code: def test_rbf_sampler_dtype_equivalence():
      """Check the equivalence of the results with 32 and 64 bits input."""
      rbf32 = RBFSampler(random_state=42)
      X32 = np.array([[1, 2], [3, 4], [5, 6]], dtype=np.float32)
      rbf32.fit(X32)
  
      rbf64 = RBFSampler(random_state=42)
      X64 = np.array([[1, 2], [3, 4], [5, 6]], dtype=np.float64)
      rbf64.fit(X64)
  
      assert_allclose(rbf32.random_offset_, rbf64.random_offset_)
      assert_allclose(rbf32.random_weights_, rbf64.random_weights_)
  
imports: import re
  import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.kernel_approximation import AdditiveChi2Sampler, Nystroem, PolynomialCountSketch, RBFSampler, SkewedChi2Sampler
  from sklearn.metrics.pairwise import chi2_kernel, kernel_metrics, polynomial_kernel, rbf_kernel
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, 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_rbf_sampler_dtype_equivalence() without return types