code: def test_sparse_matrix_to_string():
      m = np.zeros((9, 9))
      m[0, 4] = 5.0
      m[3, 3] = 6.0
      m_sparse = scipy.sparse.csr_matrix(m)
      expected_result = "  (0, 4)\t5.0\n  (3, 3)\t6.0"
      result = (
          rasa.shared.nlu.training_data.util.sparse_matrix_to_string(
              m_sparse
          )
      )
      assert result == expected_result
  
imports: from typing import Text
  import pytest
  import numpy
  import scipy.sparse
  import rasa.shared.nlu.training_data.util
label_desc: Use image node_id 2 for calling a global function with example usage: test_sparse_matrix_to_string() without return types