code: def test_reshape_array_shapelets_inverse(shapelets, lengths):
      """Test that the actual results are the expected ones."""
      shapelets_array = _reshape_array_shapelets(shapelets, lengths)
      shapelets_tuple = tuple(
          _reshape_list_shapelets(shapelets_array, lengths)
      )
      assert len(shapelets) == len(shapelets_tuple)
      for arr_actual, arr_desired in zip(shapelets, shapelets_tuple):
          np.testing.assert_allclose(
              arr_actual, arr_desired, atol=1e-5, rtol=0.0
          )
  
imports: import numpy
  import pytest
  import re
  from sklearn.exceptions import ConvergenceWarning
  from pyts.classification.learning_shapelets import CrossEntropyLearningShapelets
  from pyts.classification import LearningShapelets
  from pyts.classification.learning_shapelets import _expit, _xlogy, _softmin, _softmin_grad, _softmax, _derive_shapelet_distances, _derive_all_squared_distances, _reshape_list_shapelets, _reshape_array_shapelets, _loss, _grad_weights, _grad_shapelets
label_desc: Use image node_id 11 for calling a global function with example usage: test_reshape_array_shapelets_inverse(shapelets, lengths) without return types