keras-dense-sparse-matmul 0.1.0

Multiply row vector with sparse matrix in tensorflow

keras-dense-sparse-matmul

This package only contains one utility function dense_sparse_matmul to multiply a (dense) row vector with sparse matrix in tensorflow.

Installation

The keras-dense-sparse-matmul git repo is available as PyPi package

pip install keras-dense-sparse-matmul
pip install git+ssh://[e-mail]/ulf1/keras-dense-sparse-matmul.git

Usage

import tensorflow as tf
from keras_dense_sparse_matmul import dense_sparse_matmul

# 1x3 row vector
h = tf.constant([1., 2., 3.])

# 3x4 sparse matrix
W = tf.sparse.SparseTensor(
    indices=([0, 1], [1, 1], [1, 2], [2, 0], [2, 2], [0, 3], [2, 3]),
    values=[1., 2., 3., 4., 5., 6., 7.],
    dense_shape=(3, 4))
W = tf.sparse.reorder(W)

# result is a 1x4 row vector
net = dense_sparse_matmul(h, W)

Check the example notebook.

Appendix

Install in a virtual environment

If you want to check the function dense_sparse_matmul first, you can use Binder or install a virtual environment on your local computer

python3.6 -m venv .venv
source .venv/bin/activate
pip3 install --upgrade pip
pip3 install -r requirements.txt

(If your git repo is stored in a folder with whitespaces, then don't use the subfolder .venv. Use an absolute path without whitespaces.)

Python commands

• Activate the virtual env: source .venv/bin/activate
• Jupyter for the examples: jupyter lab
• Check syntax: flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')
• Run Unit Tests: pytest
• Upload to PyPi with twine: python setup.py sdist && twine upload -r pypi dist/*

Clean up commands

find . -type f -name "*.pyc" | xargs rm
find . -type d -name "__pycache__" | xargs rm -r
rm -r .pytest_cache
rm -r .venv

Support

Please open an issue for support.

Contributing

Please contribute using Github Flow. Create a branch, add commits, and open a pull request.