This repo contains the code for the following paper: https://openreview.net/pdf?id=rJY0-Kcll
The following libaries are necessary:
- torch-autograd
- torch-ipc (use version from commit 'c1b2984c4c2dae085005d385996f4c0660173b27')
- torch-Dataset
- moses
Splits corresponding to meta-training, meta-validation, and meta-testing are
placed in data/miniImagenet/. Download corresponding imagenet images and
place in folder called images and place folder in data/miniImagenet/.
To train a model:
th train/run-train.lua --task [1-shot or 5-shot task] --data config.imagenet --model [model name]
For example, to run matching-nets:
th train/run-train.lua --task config.5-shot-5-class --data config.imagenet --model config.baselines.train-matching-net
And, to run LSTM meta-learner for 5-shot task:
th train/run-train.lua --task config.5-shot-5-class --data config.imagenet --model config.lstm.train-imagenet-5shot
For questions about miniImagenet format, please contact Sachin Ravi at email given in the paper.