code: def test_sparse_nd_pickle():
      dim0 = 40
      dim1 = 40
      stypes = ["row_sparse", "csr"]
      densities = [0, 0.5]
      stype_dict = {"row_sparse": RowSparseNDArray, "csr": CSRNDArray}
      shape = rand_shape_2d(dim0, dim1)
      for stype in stypes:
          for density in densities:
              a, _ = rand_sparse_ndarray(shape, stype, density)
              assert isinstance(a, stype_dict[stype])
              data = pkl.dumps(a)
              b = pkl.loads(data)
              assert isinstance(b, stype_dict[stype])
              assert same(a.asnumpy(), b.asnumpy())
  
imports: import pickle
  from mxnet.ndarray import NDArray
  import mxnet
  from mxnet.test_utils import *
  from common import random_seed
  from mxnet.base import mx_real_t
  from numpy.testing import assert_allclose
  import numpy.random
  import numpy
  import scipy.sparse
  from common import assertRaises, xfail_when_nonstandard_decimal_separator
  from mxnet.ndarray.sparse import RowSparseNDArray, CSRNDArray
  import pytest
label_desc: Use image node_id 24 for calling a global function with example usage: test_sparse_nd_pickle() without return types