

def compute_trials(self, model, data, max_evals):
    model_string = get_hyperopt_model_string(model, data)
    bc_model = self.spark_context.broadcast(model_string)
    bc_max_evals = self.spark_context.broadcast(max_evals)
    hyperas_worker = HyperasWorker(bc_model, bc_max_evals)
    dummy_rdd = self.spark_context.parallelize([i for i in range(1, 1000)])
    dummy_rdd = dummy_rdd.repartition(self.num_workers)
    trials_list = data.mapPartitions(hyperas_worker.minimize).collect()
    return trials_list

dataset/ETHPy150Open maxpumperla/elephas/elephas/hyperparam.py HyperParamModel.compute_trials/VarMisuse@91/148 `dummy_rdd`->`data`