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Commit a2ed96b

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ver 0.8
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‎.gitignore

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build/*
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_*
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_*/
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dist/*
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torchbnn.egg-info/*

‎README.md

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@@ -20,6 +20,10 @@ To help construct bayesian neural network intuitively, all codes are modified ba
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import torchbnn
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```
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### Demos
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* **Bayesian Neural Network with Iris Data** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/White%20Box%20Attack%20with%20Imagenet.ipynb)):
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To classify Iris data, in this demo, two-layer bayesian neural network is constructed and tested with plots. It shows how bayesian-neural-network works and randomness of the model.
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## Thanks to
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* @kumar-shridhar [github:PyTorch-BayesianCNN](https://github.com/kumar-shridhar/PyTorch-BayesianCNN)
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* **modules** : For supporting **freeze** method, freeze, weight_eps and bias_eps is added to each modules. If freeze is False (Defalt), weight_eps and bias_eps will be initialized with normal noise at every forward. If freeze is True, weight_eps and bias_eps won't be changed.
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### Version 0.7
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* **DO NOT USE**
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### Version 0.8
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* **modules** : For supporting **freeze** method, weight_eps and bias_eps is changed to buffer with register_buffer method. Thorugh this change, it provides save and load even if bayesian neural network is freezed.
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* **BayesModule is added** : Bayesian version of torch.nn.Module. Not being used currently.
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* **utils/freeze_model.py** :
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* **freeze, unfreeze methods are modified** : Previous methods didn't work on single layer network.
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* **freeze, unfreeze methods are modified** : Previous methods didn't work on single layer network.
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* **Demos are uploaded** : "Bayesian Neural Network with Iris Data".

‎demos/Bayesian Neural Network with Iris Data.ipynb

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‎torchbnn/__init__.py

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from .modules import *
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from . import utils
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from . import utils
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__version__ = 0.8

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