code: def create_table(fid_w, csv_file):
      """
      Reads the input CSV file and adds performance tables to the output file.
  
      Args:
          fid_w (file pointer): Pointer to the output performance file.
          csv_file (str): Path to the recipe CSV file containing recipe information
                          (e.g., 'tests/recipes/LibriSpeech.csv').
  
      Returns:
          None
      """
  
      # Read CSV file into a list of dictionaries
      with open(csv_file, "r") as file:
          csv_reader = csv.DictReader(file)
          recipes_lst = [row for row in csv_reader]
  
          dataset = recipes_lst[0].get("Dataset", "")
          if not recipes_lst or "performance" not in recipes_lst[0]:
              return
  
          print(f"## {dataset} Dataset\n", file=fid_w)
  
      # Filter recipes
      recipes = {
          task: [] for task in set(row["Task"] for row in recipes_lst)
      }
  
      for recipe_line in recipes_lst:
          got_performance = len(recipe_line["performance"].strip()) > 0
  
          if not got_performance:
              continue
  
          task = recipe_line["Task"]
          recipes[task].append(recipe_line)
  
      # Creating performance tables for each task
      for task, recipes_task in recipes.items():
          if not recipes_task:
              continue  # Skip empty task
  
          print(f"### {task} \n", file=fid_w)
  
          performance_dict = extract_name_value_pairs(
              recipes_task[0]["performance"]
          )
          performance_metrics = performance_dict.keys()
          performance_metrics = " | ".join(performance_metrics) + " | "
  
          print(
              f"| Model | Checkpoints | HuggingFace | {performance_metrics}",
              file=fid_w,
          )
          print(
              "".join(["| --------"] * (3 + len(performance_dict)))
              + "|",
              file=fid_w,
          )
  
          for recipe in recipes_task:
              performance_dict = extract_name_value_pairs(
                  recipe["performance"]
              )
              performance_values = (
                  " | ".join(performance_dict.values()) + " | "
              )
  
              str_res = (
                  f'[here]({recipe["Result_url"]})'
                  if recipe["Result_url"]
                  else "-"
              )
              hf_repo = (
                  f'[here]({recipe["HF_repo"]})'
                  if recipe["HF_repo"]
                  else "-"
              )
  
              performance_line = f' | {recipe["Hparam_file"]} | {str_res} | {hf_repo} | {performance_values}'
              print(performance_line, file=fid_w)
  
          print("\n", file=fid_w)
  
imports: import csv
  import re
  import argparse
  from speechbrain.utils.data_utils import get_all_files
label_desc: Use image node_id 1 for calling a global function with example usage: create_table(fid_w, csv_file) without return types