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Bayesian Neural Network for PyTorch

Project description


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.



  • torch 1.2.0
  • python 3.6


  • pip install torchbnn or
  • git clone
import torchbnn

Thanks to

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

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