Also report best_iter + 1 as best iteration

Author: lamblin

code/convolutional_mlp.py

@@ -290,7 +290,7 @@ def evaluate_lenet5(learning_rate=0.1, n_epochs=200,
     print('Optimization complete.')
     print('Best validation score of %f %% obtained at iteration %i,'\
           'with test performance %f %%' %
-          (best_validation_loss * 100., best_iter, test_score * 100.))
+          (best_validation_loss * 100., best_iter + 1, test_score * 100.))
     print >> sys.stderr, ('The code for file ' +
                           os.path.split(__file__)[1] +
                           ' ran for %.2fm' % ((end_time - start_time) / 60.))

code/mlp.py

@@ -348,7 +348,7 @@ def test_mlp(learning_rate=0.01, L1_reg=0.00, L2_reg=0.0001, n_epochs=1000,
     end_time = time.clock()
     print(('Optimization complete. Best validation score of %f %% '
            'obtained at iteration %i, with test performance %f %%') %
-          (best_validation_loss * 100., best_iter, test_score * 100.))
+          (best_validation_loss * 100., best_iter + 1, test_score * 100.))
     print >> sys.stderr, ('The code for file ' +
                           os.path.split(__file__)[1] +
                           ' ran for %.2fm' % ((end_time - start_time) / 60.))