code: def test_check_report_dims():
      test_input = (1200, "a")
      expected_output = (1600, 800)
      expected_warning_text = (
          "Report size has invalid values. Using default 1600x800"
      )
      with pytest.warns(UserWarning, match=expected_warning_text):
          actual_output = glmr._check_report_dims(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 7 for calling a global function with example usage: test_check_report_dims() without return types