Codebase for Reconstructing feedback representations in ventral visual pathway with a generative adversarial autoencoder. In this repository, we only have PyTorch implementation. Please follow the steps below to ensure that the code work correctly.
Before running the scripts, install all the python libraries:
pip install -r requirements.txt
Additionally, we pre-installed cuda/10.1, cudnn/7.6.5, and nccl/2.5.6. Instructions can be found here https://developer.nvidia.com/cuda-toolkit-archive
There is one main script that perform most operations used in the paper: main.py
To start training with default options, this command will do:
python main.py train_aae
The command above will train an adversarial autoencoder. To change that, you can replace the function with:
python main.py train_vae
This will train a variational autoencoder.
To get the RDMs after training you'll need to run:
python main.py gen_rdm
Make sure that you have the saved model in the ./model directory.
Models for the final results can be downloaded from [GOOGLE DRIVE]
Please make sure to maintain the folder structure.