code: def test_algorithms():
      svd_a = sd.TruncatedSVD(30, algorithm="arpack")
      svd_r = dd.TruncatedSVD(30, algorithm="tsqr", random_state=42)
  
      Xa = svd_a.fit_transform(Xdense)[:, :6]
      Xr = svd_r.fit_transform(dXdense)[:, :6]
      assert_array_almost_equal(
          flip_vector_signs(Xa, axis=0),
          flip_vector_signs(Xr, axis=0),
          decimal=5,
      )
  
      comp_a = np.abs(svd_a.components_)
      comp_r = np.abs(svd_r.components_)
      # All elements are equal, but some elements are more equal than others.
      assert_array_almost_equal(comp_a[:9], comp_r[:9])
      assert_array_almost_equal(comp_a[9:], comp_r[9:], decimal=2)
  
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 2 for calling a global function with example usage: test_algorithms() without return types