch_runstats` requires PyTorch.

The library can be installed from PyPI:
```bash
$ pip install torch_runstats
```

The latest development version of the code can also be installed from `git`:
```bash
$ git clone https://github.com/mir-group/pytorch_runstats
```
and install it by running
```bash
$ cd torch_runstats/
$ pip install .
```

You can run the tests with
```bash
$ pytest tests/
```

## License

`pytorch_runstats` is distributed under an [MIT license](LICENSE).



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torch-runstats

pytorch_runstats

Install

License

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