code: def test_initialization():
      rng = np.random.RandomState(0)
      U_init = rng.randn(5, 3)
      V_init = rng.randn(3, 4)
      model = SparsePCA(
          n_components=3,
          U_init=U_init,
          V_init=V_init,
          max_iter=0,
          random_state=rng,
      )
      model.fit(rng.randn(5, 4))
      assert_allclose(
          model.components_,
          V_init / np.linalg.norm(V_init, axis=1)[:, None],
      )
  
imports: import sys
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from sklearn.decomposition import PCA, MiniBatchSparsePCA, SparsePCA
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, if_safe_multiprocessing_with_blas
label_desc: Use image node_id 7 for calling a global function with example usage: test_initialization() without return types