/lxmls-toolkit

Machine Learning applied to Natural Language Processing Toolkit used in the Lisbon Machine Learning Summer School

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LxMLS 2024

Machine learning toolkit for natural language processing. Written for LxMLS - Lisbon Machine Learning Summer School

  • Scientific Python and Mathematical background
  • Linear Classifiers (Gradient Descent)
  • Feed-forward models in deep learning (Backpropagation)
  • Sequence models in deep learning
  • Attention Models (Transformers)

Bear in mind that the main purpose of the toolkit is educational. You may resort to other toolboxes if you are looking for efficient implementations of the algorithms described.

Instructions for Students

Download the code. If you are used to git just clone the student branch. For example from the command line in do

git clone git@github.com:LxMLS/lxmls-toolkit.git lxmls-toolkit-student

If you do not have a pyhon installation, install miniconda. Go to

https://docs.conda.io/en/latest/miniconda.html

and follow the instructions for installation using Python 3.

After setting up the anaconda:

use your favorite git tool to create a clone of this repository
navigate to the folder where the repository resides

install anaconda (see instruction)
conda create --name lxmls_new
conda activate lxmls_new
conda install pip
pip install --editable .

and follow the instructions for your platform (Windows, Linux, OSX). We reccomend that you create your virtual environment with a recent python version i.e.

cd lxmls-toolkit-student
conda create -y -p ./lxmls2023 python=3.9 -y
conda activate ./lxmls2023

Note the ./ in ./lxmls2023 -- this will install the virtual environment locally, so if you delete lxmls-toolkit-student you will also remove the environment.

Then install the toolkit, just to be sure upgrade your pip (always good)

pip install pip setuptools --upgrade
pip install -r requirements.txt

This will install the toolkit in a way that is modifiable. Remember to run scripts from the root directory lxmls-toolkit-student

Running

  • Run from the project root directory. If an importing error occurs, try first adding the current path to the PYTHONPATH environment variable, e.g.:
    • export PYTHONPATH=.
### Development

To run the all tests install `tox` and `pytest`

    pip install tox pytest

and run

    tox

Note, to combine the coverage data from all the tox environments run:


* Windows
    set PYTEST_ADDOPTS=--cov-append
	
* Other
    PYTEST_ADDOPTS=--cov-append tox