code: def run_multiple(self, n=5, n_samples=1000):
      for idx in range(n):
          self.run(n_samples=n_samples, random_state=idx)
  
imports: import gzip
  import pickle
  import time
  from os import path
  import fire
  import numpy
  from MulticoreTSNE import MulticoreTSNE
  from sklearn.manifold import TSNE
  from sklearn.utils import check_random_state
  import openTSNE
  import openTSNE.callbacks
label_desc: Use image node_id 2 for calling the TSNEBenchmark obj's underlying member method code with example usage: obj.run_multiple(n, n_samples) without return types