code: def test_tsne_large(nrows, ncols, method):
      """
      This tests how TSNE handles large input
      """
      X, y = make_blobs(
          n_samples=nrows, centers=8, n_features=ncols, random_state=1
      ).astype(np.float32)
  
      tsne = TSNE(
          random_state=1,
          exaggeration_iter=1,
          n_iter=2,
          method=method,
          min_grad_norm=1e-12,
      )
      Y = tsne.fit_transform(X)
      nans = np.sum(np.isnan(Y))
      assert nans == 0
  
imports: import pytest
  from sklearn.manifold import TSNE
  from sklearn import datasets
  from sklearn.manifold import trustworthiness
  from sklearn.datasets import make_blobs
  from sklearn.neighbors import NearestNeighbors
  from cuml.manifold import TSNE
  from cuml.neighbors import NearestNeighbors
  from cuml.metrics import pairwise_distances
  from cuml.testing.utils import array_equal, stress_param
  from cuml.internals.safe_imports import cpu_only_import
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 6 for calling a global function with example usage: test_tsne_large(nrows, ncols, method) without return types