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))