code: public <T extends Evaluation> T evaluate(String path, int batchSize, DataSetLoader loader){
          JavaRDD<String> paths;
          try {
              paths = SparkUtils.listPaths(sc, path);
          } catch (IOException e) {
              throw new RuntimeException("Error listing paths in directory", e);
          }
  
          JavaRDD<DataSet> rdd = paths.map(new LoadDataSetFunction(loader, new RemoteFileSourceFactory(BroadcastHadoopConfigHolder.get(sc))));
          return (T)doEvaluation(rdd, batchSize, new org.deeplearning4j.eval.Evaluation())[0];
      }
docs: Evaluate on a directory containing a set of DataSet objects to be loaded with a {@link DataSetLoader}.
  Uses default batch size of {@link #DEFAULT_EVAL_SCORE_BATCH_SIZE}
  @param path Path/URI to the directory containing the datasets to load
  @return Evaluation