code: def test_coerce_to_dict_with_array_of_ints():
      test_input = np.array([1, 0, 1])
      expected_output = {"[1 0 1]": np.array([1, 0, 1])}
      actual_output = glmr._coerce_to_dict(test_input)
      assert expected_output.keys() == actual_output.keys()
      assert np.array_equal(
          actual_output["[1 0 1]"], expected_output["[1 0 1]"]
      )
  
imports: import numpy
  import pandas
  import pytest
  from nibabel import load
  from nilearn._utils.data_gen import write_fake_fmri_data_and_design
  from nilearn.glm.first_level import FirstLevelModel
  from nilearn.glm.first_level.design_matrix import make_first_level_design_matrix
  from nilearn.glm.second_level import SecondLevelModel
  from nilearn.maskers import NiftiMasker
  from nilearn.reporting import glm_reporter
label_desc: Use image node_id 14 for calling a global function with example usage: test_coerce_to_dict_with_array_of_ints() without return types