Addressing Catastrophic Forgetting in Few-Shot Problems

The code in this repository is for the experiments in Addressing Catastrophic Forgetting in Few-Shot Problems.

Main dependencies

• Python 3.8
• PyTorch 1.8.0
• Tensorboard 2.5.0
• Torchmeta 1.8.0

Getting started

1. Install requirements: pip install -r requirements.txt and internal modules: pip install -e .

2. Install PyTorch based on the download information in PyTorch website.

3. See data_prepare README to prepare for the datasets necessary for this project.

4. A 16GB GPU is sufficient to run any of the experiments, although a smaller GPU might also be possible by setting cuda_img=false in the config files.

Experiments

Triathlon and Pentathlon

• Use main file main_la_seqdataset.py for LA, main_vi_seqdataset.py for VI.

• Use config files triathlon_*.json for triathlon and pentathlon_*.json pentathlon.

• data_path takes the path of the parent folder containing all datasets.

  python train/<MAIN_FILE> --config_path config/<CONFIG_FILE> --data_path <PARENT_DATA_PATH>
  

Omniglot Sequential Task

• Use main file main_la_seqtask.py and config file omniglot_seqtask_la.json for LA, main_vi_seqtask.py and omniglot_seqtask_vi.json for VI.

  python train/<MAIN_FILE> --config_path config/<CONFIG_FILE> --data_path <PARENT_DATA_PATH>