torch-bincount

Optimized PyTorch BinCount Operation


Keywords
pytorch, bincount, python
License
MIT
Install
pip install torch-bincount==0.1.1

Documentation

PyTorch BinCount

PyPI Version Build Status Code Coverage

This package consists of a small extension library of a highly optimized bincount operation for the use in PyTorch, which is missing in the main package. The operation works on varying data types and is implemented both for CPU and GPU.

Installation

Ensure that at least PyTorch 0.4.1 is installed and verify that cuda/bin and cuda/install are in your $PATH and $CPATH respectively, e.g.:

$ python -c "import torch; print(torch.__version__)"
>>> 0.4.1

$ echo $PATH
>>> /usr/local/cuda/bin:...

$ echo $CPATH
>>> /usr/local/cuda/install:...

Then run:

pip install torch-scatter torch-bincount

If you are running into any installation problems, please create an issue.

Usage

torch_bincount.bincount(src, size=None) -> LongTensor

Counts the number of occurrences of each value in a non-negative tensor.

Parameters

  • src (Tensor) - The input tensor.
  • size (int, optional) - The maximum number of bins for the output array. (default: None)

Returns

  • out (LongTensor) - The result of binning the input tensor.

Example

import torch
from torch_bincount import bincount

src = torch.tensor([2, 1, 1, 2, 4, 4, 2])
out = bincount(src)
print(out)
tensor([ 0,  2,  3,  0,  2])

Running tests

python setup.py test