Codes of the paper "MERINA+: Improving Generalization for Neural Video Adaptation via Information-Theoretic Meta-Reinforcement Learning" - Nuowen Kan, et. al. 2023.
This document illustrates how to obtain the results shown in the paper.
Anaconda is suggested to be installed to manage the test environments.
- Linux or macOS
- Python >=3.6
- Pytorch >= 1.6.0
- numpy, pandas
- tqdm
- seaborn
- matplotlib
- CPU or NVIDIA GPU + CUDA CuDNN
Install PyTorch. Note that the command of PyTorch intallation depends on the actual compute platform of your own computer, and you can choose appropriate version following the guide page. For example, if you have intalled CUDA 10.2, you can intall PyTorch with the latest version by running this Command:
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
Or you can create a specific environment (many redundant dependencies will be installed) just via
conda env create -f torch.yaml