docstr: :returns: {str: [metric_score] -> float}
      A dictionary where keys are the names of submetrics and values are
      functions that aggregate a list of metric scores
docstr_tok: [":","returns",":","{","str",":","[","metric_score","]","-",">","float","}","A","dictionary","where","keys","are","the","names","of","submetrics","and","values","are","functions","that","aggregate","a","list","of","metric","scores"]
code: def aggregation(self):
      """
      :returns: {str: [metric_score] -> float}
          A dictionary where keys are the names of submetrics and values are
          functions that aggregate a list of metric scores
      """
      # TODO: For each (sub)metric in the task evaluation, add a key-value pair
      # with the metric name as key and an aggregation function as value which
      # determines how to combine results from each document in the dataset.
      # Check `lm_eval.metrics` to find built-in aggregation functions.
      return {}
  
file_path: lm-evaluation-harness/templates/new_task.py
imports: from lm_eval.base import Task
label_desc: Use image node_id 12 for calling the NewTask obj's underlying member method code with example usage: obj.aggregation() and returns: dict