code: def test_pca_randomized_solver():
      # Loop excluding the 0, invalid for randomized
      for n_comp in np.arange(1, dX.shape[1]):
          pca = dd.PCA(
              n_components=n_comp,
              svd_solver="randomized",
              random_state=0,
              iterated_power=4,
          )
  
          X_r = pca.fit(dX).transform(dX)
          np.testing.assert_equal(X_r.shape[1], n_comp)
  
          X_r2 = pca.fit_transform(dX)
          # TODO: fails assert_eq
          assert_eq(X_r.compute(), X_r2.compute(), atol=1e-3)
  
          X_r = pca.transform(dX)
          # TODO: fails assert_eq
          assert_eq(X_r.compute(), X_r2.compute(), atol=1e-3)
  
          # Test get_covariance and get_precision
          cov = pca.get_covariance()
          precision = pca.get_precision()
          assert_array_almost_equal(
              np.dot(cov, precision), np.eye(X.shape[1]), 12
          )
  
      pca = dd.PCA(
          n_components=0, svd_solver="randomized", random_state=0
      )
      with pytest.raises(ValueError):
          pca.fit(dX)
  
      # Check internal state
      assert (
          pca.n_components
          == dd.PCA(
              n_components=0, svd_solver="randomized", random_state=0
          ).n_components
      )
      assert (
          pca.svd_solver
          == dd.PCA(
              n_components=0, svd_solver="randomized", random_state=0
          ).svd_solver
      )
  
imports: from itertools import product
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pytest
  import scipy
  import sklearn.decomposition
  from dask.array.utils import assert_eq
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_raises
  from sklearn import datasets
  from sklearn.utils import check_random_state
  import dask_ml.decomposition
  from dask_ml._compat import DASK_2_26_0
  from dask_ml.utils import assert_estimator_equal, flip_vector_signs, svd_flip
label_desc: Use image node_id 3 for calling a global function with example usage: test_pca_randomized_solver() without return types