def train(data, model, num_frontends, resume_epoch, model_dir): cb = SaveModelsAndTerminateEarly() cb.set_params(model_dir, resume_epoch) X_train, y_train = data[0] X_val, y_val = data[1] if 1 < num_frontends: X_train = [X_train] * num_frontends X_val = [X_val] * num_frontends try: model.fit(X_train, y_train, validation_data=(X_val, y_val), nb_epoch=10000, batch_size=128, callbacks=[cb], show_accuracy=True) except EarlyTermination: pass