class_docstr: The leaderBoard that can be used to store / sort the model performance automatically.
  
  Parameters
  ----------
  fields: list of `str`
      A list of field name that shows the model performance. The first field is used as
      the major field for sorting the model performances.
  
  is_higher_better: `dict` of *field* -> `bool`
      A mapping of indicator that whether each field is higher better.
class_docstr_tok: ["The","leaderBoard","that","can","be","used","to","store","\/","sort","the","model","performance","automatically",".","Parameters","--","--","--","--","--","fields",":","list","of","`","str","`","A","list","of","field","name","that","shows","the","model","performance",".","The","first","field","is","used","as","the","major","field","for","sorting","the","model","performances",".","is_higher_better",":","`","dict","`","of","*","field","*","-",">","`","bool","`","A","mapping","of","indicator","that","whether","each","field","is","higher","better","."]
docstr: Show current LeaderBoard (from best model to worst).
  
  Parameters
  ----------
  top_k: `int`
      Controls the number model shown.
      If less than or equal to `0`, will show all the models. Default to `0`.
  
  Returns
  -------
  None
docstr_tok: ["Show","current","LeaderBoard","(","from","best","model","to","worst",")",".","Parameters","--","--","--","--","--","top_k",":","`","int","`","Controls","the","number","model","shown",".","If","less","than","or","equal","to","`","0","`",",","will","show","all","the","models",".","Default","to","`","0","`",".","Returns","--","--","--","-","None"]
code: def show(self, top_k=0) -> None:
      """
      Show current LeaderBoard (from best model to worst).
  
      Parameters
      ----------
      top_k: `int`
          Controls the number model shown.
          If less than or equal to `0`, will show all the models. Default to `0`.
  
      Returns
      -------
      None
      """
      top_k: int = top_k if top_k > 0 else len(self.perform_dict)
  
      """
          reindex self.__performance_data_frame
          to ensure the columns of name and representation are in left-side of the data frame
          """
      _columns = self.perform_dict.columns.tolist()
      maxcolwidths: _typing.List[_typing.Optional[int]] = []
      if "name" in _columns:
          _columns.remove("name")
          _columns.insert(0, "name")
          maxcolwidths.append(40)
      self.perform_dict = self.perform_dict[_columns]
  
      sorted_performance_df: pd.DataFrame = (
          self.perform_dict.sort_values(
              self.major_field,
              ascending=not self.is_higher_better[self.major_field],
          )
      )
      sorted_performance_df = sorted_performance_df.head(top_k)
  
      from tabulate import tabulate
  
      _columns = sorted_performance_df.columns.tolist()
      maxcolwidths.extend(
          [None for _ in range(len(_columns) - len(maxcolwidths))]
      )
      print(
          tabulate(
              list(
                  zip(
                      *[
                          sorted_performance_df[column]
                          for column in _columns
                      ]
                  )
              ),
              headers=_columns,
              tablefmt="grid",
          )
      )
  
imports: import random
  import typing
  import torch
  import torch.backends.cudnn
  import numpy
  import pandas
  from ..backend import DependentBackend
  from ..data import Dataset
  from ..data.graph import GeneralStaticGraph
  from ..utils import get_logger
label_desc: Use image node_id 6 for calling the LeaderBoard obj's underlying member method code with example usage: obj.show(top_k) without return types