print("Test loss: {:.3f}".format(np.mean(test_losses)))
test_acc = num_correct / len(test_loader.dataset)
print("Test accuracy: {:.3f}%".format(test_acc * 100))
test_acc = num_correct / len(test_loader.dataset)
print("Test accuracy: {:.3f}%".format(test_acc * 100))
test_labels_vector = np.array(test_labels_vector)
test_pred_vector = np.array(test_pred_vector)
stats = Stats(test_labels_vector, test_pred_vector)
all_stats.append(stats)
cf_matrix = stats.confusion_matrix()
cf_matrices.append(cf_matrix)
accuracy = stats.accuracy()
accuracies.append(accuracy)
recall = stats.recall()
recalls.append(recall)
precision = stats.precision()
precisions.append(precision)
f1 = stats.f_measure()
f1_measures.append(f1)
print(cf_matrix)
print('Accuracy: ', accuracy)
print('Average recall score: {0:0.4f}'.format(recall))
print('Average precision score: {0:0.4f}'.format(precision))
