code: def test_sparse_quadratic_function():
      def f(x, a, b, c):
          return a * x**2 + b * x + c
  
      def check_sparse_quadratic_function(a, b, c, expected_stype):
          # check forward and compare the result with dense op
          ndim = 2
          shape = rand_shape_nd(ndim, 5)
          data = rand_ndarray(shape=shape, stype="csr")
          data_np = data.asnumpy()
          expected = f(data_np, a, b, c)
          output = mx.nd.contrib.quadratic(data, a=a, b=b, c=c)
          assert output.stype == expected_stype
          assert_almost_equal(output.asnumpy(), expected)
  
      a = np.random.random_sample()
      b = np.random.random_sample()
      check_sparse_quadratic_function(a, b, 0.0, "csr")
      check_sparse_quadratic_function(a, b, 1.0, "default")
  
imports: from mxnet.test_utils import *
  from mxnet.base import MXNetError
  import pytest
  from common import assertRaises
  import random
  import warnings
label_desc: Use image node_id 36 for calling a global function with example usage: test_sparse_quadratic_function() and returns: unknown