| 137 | return model, params |
| 138 | |
| 139 | def train(selected_model, X_train, Y_train, X_valid, Y_valid, params): |
| 140 | my_history=selected_model.fit(X_train, Y_train, |
| 141 | validation_data=(X_valid, Y_valid), |
| 142 | batch_size=params['batch_size'], |
| 143 | epochs=params['epochs'], |
| 144 | callbacks=[EarlyStopping(patience=params['early_stop'], monitor="val_loss", restore_best_weights=True), History()]) |
| 145 | |
| 146 | return selected_model, my_history |
| 147 | |
| 148 | def summary_statistics(X, Y, set, task, main_model, main_params, out_dir): |
| 149 | pred = main_model.predict(X, batch_size=main_params['batch_size']) # predict |