def test(model, x_test): return common_test(model, x_test)
'lstm_layers': lstm_layers, 'dropout': dropout, }) model.apply(init_weights) trainer = Trainer( gpus=1, min_epochs=12, max_epochs=100, progress_bar_refresh_rate=0, ) trainer.fit(model) xs = model.tds[:][0] ys = model.tds[:][1] y_hat = common_test(model, xs.cpu().numpy()) fig, ax = plt.subplots(1, 1) cm_train = u_metrics.create_confusion_matrix( classes, y_hat, ys) u_plot.plot_confusion_matrix(cm_train, title=f'All', ax=ax) plt.show() print('Dist: ', np.histogram(ys.cpu().numpy(), bins=classes)[0]) acc_train, recall_train, f1_train = u_metrics.get_metrics( y_hat, ys.cpu().numpy()) print( f'layers: {lstm_layers:6} hidden: {hidden:6} dout: {dropout:6} LR: {lr:6} Acc: {acc_train:6.3f}, Rec: {recall_train:6.3f}, F1: {f1_train:6.3f}' )