What model to train to restore MNIST test dataset

I came across this problem, and not sure where to start. What model would work best for this problem and why?

Imagine the digits in the test set of the MNIST dataset (http://yann.lecun.com/exdb/mnist/) got cut in half vertically and shuffled around. Implement a way to restore the original test set from the two halves, whilst maximising the overall matching accuracy.

Topic mnist machine-learning-model model-selection classification python

Category Data Science

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