def METHOD_NAME(self, model_list):
    training_num = 0
    for i in range(0, len(model_list)):
        local_sample_number, local_model_params = model_list[i]
        training_num += local_sample_number
    (num0, averaged_params) = model_list[0]
    for k in averaged_params.keys():
        for i in range(0, len(model_list)):
            local_sample_number, local_model_params = model_list[i]
            if i == 0:
                averaged_params[k] = (
                    local_model_params[k] * local_sample_number / training_num
                )
            else:
                averaged_params[k] += (
                    local_model_params[k] * local_sample_number / training_num
                )
    return averaged_params