I want to compute and display accuracy on the test set while the network is training.
In the MNIST tutorial that uses feeds, one can see that it can be done easily by feeding test data rather than train data. Simple solution to a simple problem.
However I am not able to find such an easy example when using queues for batching. AFAICS, the documentation proposes two solutions:
- Offline testing with saved states. I don't want offline.
- Making a second 'test' network that share weights with the network being trained. That doesn't sound simple and I have not seen an example of that.
Is there a third, easy way to compute test metrics at run time? Or is there an example somewhere of the second, test network with shared weights that proves me wrong by being super simple to implement?
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