code: def test_sparse_divide():
      s1 = SparseNDArray(s1_data)
      s2 = SparseNDArray(s2_data)
  
      assert_array_equal(s1 / s2, s1 / s2, almost=True)
      assert_array_equal(s1 / d1, s1 / d1, almost=True)
      assert_array_equal(d1 / s1, d1 / s1.toarray(), almost=True)
      assert_array_equal(s1 / 2, s1 / 2, almost=True)
      assert_array_equal(2 / s1, 2 / s1.toarray(), almost=True)
  
      # test sparse vector
      v = SparseNDArray(v1, shape=(3,))
      assert_array_equal(v / v, v1_data / v1_data, almost=True)
      assert_array_equal(v / d1, v1_data / d1, almost=True)
      assert_array_equal(d1 / v, d1 / v1_data, almost=True)
      r = sps.csr_matrix(
          ((v1.data / 1), v1.indices, v1.indptr), v1.shape
      )
      assert_array_equal(v / 1, r.toarray().reshape(3), almost=True)
      r = sps.csr_matrix(
          ((1 / v1.data), v1.indices, v1.indptr), v1.shape
      )
      assert_array_equal(1 / v, r.toarray().reshape(3), almost=True)
  
imports: import pickle
  import numpy
  import pytest
  import scipy.sparse
  from ...None import sparse
  from ..None import SparseNDArray, SparseVector, SparseMatrix
  from ..core import issparse
label_desc: Use image node_id 6 for calling a global function with example usage: test_sparse_divide() without return types