This project includes the codes and some results of our paper. The codes of models in "models.py" are written to implement a new autoencoding architecture.
We work with a conda environment.
conda env create -f environment.yml
conda activate DPCRL
- Install CMU Multimodal SDK. Ensure, you can perform
from mmsdk import mmdatasdk
. - Option 1: Download pre-computed splits and place the contents inside
datasets
folder. - Option 2: Re-create splits by downloading data from MMSDK. For this, simply run the code as detailed next.
- Set
word_emb_path
inconfig.py
to glove file. - Set
sdk_dir
to the path of CMU-MultimodalSDK. python train.py --data mosi
. Replacemosi
withmosei
orur_funny
for other datasets.