code: def aggregate_iqm(scores: np.ndarray):
      """Computes the interquartile mean across runs and tasks.
  
      Args:
        scores: A matrix of size (`num_runs` x `num_tasks`) where scores[n][m]
          represent the score on run `n` of task `m`.
      Returns:
        IQM (25% trimmed mean) of scores.
      """
      return scipy.stats.trim_mean(
          scores, proportiontocut=0.25, axis=None
      )
  
imports: import numpy
  import scipy.stats
label_desc: Use image node_id 4 for calling a global function with example usage: aggregate_iqm(scores) and returns: scipy