code: def test_passing_masker_arguments_to_estimator(
      affine_eye, canica_data
  ):
      dict_learning = DictLearning(
          n_components=3,
          target_affine=affine_eye,
          target_shape=(6, 8, 10),
          mask_strategy="background",
      )
      dict_learning.fit(canica_data)
  
imports: import numpy
  import pytest
  from nibabel import Nifti1Image
  from nilearn._utils.testing import write_imgs_to_path
  from nilearn.conftest import _affine_eye
  from nilearn.decomposition.dict_learning import DictLearning
  from nilearn.decomposition.tests.test_canica import _make_canica_test_data
  from nilearn.image import get_data, iter_img
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 9 for calling a global function with example usage: test_passing_masker_arguments_to_estimator(affine_eye, canica_data) without return types