code: def test_sparse_nd_random():
      """test sparse random operator on cpu"""
      # gpu random operator doesn't use fixed seed
      if default_device().device_type is "gpu":
          return
      shape = (100, 100)
      fns = [
          mx.nd.random.uniform,
          mx.nd.random.normal,
          mx.nd.random.gamma,
      ]
      for fn in fns:
          rsp_out = mx.nd.zeros(shape=shape, stype="row_sparse")
          dns_out = mx.nd.zeros(shape=shape, stype="default")
          with random_seed(0):
              fn(shape=shape, out=dns_out)
          with random_seed(0):
              fn(shape=shape, out=rsp_out)
          assert_almost_equal(dns_out.asnumpy(), rsp_out.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 21 for calling a global function with example usage: test_sparse_nd_random() without return types