code: def metrics(results_fh):
      """
      Compute metrics from collated GAIA results.
  
      Args:
          results_fh (File Stream): A file stream containing the collated results in CSV.
      """
  
      reader = csv.reader(results_fh)
      first_row = next(reader)  # Read the first line
  
      num_trials = (
          len(first_row) - 1
      )  # Don't count the first column (TestId)
  
      # Set up the counters
      counters = []
      for i in range(0, num_trials):
          counters.append({"successes": 0, "failures": 0, "missing": 0})
  
      # Load the results. We'll need to iterate over them a few times.
      results = list()
      for row in reader:
          name = row[0]
          trials = [
              (None if v.strip() == "" else int(v)) for v in row[1:]
          ]
          for i in range(0, len(trials)):
              v = trials[i]
              if v is None:
                  counters[i]["missing"] += 1
              elif v > 0:
                  counters[i]["successes"] += 1
              else:
                  counters[i]["failures"] += 1
  
          results.append([name, trials])
  
      def _safe_div(num, denom):
          if denom == 0:
              return ""
          else:
              return num / denom
  
      # Print the header
      for i in range(0, len(counters)):
          counter = counters[i]
          n = (
              counter["successes"]
              + counter["failures"]
              + counter["missing"]
          )
          score = _safe_div(counter["successes"], n)
          print(
              f"{i},{n},{counter['successes']},{counter['failures']},{counter['missing']},{score}"
          )
  
imports: import os
  import sys
  import argparse
  import csv
label_desc: Use image node_id 1 for calling a global function with example usage: metrics(results_fh) and returns: str, unknown