R-NET
A Tensorflow Implementation of R-net: Machine reading comprehension with self matching networks.
Requirements
- Python2.7
- NumPy
- tqdm
- spacy
- TensorFlow==1.2
Downloads and Setup
Once you clone this repo, run the following lines from bash just once to process the dataset (SQuAD).
$ pipenv install
$ bash setup.sh
$ pipenv shell
$ python process.py --reduce_glove True --process True
Training / Testing / Debugging / Interactive Demo
You can change the hyperparameters from params.py file to fit the model in your GPU. To train the model, run the following line.
$ python model.py
To test or debug your model after training, change mode="train" to debug or test from params.py file and run the model.
To use demo, put batch size = 1
Tensorboard
Run tensorboard for visualisation.
$ tensorboard --logdir=r-net:train/