code: def convert_sum(node, **kwargs):
      """Map MXNet's sum operator attributes to onnx's ReduceSum operator
      and return the created node.
      """
      from onnx.helper import make_node
  
      name, input_nodes, attrs = get_inputs(node, kwargs)
  
      mx_axis = attrs.get("axis", None)
      axes = (
          convert_string_to_list(str(mx_axis))
          if mx_axis not in [None, "None"]
          else None
      )
  
      keepdims = get_boolean_attribute_value(attrs, "keepdims")
  
      if axes:
          create_tensor(axes, name + "_axes", kwargs["initializer"])
          input_nodes.append(name + "_axes")
          node = make_node(
              "ReduceSum",
              inputs=input_nodes,
              outputs=[name],
              keepdims=keepdims,
              name=name,
          )
          return [node]
      else:
          create_tensor([1], name + "_1", kwargs["initializer"])
          nodes = [
              onnx.helper.make_node(
                  "ReduceSum",
                  inputs=input_nodes,
                  outputs=[name],
                  keepdims=keepdims,
              )
          ]
      return nodes
  
imports: import re
  import logging
  import numpy
  from .._export_onnx import MXNetGraph
label_desc: Use image node_id 24 for calling a global function with example usage: convert_sum(node) and returns: nodes, list