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Packages \u003csmall\u003e(14)\u003c/small\u003e"],"sub_categories":["\u003cimg src=\"assets/pytorch.svg\" alt=\"PyTorch\" height=\"20px\"\u003e \u0026nbsp;PyTorch Packages"],"readme":"|Logo|\n\n.. image:: https://github.com/vislearn/FrEIA/workflows/CI/badge.svg\n   :alt: Build Status\n\nThis is the **Fr**\\ amework for **E**\\ asily **I**\\ nvertible **A**\\ rchitectures (**FrEIA**).\n\n* Construct Invertible Neural Networks (INNs) from simple invertible building blocks.\n* Quickly construct complex invertible computation graphs and INN topologies.\n* Forward and inverse computation guaranteed to work automatically.\n* Most common invertible transforms and operations are provided.\n* Easily add your own invertible transforms.\n\n.. contents:: Table of contents\n   :backlinks: top\n   :local:\n\nPapers\n--------------\n\nOur following papers use FrEIA, with links to code given below.\n\n**\"Generative Classifiers as a Basis for Trustworthy Image Classification\" (CVPR 2021)**\n\n* Paper: https://arxiv.org/abs/2007.15036\n* Code: https://github.com/RayDeeA/ibinn_imagenet\n\n**\"Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification\" (Neurips 2020)**\n\n* Paper: `arxiv.org/abs/2001.06448 \u003chttps://arxiv.org/abs/2001.06448\u003e`_\n* Code: `github.com/vislearn/IB-INN \u003chttps://github.com/vislearn/IB-INN\u003e`_\n\n**\"Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)\" (ICLR 2020)**\n\n* Paper: `arxiv.org/abs/2001.04872 \u003chttps://arxiv.org/abs/2001.04872\u003e`_\n* Code: `github.com/vislearn/GIN \u003chttps://github.com/vislearn/GIN\u003e`_\n\n**\"Guided Image Generation with Conditional Invertible Neural Networks\" (2019)**\n\n* Paper: `arxiv.org/abs/1907.02392 \u003chttps://arxiv.org/abs/1907.02392\u003e`_\n* Supplement: `drive.google.com/file/d/1_OoiIGhLeVJGaZFeBt0OWOq8ZCtiI7li \u003chttps://drive.google.com/file/d/1_OoiIGhLeVJGaZFeBt0OWOq8ZCtiI7li\u003e`_\n* Code: `github.com/vislearn/conditional_INNs \u003chttps://github.com/vislearn/conditional_INNs\u003e`_\n\n**\"Analyzing inverse problems with invertible neural networks.\" (ICLR 2019)**\n\n* Paper: `arxiv.org/abs/1808.04730 \u003chttps://arxiv.org/abs/1808.04730\u003e`_\n* Code: `github.com/vislearn/analyzing_inverse_problems \u003chttps://github.com/vislearn/analyzing_inverse_problems\u003e`_\n\n\nInstallation\n--------------\n\nFrEIA has the following dependencies:\n\n+---------------------------+-------------------------------+\n| **Package**               | **Version**                   |\n+---------------------------+-------------------------------+\n| Python                    | \u003e= 3.7                        |\n+---------------------------+-------------------------------+\n| Pytorch                   | \u003e= 1.0.0                      |\n+---------------------------+-------------------------------+\n| Numpy                     | \u003e= 1.15.0                     |\n+---------------------------+-------------------------------+\n| Scipy                     | \u003e= 1.5                        |\n+---------------------------+-------------------------------+\n\nThrough pip\n^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n.. code:: sh\n\n   pip install FrEIA\n\nManually\n^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nFor development:\n\n.. code:: sh\n\n   # first clone the repository\n   git clone https://github.com/vislearn/FrEIA.git\n   cd FrEIA\n   # install the dependencies\n   pip install -r requirements.txt\n   # install in development mode, so that changes don't require a reinstall\n   python setup.py develop\n\n\nDocumentation\n-----------------\n\nThe full manual can be found at\nhttps://vislearn.github.io/FrEIA\nincluding\n\n* `Quickstart guide \u003chttps://vislearn.github.io/FrEIA/_build/html/tutorial/quickstart.html\u003e`_\n* `Tutorial \u003chttps://vislearn.github.io/FrEIA/_build/html/tutorial/tutorial.html\u003e`_\n* `Examples \u003chttps://vislearn.github.io/FrEIA/_build/html/tutorial/examples.html\u003e`_\n* `API documentation \u003chttps://vislearn.github.io/FrEIA/_build/html/index.html#package-documentation\u003e`_\n\n\nHow to cite this repository\n-------------------------------\n\nIf you used this repository in your work, please cite it as below:\n\n.. code-block:: \n   \n   @software{freia,\n     author = {Ardizzone, Lynton and Bungert, Till and Draxler, Felix and Köthe, Ullrich and Kruse, Jakob and Schmier, Robert and Sorrenson, Peter},\n     title = {{Framework for Easily Invertible Architectures (FrEIA)}},\n     year = {2018-2022},\n     url = {https://github.com/vislearn/FrEIA}\n   }\n\n.. |Logo| image:: docs/freia_logo_invertible.svg\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvislearn%2FFrEIA","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvislearn%2FFrEIA","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvislearn%2FFrEIA/lists"}