code: def test_inverse_transform():
      # We need a lot of components for the reconstruction to be "almost
      # equal" in all positions. XXX Test means or sums instead?
      a = dd.TruncatedSVD(n_components=52, random_state=42, n_iter=5)
      b = sd.TruncatedSVD(n_components=52, random_state=42)
      b.fit(Xdense)
      Xt = a.fit_transform(dXdense)
      Xinv = a.inverse_transform(Xt)
      assert_array_almost_equal(Xinv.compute(), Xdense, decimal=1)
  
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 6 for calling a global function with example usage: test_inverse_transform() without return types