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WP6

Jupyter notebooks

The misc/notebooks directory contains examples demonstrating how the quantum and classical NLP modules are used to solve NLP-related problems (currently – a sentence classification task).

Setup

To run the notebooks you must install some software dependencies and download a spacy language model. Due to some library incompatibilities, the quantum and classical NLP modules currently cannot share a common set of software dependencies and, as a result, need to be run in separete Python environments. The instructions below describe the steps to set up an environment for the quantum NLP module using the requirements.txt file in the project's root. The steps for setting up an environement for the classical NLP module are identical except for the fact that a different requirements file – ./misc/notebooks/classical/requirements.txt – should be used.

Dependencies

We recommend using virtualenv or anaconda to create an isolated environment for the project's dependencies. Here are instructions for virtualenv.

# Install virtualenv using your distribution's package manager or pip, e.g.,
apt install virtualenv  # if using Ubuntu

# Create a new virtual environment called, e.g., venv.
# This will create a directory called venv in the project root which will
# contain all of the packages installed in the following steps. It can be safelly
# delted to get rid of the these packages.
virtualenv venv

# Activate the newly created environment
. ./venv/bin/activate

# Install the dependencies into the virtual environment
pip install -r requirements.txt
A note on the Python version

We've tested that the code works using Python 3.9. Earlier versions might not work on Linux due to incompatibility with myqlm.

Spacy language model

Some of the tools used in the quantum NLP module require a language model to be downloaded to the users system. To do it automatically, execute the following command into the virtual environment after the dependencies have been installed (see the Dependencies section above).

# Make sure the virtual environement is activated
. ./venv/bin/activate

# The language model will be stored in the venv directory
python -m spacy download en_core_web_lg

Running

To run the the notebooks, start jupyter lab and navigate to the notebooks in misc/notebooks/

# Make sure the virtual environement is activated
. ./venv/bin/activate

# Start jupyter lab and follow the instructions in the console
# output to open jupyter lab in the browser
jupyter-lab

More information

Some more information about the notebooks is provided in misc/notebooks/README.md

Generating the animal dataset

Manual dataset generation isn't necessary for running the Jupyter notebooks. However, if needed for some different purpose, the dataset can be generated using the following commands.

Run

# Choose a seed number, e.g, 1337, to deterministically randomize the sentence order
./my_lib/src/DataPreparation/gen_animal_dataset.py --seed 1337 > outfile

to generate a tab-separated file containing lines of the form <sentence>\t<sentence_type>\t<truth_value> where <truth_value> is 1 if the sentence states a fact that is true and 0 otherwise, and <sentence_type> denotes the sentence type, e.g., NOUN-TVERB-NOUN.