code: def test_sklearnex_import(dataframe, queue, macro_block):
      from sklearnex.preview.decomposition import PCA
  
      X = [[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]]
      X = _convert_to_dataframe(
          X, sycl_queue=queue, target_df=dataframe
      )
      pca = PCA(n_components=2, svd_solver="full")
      if daal_check_version((2024, "P", 0)) and macro_block is not None:
          pca.get_hyperparameters("fit").cpu_macro_block = macro_block
      pca.fit(X)
      assert "sklearnex" in pca.__module__
      assert hasattr(pca, "_onedal_estimator")
      assert_allclose(
          _as_numpy(pca.singular_values_), [6.30061232, 0.54980396]
      )
  
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose
  from daal4py.sklearn._utils import daal_check_version
  from onedal.tests.utils._dataframes_support import _as_numpy, _convert_to_dataframe, get_dataframes_and_queues
label_desc: Use image node_id 1 for calling a global function with example usage: test_sklearnex_import(dataframe, queue, macro_block) without return types