code: def test_polynomial_count_sketch_dense_sparse(
      gamma, degree, coef0, csr_container
  ):
      """Check that PolynomialCountSketch results are the same for dense and sparse
      input.
      """
      ps_dense = PolynomialCountSketch(
          n_components=500,
          gamma=gamma,
          degree=degree,
          coef0=coef0,
          random_state=42,
      )
      Xt_dense = ps_dense.fit_transform(X)
      Yt_dense = ps_dense.transform(Y)
  
      ps_sparse = PolynomialCountSketch(
          n_components=500,
          gamma=gamma,
          degree=degree,
          coef0=coef0,
          random_state=42,
      )
      Xt_sparse = ps_sparse.fit_transform(csr_container(X))
      Yt_sparse = ps_sparse.transform(csr_container(Y))
  
      assert_allclose(Xt_dense, Xt_sparse)
      assert_allclose(Yt_dense, Yt_sparse)
  
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 2 for calling a global function with example usage: test_polynomial_count_sketch_dense_sparse(gamma, degree, coef0, csr_container) without return types