code: def test_get_ignored_labels_mask_sparse(self):
      y = csr_matrix(
          np.array(
              [
                  [1, 1],
                  [LABEL_IGNORED, 0],
                  [LABEL_IGNORED, LABEL_IGNORED],
                  [1, 0],
              ]
          )
      )
      mask = get_ignored_labels_mask(y, LABEL_IGNORED)
  
      assert_array_equal(np.array([False, True, True, False]), mask)
  
imports: import unittest
  import numpy
  from numpy.testing import assert_array_equal
  from scipy.sparse import csr_matrix
  from small_text.base import LABEL_IGNORED, LABEL_UNLABELED
  from small_text.utils.labels import concatenate, csr_to_list, get_flattened_unique_labels, get_ignored_labels_mask, get_num_labels, list_to_csr, remove_by_index
  from tests.utils.testing import assert_csr_matrix_equal
  from tests.utils.datasets import random_sklearn_dataset
label_desc: Use image node_id 6 for calling the LabelUtilsTest obj's underlying member method code with example usage: obj.test_get_ignored_labels_mask_sparse() without return types