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This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset

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Matching Networks for One Shot Learning

This repo provides a Pytorch implementation fo the Matching Networks for One Shot Learning paper.

Installation of pytorch

The experiments needs installing Pytorch


For the Omniglot dataset the download of the dataset is automatic. For the miniImageNet you need to download the ImageNet dataset and execute the script changing the lines: ``` pathImageNet = '<pathtodownloadedImageNet>/ILSVRC2012imgtrain' pathminiImageNet = '/miniImagenet/'

And also change the main file line or pass it by command line arguments:
parser.addargument('--dataroot', type=str, default='<pathtosaveMiniImageNet>/miniImagenet/',help='path to dataset') ```


$ pip install -r requirements.txt
$ python `#Code for OmniGlot`
$ python `#Code for miniImageNet`


Special thanks to and for their Matching Networks implementation. I intend to use some parts for this implementation. More details at and


  title={Matching networks for one shot learning},
  author={Vinyals, Oriol and Blundell, Charles and Lillicrap, Tim and Wierstra, Daan and others},
  booktitle={Advances in Neural Information Processing Systems},


  • Albert Berenguel (@aberenguel) Webpage

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