66 lines
1.3 KiB
Markdown
66 lines
1.3 KiB
Markdown
# BayesNet
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[](https://opensource.org/licenses/MIT)
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Bayesian Network Classifier with libtorch from scratch
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## 0. Setup
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Before compiling BayesNet.
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### boost library
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[Getting Started](<https://www.boost.org/doc/libs/1_83_0/more/getting_started/index.html>)
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The best option is install the packages that the Linux distribution have in its repository. If this is the case:
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```bash
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sudo dnf install boost-devel
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```
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If this is not possible and the compressed packaged is installed, the following environment variable has to be set pointing to the folder where it was unzipped to:
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```bash
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export BOOST_ROOT=/path/to/library/
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```
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In some cases, it is needed to build the library, to do so:
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```bash
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cd /path/to/library
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mkdir own
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./bootstrap.sh --prefix=/path/to/library/own
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./b2 install
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export BOOST_ROOT=/path/to/library/own/
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```
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Don't forget to add the export BOOST_ROOT statement to .bashrc or wherever it is meant to be.
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### libxlswriter
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```bash
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cd lib/libxlsxwriter
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make
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make install DESTDIR=/home/rmontanana/Code PREFIX=
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```
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Environment variable has to be set:
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```bash
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export LD_LIBRARY_PATH=/usr/local/lib
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```
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### Release
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```bash
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make release
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```
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### Debug & Tests
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```bash
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make debug
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```
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## 1. Introduction
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