def on_train_end(self):
    for (tag, df) in self.trainer.datamodule.val_history.items():
        if (tag == 'test'):
            continue
        tmp_path = 'outputs/val_predictions.csv'
        df.to_csv(tmp_path)
        mlflow.log_artifact(tmp_path, tag)
def on_train_end(self):
    for (tag, df) in self.trainer.datamodule.val_history.items():
        if (tag == 'test'):
            continue
        tmp_path = 'outputs/val_predictions.csv'
        df.to_csv(tmp_path)
        mlflow.log_artifact(tmp_path, tag)