code: def test_compute(algorithm, compute):
      est = dd.TruncatedSVD(
          random_state=0, algorithm=algorithm, compute=compute
      )
      est.fit(dXdense)
      array_class = np.ndarray if compute else da.Array
      assert isinstance(est.components_, array_class)
      assert isinstance(est.explained_variance_, array_class)
      assert isinstance(est.explained_variance_ratio_, array_class)
      assert isinstance(est.singular_values_, array_class)
  
file_path: dask-ml/tests/test_svd.py
imports: import dask.array
  import numpy
  import pytest
  import scipy.sparse
  from numpy.testing import assert_array_almost_equal
  from sklearn import decomposition
  from sklearn.utils import check_random_state
  from dask_ml import decomposition
  from dask_ml.utils import assert_estimator_equal, flip_vector_signs
label_desc: Use image node_id 4 for calling a global function with example usage: test_compute(algorithm, compute) without return types