Metadata-Version: 2.1
Name: baytorch
Version: 0.0.1.dev0
Summary: BayTorch - Bayesian layers for PyTorch
Author-email: "Richard D. Paul" <richard@los-paul.eu>
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown

# BayTorch - Bayesian layers in PyTorch

Bayesian layers are probabilistic layers where weights are stochastic and sampled from the posterior distribution
or an approximation.

So far, this module includes diagonal Gaussian linear and convolutional layers with mean and standard deviation
of every weight as learnable parameters, as well as an implementation of the variational free energy loss for
stochastic gradient VI according to the Bayes-by-Backprop algorithm [1].

[1] Blundell et al., Weight Uncertainty in Neural Networks, 2015.

## Installation

Install from PyPI
```
pip install baytorch
```
or clone the repository, build and install from source
```
git clone https://jugit.fz-juelich.de/ias-8/baytorch.git && cd baytorch
python -m build
pip install dist/baytorch*whl
```
