code: def load_data(self, n_samples=None):
      with gzip.open(
          path.join("data", "10x_mouse_zheng.pkl.gz"), "rb"
      ) as f:
          data = pickle.load(f)
  
      x, y = data["pca_50"], data["CellType1"]
  
      if n_samples is not None:
          indices = np.random.choice(
              list(range(x.shape[0])), n_samples, replace=False
          )
          x, y = x[indices], y[indices]
  
      return x, y
  
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 3 for calling the TSNEBenchmark obj's underlying member method code with example usage: obj.load_data(n_samples) and returns: x,  y