A data scientist uses Hyperopt with SparkTrials for distributed hyperparameter tuning. Which code pattern correctly implements distributed tuning?

Afmin(fn=objective, space=search_space, algo=tpe.suggest, max_evals=50)

Bfmin(fn=objective, space=search_space, algo=tpe.suggest, max_evals=50, trials=SparkTrials())

CSparkTrials.run(fn=objective, space=search_space, max_evals=50)

Dfmin(fn=objective, space=search_space, trials=SparkTrials(), parallelism=4)

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