code: def flm(tmp_path):
      """Generate first level model."""
      shapes, rk = ((7, 7, 7, 5),), 3
      (
          mask,
          fmri_data,
          design_matrices,
      ) = write_fake_fmri_data_and_design(
          shapes, rk, file_path=tmp_path
      )
      return FirstLevelModel(mask_img=mask).fit(
          fmri_data, design_matrices=design_matrices
      )
  
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 1 for calling a global function with example usage: flm(tmp_path) and returns: FirstLevelModel