code: def list_to_latex(convert_list, bigger_flag=True, subset_columns=[]):
      result = {}
      for d in convert_list:
          for key, value in d.items():
              if key in result:
                  result[key].append(value)
              else:
                  result[key] = [value]
  
      df = pd.DataFrame.from_dict(result, orient="index").T
  
      if len(subset_columns) == 0:
          tex = df.to_latex(index=False)
          return df, tex
  
      def bold_func(x, bigger_flag):
          if bigger_flag:
              return np.where(
                  x == np.max(x.to_numpy()), "font-weight:bold", None
              )
          else:
              return np.where(
                  x == np.min(x.to_numpy()), "font-weight:bold", None
              )
  
      style = df.style
      style.apply(
          bold_func, bigger_flag=bigger_flag, subset=subset_columns
      )
      style.format(precision=4)
  
      num_column = len(df.columns)
      column_format = "c" * num_column
      tex = style.hide(axis="index").to_latex(
          caption="Result Table",
          label="Result Table",
          convert_css=True,
          hrules=True,
          column_format=column_format,
      )
  
      return df, tex
  
imports: import datetime
  import importlib
  import os
  import random
  import pandas
  import numpy
  import torch
  import torch.nn
  from torch.utils.tensorboard import SummaryWriter
  from texttable import Texttable
  from recbole.utils.enum_type import ModelType
label_desc: Use image node_id 12 for calling a global function with example usage: list_to_latex(convert_list, bigger_flag, subset_columns) and returns: df,  tex, df,  tex, np, np