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the model optimizer. def create_optimizer(self, dy_model, config): lr = config.get("hyper_parameters.optimizer.learning_rate", 0.001) optimizer = paddle.optimizer.Adam( learning_rate=lr, parameters=dy_model.parameters()) return optimizer In addition, PaddleRec writes hyperparameters in config.yaml,