torchbnn 0.2

Bayesian Neural Network for PyTorch

Bayesian-Neural-Network-Pytorch

This is a lightweight repository of bayesian neural network for Pytorch. There are bayesian versions of pytorch layers and some utils. The aim is to help construct bayesian neural network intuitively.

Usage

Dependencies

• torch 1.2.0
• python 3.6

Installation

• pip install torchbnn or
• git clone https://github.com/Harry24k/bayesian-neural-network-pytorch

import torchbnn

Thanks to

• @kumar-shridhar github:PyTorch-BayesianCNN
• @xuanqing94 github:BayesianDefense

Update Records

Version 0.1

• modules : BayesLinear, BayesConv2d, BayesBatchNorm2d
• utils : convert_model(nonbayes_to_bayes, bayes_to_nonbayes)
• functional : bayesian_kl_loss

Version 0.2

• prior_sigma is used when initialize modules and functions instead of prior_log_sigma
  • Modules(BayesLinear, BayesConv2d, BayesBatchNorm2d) are re-defined with prior_sigma instead of prior_log_sigma.
  • convert_model(nonbayes_to_bayes, bayes_to_nonbayes) is also changed with prior_sigma instead of prior_log_sigma.
• Modules(BayesLinear, BayesConv2d, BayesBatchNorm2d) : Base initialization method is changed to the method of Adv-BNN from the original torch method.
• functional : bayesian_kl_loss is changed similar to ones in torch.functional
• loss : BKLLoss is added based on bayesian_kl_loss similar to ones in torch.loss