code: def test_coerce_to_dict_with_list_of_strings():
      test_input = ["contrast_name_0", "contrast_name_1"]
      expected_output = {
          "contrast_name_0": "contrast_name_0",
          "contrast_name_1": "contrast_name_1",
      }
      actual_output = glmr._coerce_to_dict(test_input)
      assert actual_output == expected_output
  
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 9 for calling a global function with example usage: test_coerce_to_dict_with_list_of_strings() without return types