code: def test_sparse_nd_fluent():
      def check_fluent_regular(
          stype, func, kwargs, shape=(5, 17), equal_nan=False
      ):
          with mx.name.NameManager():
              data = mx.nd.random_uniform(
                  shape=shape, ctx=default_device()
              ).tostype(stype)
              regular = getattr(mx.ndarray, func)(data, **kwargs)
              fluent = getattr(data, func)(**kwargs)
              if isinstance(regular, list):
                  for r, f in zip(regular, fluent):
                      assert almost_equal(
                          r.asnumpy(), f.asnumpy(), equal_nan=equal_nan
                      )
              else:
                  assert almost_equal(
                      regular.asnumpy(),
                      fluent.asnumpy(),
                      equal_nan=equal_nan,
                  )
  
      all_funcs = [
          "zeros_like",
          "square",
          "round",
          "rint",
          "fix",
          "floor",
          "ceil",
          "trunc",
          "abs",
          "sign",
          "sin",
          "degrees",
          "radians",
          "expm1",
      ]
      for func in all_funcs:
          check_fluent_regular("csr", func, {})
          check_fluent_regular("row_sparse", func, {})
  
      all_funcs = [
          "arcsin",
          "arctan",
          "tan",
          "sinh",
          "tanh",
          "arcsinh",
          "arctanh",
          "log1p",
          "sqrt",
          "relu",
      ]
      for func in all_funcs:
          check_fluent_regular("csr", func, {}, equal_nan=True)
          check_fluent_regular("row_sparse", func, {}, equal_nan=True)
  
      check_fluent_regular(
          "csr",
          "slice",
          {"begin": (2, 5), "end": (4, 7)},
          shape=(5, 17),
      )
      check_fluent_regular(
          "row_sparse", "clip", {"a_min": -0.25, "a_max": 0.75}
      )
      check_fluent_regular(
          "csr", "clip", {"a_min": -0.25, "a_max": 0.75}
      )
  
      for func in ["sum", "mean", "norm"]:
          check_fluent_regular("csr", func, {"axis": 0})
  
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 35 for calling a global function with example usage: test_sparse_nd_fluent() without return types