code: def get_result_type_with_scalar(call, dflt_stype):
      """Try to infer result storage type when operating a sparse matrices and a scalar"""
      if call is not None and dflt_stype != "default":
          zero = np.zeros(([1]))
          result = call(zero, 5)
  
          if not almost_equal(result, zero, equal_nan=True):
              expected_result_type = "default"
          else:
              if dflt_stype is not None:
                  expected_result_type = dflt_stype
              else:
                  expected_result_type = "default"
      else:
          expected_result_type = "default"
  
      return expected_result_type
  
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 3 for calling a global function with example usage: get_result_type_with_scalar(call, dflt_stype) and returns: expected_result_type