Models tested on MarioQA dataset

1. Dependencies (This project is tested on linux 14.04 64bit with gpu of Titan X and python 2.7.12 with anaconda 4.1.9)

Dependencies for torch (need for model training and evaluation)

• torch ['https://github.com/torch/distro']
• nn (luarocks install nn)
• cutorch (luarocks install cutorch)
• cunn (luarocks install cunn)
• cudnn ['https://github.com/soumith/cudnn.torch'] (If you don't want to use cudnn, set flag of backend in train.m and eval.m as 'nn'.)
• hdf5 (luarocks install hdf5)
• image (luarocks install image)
• npy4th (luarocks install npy4th) ['https://github.com/htwaijry/npy4th']

Dependencies for python (need for data pre-processing)

• json
• cPickle
• nltk
• numpy
• ipython notebook (need for visualization of QA annotations)
• h5py (conda install h5py or pip install h5py)
• moviepy (pip install moviepy) ['http://zulko.github.io/moviepy/']
• theano ['http://deeplearning.net/software/theano/index.html'] (need to ship the parameters of skip-thought model from python to lua.)

1. Setup instruction

We need two following processes in 001_data_constuction.

• Pre-processing annotations
• Shipping parameters of skip-thought model to be loaded in lua

Perform each process in proper folder by following the README file.

2. Training and evaluating models

Model training

Move to folder that you want to train the model, and run following lines.

mv 003_neural_models/003_spatio_temporal_attention/
bash gen_simulinks.sh
bash run_train.sh

Model evaluation

Move to folder that you want to evaluate the model, and run following lines.

mv 003_neural_models/003_spatio_temporal_attention/
bash gen_simulinks.sh
bash run_download_pretrained_model.sh
bash run_eval.sh