code: def test_64bit(method, dt):
      # Ensure 64bit arrays are handled correctly.
      random_state = check_random_state(0)
  
      X = random_state.randn(10, 2).astype(dt, copy=False)
      tsne = TSNE(
          n_components=2,
          perplexity=2,
          learning_rate=100.0,
          random_state=0,
          method=method,
          verbose=0,
          n_iter=300,
          init="random",
      )
      X_embedded = tsne.fit_transform(X)
      effective_type = X_embedded.dtype
  
      # tsne cython code is only single precision, so the output will
      # always be single precision, irrespectively of the input dtype
      assert effective_type == np.float32
  
imports: import sys
  from io import StringIO
  import numpy
  import pytest
  import scipy.sparse
  from numpy.testing import assert_allclose
  from scipy.optimize import check_grad
  from scipy.spatial.distance import pdist, squareform
  from sklearn import config_context
  from sklearn.datasets import make_blobs
  from sklearn.exceptions import EfficiencyWarning
  from sklearn.manifold import TSNE, _barnes_hut_tsne
  from sklearn.manifold._t_sne import _gradient_descent, _joint_probabilities, _joint_probabilities_nn, _kl_divergence, _kl_divergence_bh, trustworthiness
  from sklearn.manifold._utils import _binary_search_perplexity
  from sklearn.metrics.pairwise import cosine_distances, manhattan_distances, pairwise_distances
  from sklearn.neighbors import NearestNeighbors, kneighbors_graph
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal, ignore_warnings, skip_if_32bit
  from sklearn.utils.fixes import CSR_CONTAINERS, LIL_CONTAINERS
label_desc: Use image node_id 33 for calling a global function with example usage: test_64bit(method, dt) without return types