def METHOD_NAME(self):
    self.train_dataset, self.train_file_list = get_reader(self.input_data,
                                                          config)
    self.test_dataset, self.test_file_list = get_infer_reader(
        self.input_data, config)
    if self.role is not None:
        self.fl_client = MyFLClient()
        self.fl_client.set_basic_config(self.role, self.config,
                                        self.metrics)
    else:
        raise ValueError("self.role is none")
    self.fl_client.set_train_dataset_info(self.train_dataset,
                                          self.train_file_list)
    self.fl_client.set_test_dataset_info(self.test_dataset,
                                         self.test_file_list)
    example_nums = 0
    self.count_method = self.config.get("runner.example_count_method",
                                        "example")
    if self.count_method == "example":
        example_nums = get_example_num(self.train_file_list)
    elif self.count_method == "word":
        example_nums = get_word_num(self.train_file_list)
    else:
        raise ValueError(
            "Set static_benchmark.example_count_method for example / word for example count."
        )
    self.fl_client.set_train_example_num(example_nums)