code: def trim_mean(data, trim_percent):
      """Compute the trimmed mean of a list of numbers.
  
      Args:
          data (list): List of numbers.
          trim_percent (float): Percentage of data to trim.
  
      Returns:
          float: Trimmed mean.
      """
      assert trim_percent >= 0.0 and trim_percent <= 1.0
      n = len(data)
      # Account for edge case of empty list
      if len(data) == 0:
          return 0
      data.sort()
      k = int(round(n * (trim_percent)))
      return mean(data[k : n - k])
  
imports: import time
  import torch
  from numpy import mean
  from deepspeed.utils.logging import log_dist
  from deepspeed import comm
label_desc: Use image node_id 1 for calling a global function with example usage: trim_mean(data, trim_percent) and returns: mean, int