code: 
  from cuml.manifold import TSNE
  
  from sklearn.manifold.t_sne import trustworthiness
  from sklearn import datasets
  import pandas as pd
  import numpy as np
  import cudf
  import pytest
  
  dataset_names = ['digits', 'boston', 'iris', 'breast_cancer',
                   'diabetes']
  
  
  @pytest.mark.parametrize('name', dataset_names)
  def test_tsne(name):
      """
      This tests how TSNE handles a lot of input data across time.
      (1) cuDF DataFrames are passed input
      (2) Numpy arrays are passed in
      (3) Params are changed in the TSNE class
      (4) The class gets re-used across time
      (5) Trustworthiness is checked
      (6) Tests NAN in TSNE output for learning rate explosions
      (7) Tests verbosity
      """
      datasets
      X = eval("datasets.load_{}".format(name))().data
      X_cudf = cudf.DataFrame.from_pandas(pd.DataFrame(X))
  
      for i in range(3):
          print("iteration = ", i)
  
          tsne = TSNE(2, random_state=i, verbose=0, learning_rate=2+i)
  
          Y = tsne.fit_transform(X_cudf).to_pandas().values
          nans = np.sum(np.isnan(Y))
          trust = trustworthiness(X, Y)
          print("Trust = ", trust)
          assert trust > 0.76
          assert nans == 0
          del Y
  
          # Reuse
          Y = tsne.fit_transform(X)
          nans = np.sum(np.isnan(Y))
          trust = trustworthiness(X, Y)
          print("Trust = ", trust)
          assert trust > 0.76
          assert nans == 0
          del Y
  
          # Again
          tsne = TSNE(2, random_state=i+2, verbose=1, learning_rate=2+i+2)
  
          Y = tsne.fit_transform(X_cudf).to_pandas().values
          nans = np.sum(np.isnan(Y))
          trust = trustworthiness(X, Y)
          print("Trust = ", trust)
          assert trust > 0.76
          assert nans == 0
          del Y
  
          # Reuse
          Y = tsne.fit_transform(X)
          nans = np.sum(np.isnan(Y))
          trust = trustworthiness(X, Y)
          print("Trust = ", trust)
          assert trust > 0.76
          assert nans == 0
          del Y
  
apis: sklearn.manifold.t_sne.trustworthiness pandas.DataFrame numpy.isnan