keras-tweaks 0.4.2

ID Sequence to Bool Mask

import tensorflow as tf
from keras_tweaks import idseqs_to_mask

idseqs = [[1, 1, 0, 0, 2, 2, 3], [1, 3, 2, 1, 0, 0, 2]]

masks = idseqs_to_mask(
    idseqs, n_seqlen=6, ignore=[1],
    dtype=tf.uint8, dense=False)

print(tf.sparse.to_dense(masks))

See example

Multiply row vector with sparse matrix

Please check the notebooks for an example and an explanation

import tensorflow as tf
from keras_tweaks 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)

Sparsity Patterns for Keras

The block-diagonal pattern for tensorflow

import tensorflow as tf
from keras_tweaks import get_sparsity_pattern

n_rows, n_cols = 10, 12
mat_pattern = get_sparsity_pattern('block', min(n_rows, n_cols), block_sizes=[3, 1, 2])
mat_values = range(1, len(mat_pattern)+1)

mat = tf.sparse.SparseTensor(
    dense_shape=(n_rows, n_cols),
    indices=mat_pattern,
    values=mat_values)

print(tf.sparse.to_dense(mat))

Please, check the howto.ipynb of the sparsity-pattern package for more sparsity patterns. The keras_tweaks.get_sparsity_pattern method works exactly the same.

Install a virtual environment

python3 -m venv .venv
source .venv/bin/activate
pip3 install --upgrade pip
pip3 install -r requirements.txt --no-cache-dir
pip3 install -r requirements-dev.txt --no-cache-dir
pip3 install -r requirements-demo.txt --no-cache-dir

(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

• Jupyter for the examples: jupyter lab

• Check syntax: flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')

• Run Unit Tests: pytest

Publish

pandoc README.md --from markdown --to rst -s -o README.rst
python setup.py sdist
twine upload -r pypi dist/*

Clean up

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

License and citation

• The function keras_tweaks.get_sparsity_pattern is a wrapper for the python package sparsity-pattern what is also licensed under Apache License 2.0. If you are using the function, and like to cite the sparsity-pattern package, then use the DOI: 10.5281/zenodo.4357290