code: def test_sparse_nd_copy():
      def check_sparse_nd_copy(from_stype, to_stype, shape):
          from_nd = rand_ndarray(shape, from_stype)
          # copy to ctx
          to_ctx = from_nd.copyto(default_device())
          # copy to stype
          to_nd = rand_ndarray(shape, to_stype)
          to_nd = from_nd.copyto(to_nd)
          assert (
              np.sum(np.abs(from_nd.asnumpy() != to_ctx.asnumpy()))
              == 0.0
          )
          assert (
              np.sum(np.abs(from_nd.asnumpy() != to_nd.asnumpy()))
              == 0.0
          )
  
      shape = rand_shape_2d()
      shape_3d = rand_shape_3d()
      stypes = ["row_sparse", "csr"]
      for stype in stypes:
          check_sparse_nd_copy(stype, "default", shape)
          check_sparse_nd_copy("default", stype, shape)
      check_sparse_nd_copy("row_sparse", "row_sparse", shape_3d)
      check_sparse_nd_copy("row_sparse", "default", shape_3d)
      check_sparse_nd_copy("default", "row_sparse", shape_3d)
  
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 3 for calling a global function with example usage: test_sparse_nd_copy() without return types