code: def download(self, name, path):
      old_name = name + "_train.bz2"
      update_name = name + "_train.svm"
  
      if os.path.exists(old_name) and os.path.exists(update_name):
          return update_name
  
      urllib.request.urlretrieve(path, filename=old_name)
  
      f_svm = open(update_name, "wt")
      with bz2.open(old_name, "rb") as f_zip:
          data = f_zip.read()
          f_svm.write(data.decode("utf-8"))
      f_svm.close()
  
      return update_name
  
imports: import bz2
  import urllib.request
  import numpy
  import datetime
  import line_profiler
  import os
  from sklearn.datasets import load_svmlight_file
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import make_pipeline
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import ExtraTreesClassifier
  from sklearn.feature_selection import SelectFromModel
  from nni.algorithms.feature_engineering.gradient_selector import FeatureGradientSelector
label_desc: Use image node_id 4 for calling the Benchmark obj's underlying member method code with example usage: obj.download(name, path) and returns: update_name, update_name