Undercounting Batches in Accuracy Calculation

[ztosi]

Hi there, nice project! I've actually been using it as a base for some of my own work on scaling CDN on HPC systems. In doing that I noticed a bug, though:

CoDeepNEAT/src/phenotype/neural_network/evaluator/evaluator.py

Line 117 in 3476078

def test_nn(model: Network, test_loader: DataLoader):

In test_nn where you calculate accuracy, you set the counter used as the denominator equal to the batch_idx, which undercounts the number of batches by one. In the limit, one can imagine a case where the entire dataset is a single batch and in that case "count" would be 0.

I was using a fairly large batch size and getting really inflated accuracy numbers.

[sash-a]

Hey sorry for getting back to you so late, I don't think I got a notification.

Good catch, I think the cleanest fix would probably be:

for batch_idx, (inputs, targets) in enumerate(test_loader, 1):

You can open a PR if you want 😄