code: def test_32_64_decomposition_shape():
      """Test that the decomposition is similar for 32 and 64 bits data
  
      Non regression test for
      https://github.com/scikit-learn/scikit-learn/issues/18146
      """
      X, y = make_blobs(
          n_samples=30,
          centers=[[0, 0, 0], [1, 1, 1]],
          random_state=0,
          cluster_std=0.1,
      )
      X = StandardScaler().fit_transform(X)
      X -= X.min()
  
      # Compare the shapes (corresponds to the number of non-zero eigenvalues)
      kpca = KernelPCA()
      assert (
          kpca.fit_transform(X).shape
          == kpca.fit_transform(X.astype(np.float32)).shape
      )
  
imports: import warnings
  import numpy
  import pytest
  import sklearn
  from sklearn.datasets import load_iris, make_blobs, make_circles
  from sklearn.decomposition import PCA, KernelPCA
  from sklearn.exceptions import NotFittedError
  from sklearn.linear_model import Perceptron
  from sklearn.metrics.pairwise import rbf_kernel
  from sklearn.model_selection import GridSearchCV
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
  from sklearn.utils.validation import _check_psd_eigenvalues
label_desc: Use image node_id 20 for calling a global function with example usage: test_32_64_decomposition_shape() without return types