code: def print_wer_summary(wer_details, file=sys.stdout):
      """Prints out WER summary details in human-readable format.
  
      This function essentially mirrors the Kaldi compute-wer output format.
  
      Arguments
      ---------
      wer_details : dict
          Dict of wer summary details,
          see ``speechbrain.utils.edit_distance.wer_summary``
          for format.
      file : stream
          Where to write. (default: sys.stdout)
      """
      print(
          "%WER {WER:.2f} [ {num_edits} / {num_scored_tokens}, {insertions} ins, {deletions} del, {substitutions} sub ]".format(  # noqa
              **wer_details
          ),
          file=file,
          end="",
      )
      print(
          " [PARTIAL]"
          if wer_details["num_scored_sents"]
          < wer_details["num_ref_sents"]
          else "",
          file=file,
      )
      print(
          "%SER {SER:.2f} [ {num_erraneous_sents} / {num_scored_sents} ]".format(
              **wer_details
          ),
          file=file,
      )
      print(
          "Scored {num_scored_sents} sentences, {num_absent_sents} not present in hyp.".format(  # noqa
              **wer_details
          ),
          file=file,
      )
  
file_path: speechbrain/speechbrain/dataio/wer.py
imports: import sys
  from speechbrain.utils import edit_distance
label_desc: Use image node_id 1 for calling a global function with example usage: print_wer_summary(wer_details, file) without return types