def METHOD_NAME(self, dy_model, metrics_list, batch_data, config):
    label, sparse_tensor, dense_tensor = self.create_feeds(batch_data,
                                                           config)
    # print("---dygraph-----label, sparse_tensor, dense_tensor",label, sparse_tensor, dense_tensor)
    pred, l2_loss = dy_model.forward(sparse_tensor, dense_tensor)
    loss = self.create_loss(pred, label) + l2_loss
    # update metrics
    predict_2d = paddle.concat(x=[1 - pred, pred], axis=1)
    # print("---dygraph----pred,loss,predict_2d---",pred,loss,predict_2d)
    # print("---dygraph----metrics_list",metrics_list)
    metrics_list[0].update(preds=predict_2d.numpy(), labels=label.numpy())
    # print_dict format :{'loss': loss} 
    print_dict = None
    return loss, metrics_list, print_dict