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This repo contains the source code accompanying a scientific paper with the same name.
Lua Python
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config set proper path for data in config for miniImagenet Feb 6, 2017
data/miniImagenet removed unnecessary meta csv file Feb 6, 2017
dataset removed garbage code Feb 6, 2017
model removed garbage code Feb 6, 2017
train cleaned up code Jan 13, 2017
util removed unused functions from util Feb 5, 2017
visualize more code-cleaninig changes Feb 3, 2017
LICENSE Initial commit Oct 21, 2016 updated contact section Feb 28, 2017


This repo contains the code for the following paper:


The following libaries are necessary:


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.

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