Metadata-Version: 2.1
Name: pytorchfi
Version: 0.2.0
Summary: UNKNOWN
Home-page: https://github.com/pytorchfi/pytorchfi
Author: UIUC RSim
License: UNKNOWN
Project-URL: Documentation, https://pytorchfi.github.io
Project-URL: Source Code, https://github.com/pytorchfi/pytorchfi
Description: <h1 align="center">
          <a href="https://pytorchfi.github.io/"><img src="https://user-images.githubusercontent.com/7104017/75485879-22e79400-5971-11ea-9376-2d898034c23a.png" width="150"></a>
          <br/>
            PyTorchFI
          </br>
        </h1>
        
        <p align="center">
            <a href="https://pypi.org/project/pytorchfi/"><img src="https://img.shields.io/pypi/dm/pytorchfi?color=da67f7"></a>
            <a href="https://opensource.org/licenses/NCSA"><img src="https://img.shields.io/badge/license-NCSA-blue"></a>
        </p>
        
        <h4 align="center">A project by <a href="http://rsim.cs.uiuc.edu/" target="_blank">RSim Research Group</a> in collaboration with <a href="https://www.nvidia.com/en-us/research/" target="_blank">NVIDIA Research.</a></h4>
        
        <p align="center">
          <a href="#background">Background</a> •
          <a href="#usage">Usage</a> •
          <a href="#technologies">Code</a> •
          <a href="#contributing">Contributing</a> •
          <a href="#contributors">Contributors</a> •
          <a href="#license">License</a>
        </p>
        
        ## Background
        
        PyTorchFI is a runtime perturbation tool for deep neural networks (DNNs), implemented for the popular PyTorch deep learning platform. PyTorchFI enables users to perform perturbation on weights or neurons of a DNN during runtime. It is extremely versatile for dependability and reliability research, with applications including resiliency analysis of classification networks, resiliency analysis of object detection networks, analysis of models robust to adversarial attacks, training resilient models, and for DNN interpertability.
        
        For example, this is an object detection network before a fault injection:
        
        <img src="https://user-images.githubusercontent.com/7104017/75512346-c313dc00-59b6-11ea-9563-95f642493e4e.png" width="750">
        
        This is the same object detection network after a fault injection:
        
        <img src="https://user-images.githubusercontent.com/7104017/75512345-c313dc00-59b6-11ea-856c-c8c0918eb7b6.png" width="750">
        
        Download on PyPI [here](https://pypi.org/project/pytorchfi/), or take a look at our documentation at [pytorchfi.github.io](https://pytorchfi.github.io/).
        
        ## Usage
        
        ### Installing
        
        **From Pip**
        
        Install using `pip install pytorchfi`
        
        **From Source**
        
        Download this repository into your project folder.
        
        ### Importing
        
        Import the entire package:
        
        ```python
        import pytorchfi
        ```
        
        Import a specific module:
        
        ```python
        from pytorchfi import core
        ```
        
        ## Code
        
        ### Structure
        
        The main source code of PyTorchFI is held in `pytorchfi`, which carries both `core` and `util` implementations.
        
        ### Formatting
        
        All python code is formatted with [black](https://black.readthedocs.io/en/stable/).
        
        ## Contributing
        
        Before contributing, please refer to our [contributing guidelines](https://github.com/pytorchfi/pytorchfi/blob/master/CONTRIBUTING.md).
        
        ## Contributors
        
        - [Sarita V. Adve](http://sadve.cs.illinois.edu/) (UIUC)
        - [Neeraj Aggarwal](https://neerajaggarwal.com) (UIUC)
        - [Christopher W. Fletcher](http://cwfletcher.net/) (UIUC)
        - [Siva Kumar Sastry Hari](https://research.nvidia.com/person/siva-hari) (NVIDIA)
        - [Abdulrahman Mahmoud](http://amahmou2.web.engr.illinois.edu/) (UIUC)
        - [Alex Nobbe](https://github.com/Alexn99) (UIUC)
        
        ## License
        
        [NCSA](https://opensource.org/licenses/NCSA) License. Copyright © 2020 [RSim Research Group](http://rsim.cs.uiuc.edu/).
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
