code: def benchmark_to_markdown(
      benchmark: List[List[str]], columns: List[str], rows: List[str]
  ):
      """Implement benchmark to markdown."""
      cell_width = max([len(x) for x in benchmark[0]])
      fmt = "{: >%d} " % cell_width
      out = (
          "|   "
          + fmt.format("|")
          + "| ".join([fmt.format(x) for x in columns])
          + "|\n"
      )
      sep = "|:" + cell_width * "-" + ":"
      out += (1 + len(columns)) * sep + "|\n"
      for i, r in enumerate(rows):
          out += "| " + fmt.format("%ds " % r)
          out += "| " + " | ".join(benchmark[i]) + " |\n"
      print(out)
      return out
  
file_path: speechbrain/tools/profiling/profile.py
imports: import sys
  import torch
  import speechbrain
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.utils.profiling import profile_report, export, report_time, report_memory
  from speechbrain.inference import Pretrained, EncoderDecoderASR, EncoderASR, EndToEndSLU, EncoderClassifier, SpeakerRecognition, VAD, SepformerSeparation, SpectralMaskEnhancement, SNREstimator
  from typing import Optional, List
label_desc: Use image node_id 3 for calling a global function with example usage: benchmark_to_markdown(benchmark, columns, rows) and returns: out