code: def test_isomap_dtype_equivalence():
      """Check the equivalence of the results with 32 and 64 bits input."""
      iso_32 = manifold.Isomap(n_neighbors=2)
      X_32 = np.array([[1, 2], [3, 4], [5, 6]], dtype=np.float32)
      iso_32.fit(X_32)
  
      iso_64 = manifold.Isomap(n_neighbors=2)
      X_64 = np.array([[1, 2], [3, 4], [5, 6]], dtype=np.float64)
      iso_64.fit(X_64)
  
      assert_allclose(iso_32.dist_matrix_, iso_64.dist_matrix_)
  
imports: import math
  from itertools import product
  import numpy
  import pytest
  from scipy.sparse import rand
  from sklearn import clone, datasets, manifold, neighbors, pipeline, preprocessing
  from sklearn.datasets import make_blobs
  from sklearn.metrics.pairwise import pairwise_distances
  from sklearn.utils._testing import assert_allclose, assert_allclose_dense_sparse, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 12 for calling a global function with example usage: test_isomap_dtype_equivalence() without return types