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+ [ ![ Build Status] ( https://github.com/IBM/LNN/actions/workflows/build.yml/badge.svg?branch=master )] ( https://github.com/IBM/LNN/actions/workflows/build.yml?query=branch%3Amaster )
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[ ![ License] ( https://img.shields.io/badge/license-Apache%202.0-blueviolet )] ( https://github.com/IBM/LNN/blob/master/LICENSE )
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[ ![ CII Best Practices] ( https://bestpractices.coreinfrastructure.org/projects/5926/badge )] ( https://bestpractices.coreinfrastructure.org/projects/5926 )
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[ ![ Code style: black] ( https://img.shields.io/badge/code%20style-black-000000.svg )] ( https://github.com/psf/black )
@@ -21,27 +22,55 @@ properties of both neural nets (learning) and symbolic logic (knowledge and reas
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## Quickstart
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To install the LNN:
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1 . Install [ GraphViz] ( https://www.graphviz.org/download/ ) and gmp (libgmp3-dev)
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- <details ><summary >Tips for errors "'gmp.h' file not found" and "'graphviz/cgraph.h' file not found" on Mac</summary ><div >
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-
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+ <details >
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+ <summary >Tips for installing Graphviz</summary >
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+ <div >
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+ If you experience a "graphviz/cgraph.h" file not found error, try the following:
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+
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+ ``` bash
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+ # Using Conda
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+ conda install -c anaconda graphviz
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+ ```
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+ Alternatively you can install the OS specific versions as follows:
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` ` ` bash
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+ # Ubuntu and Debian
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+ sudo apt-get install graphviz graphviz-dev
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+ ` ` `
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+ ` ` ` bash
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+ # MacOS
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brew install graphviz
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- # check the graphviz path from `brew info graphviz`
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- export GRAPHVIZ_DIR=" /usr/local/Cellar/graphviz/3.0.0"
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- pip install pygraphviz --global-option=build_ext --global-option=" -I$GRAPHVIZ_DIR /include" --global-option=" -L$GRAPHVIZ_DIR /lib"
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+ ` ` `
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+ ` ` ` bash
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+ # Windows
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+ sudo apt-get install python3-dev graphviz libgraphviz-dev pkg-config
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+ ` ` `
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+ < /div></details>
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+
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+ < details>
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+ < summary> Tips for installing gmp< /summary>
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+ < div>
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+ If you experience a " gmp.h" file not found error, try the following:
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+ ` ` ` bash
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+ # MacOS
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brew install gmp
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env " CFLAGS=-I/usr/local/include -L/usr/local/lib" pip install pycddlib
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` ` `
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+ ` ` ` bash
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+ # Windows
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+ sudo apt-get install python3-dev graphviz libgraphviz-dev pkg-config
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+ sudo -H apt-get install libgmp-dev python3-dev
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+ ` ` `
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< /div></details>
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2. Make sure that the python version you use in line with our [setup](https://github.com/IBM/LNN/blob/master/setup.py) file, using a fresh environment is always a good idea:
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` ` ` commandline
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- conda create -n lnn-contrib python=3.9 -y
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- conda activate lnn-contrib
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+ conda create -n lnn python=3.9 -y
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+ conda activate lnn
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` ` `
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- 3. Install the ` develop ` branch to keep up to date with the latest supported features :
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+ 3. Install the LNN as a library :
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` ` ` commandline
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- pip install git+https://github.com/IBM/LNN.git@develop
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+ pip install git+https://github.com/IBM/LNN.git
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` ` `
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# # Contribution
@@ -66,9 +95,9 @@ reference paper:
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}
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` ` `
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- [Docs]: https://pages .github.com/IBM /LNN/introduction.html
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- [Papers]: https://pages .github.com/IBM /LNN/papers.html
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- [Education]: https://pages .github.com/IBM /LNN/education/education.html
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- [API]: https://pages .github.com/IBM /LNN/usage.html
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- [Module]: https://pages .github.com/IBM /LNN/lnn/LNN.html
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+ [Docs]: https://ibm .github.io /LNN/introduction.html
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+ [Papers]: https://ibm .github.io /LNN/papers.html
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+ [Education]: https://ibm .github.io /LNN/education/education.html
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+ [API]: https://ibm .github.io /LNN/usage.html
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+ [Module]: https://ibm .github.io /LNN/lnn/LNN.html
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[Neuro-Symbolic AI]: https://research.ibm.com/teams/neuro-symbolic-ai
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