code: def test_pca_bad_solver():
      X = np.random.RandomState(0).rand(5, 4)
      pca = dd.PCA(n_components=3, svd_solver="bad_argument")
      assert_raises(ValueError, pca.fit, da.from_array(X))
  
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 26 for calling a global function with example usage: test_pca_bad_solver() without return types