docstr: :returns: {str: [float] -> float}
      A dictionary where keys are the names of submetrics and values are
      functions that aggregate a list of metrics
code: def aggregation(self):
      """
      :returns: {str: [float] -> float}
          A dictionary where keys are the names of submetrics and values are
          functions that aggregate a list of metrics
      """
      return {"em": mean, "f1": mean}
  
imports: import inspect
  import numpy
  import re
  import string
  import lm_eval.datasets.drop.drop
  from scipy.optimize import linear_sum_assignment
  from lm_eval.base import Task, rf
  from lm_eval.metrics import mean
label_desc: Use image node_id 27 for calling the DROP obj's underlying member method code with example usage: obj.aggregation() and returns: dict