exnx / ARC_Omniglot

Attentive Recurrent Comparator applied to Omniglot dataset

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ARC_Omniglot

The Attentive Recurrent Comparator (ARC) catches the difference between two characters in the same way that humans do: by iteratively glancing between the images.

Please see fellowship_submission.ipynb for analysis

To run the model

  1. update pytorch to 0.4.1. Do this if you have conda:

    • conda config --add channels soumith
    • conda update pytorch torchvision
  2. download the current repo

  3. download omniglot.npy and omniglot_strokes.npz from here and place it under ./data/

    • omniglot.npy is equivalent to vertically stacking the background and evaluation datasets from Brendan Lake's Omniglot repo
  4. run: python ARC/train.py --name model

    to continue training and read classification accuracies on test set.

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Attentive Recurrent Comparator applied to Omniglot dataset

License:MIT License


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