code: def _read_configurations(self, filename):
      with open(filename) as fh:
          csv_reader = csv.DictReader(fh)
  
          configurations = dict()
          hp_names = self.cs.get_hyperparameter_names()
          for line in csv_reader:
              configuration = dict()
              algorithm_id = line["idx"]
              for hp_name, value in line.items():
                  if not value or hp_name == "idx":
                      continue
                  if hp_name not in hp_names:
                      # skip hyperparameter
                      # if it is not existing in the current search space
                      continue
                  try:
                      value = int(value)
                  except Exception:
                      try:
                          value = float(value)
                      except Exception:
                          pass
  
                  configuration[hp_name] = value
              configurations[algorithm_id] = configuration
      self.configurations = configurations
  
file_path: auto-sklearn/autosklearn/metalearning/input/aslib_simple.py
imports: import csv
  import logging
  import os
  from collections import OrderedDict, defaultdict
  import arff
  import pandas
  from ConfigSpace.configuration_space import ConfigurationSpace
label_desc: Use image node_id 6 for calling the AlgorithmSelectionProblem obj's underlying member method code with example usage: obj._read_configurations(filename) without return types