Testing your network

We finally test our trained model against the test set.

torch.max with dim = 1 gives us a tuple in the output, where the first vector signifies the maximum value in the input matrix across each row and the other output is the index in the column that contains that maximum value. 

got_correct = 0

for idx, (data,target) in enumerate(test_loader):
    data = data.view(data.shape[0], -1)
    with torch.no_grad():
        probability = model(data)

    _, predicted_digit = torch.max(probability, dim=1)
    check_correct_predictions = predicted_digit == target
    got_correct += torch.sum(check_correct_predictions)

print("Number Of Images Tested =", len(test_loader.dataset))
print("\nModel Accuracy =", (got_correct/len(test_loader.dataset)))