original_docstring: Map MXNet's add_n operator attributes to onnx's Sum operator
      and return the created node.
      
docstring: Map MXNet's add_n operator attributes to onnx's Sum operator
  and return the created node.
docstring_tokens: Map MXNet ' s add_n operator attributes to onnx ' s Sum operator and return the created node .
code: def convert_addn(node, **kwargs):
      """Map MXNet's add_n operator attributes to onnx's Sum operator
      and return the created node.
      """
      onnx = import_onnx_modules()
      name = node["name"]
      proc_nodes = kwargs["proc_nodes"]
      inputs = node["inputs"]
  
      input_list = []
      for input_val in inputs:
          input_list.append(proc_nodes[kwargs["index_lookup"][input_val[0]]].name)
  
      sum_node = onnx.helper.make_node(
          "Sum",
          input_list,
          [name],
          name=name
      )
      return [sum_node]
code_tokens: def convert_addn ( node , ** kwargs ) : onnx = import_onnx_modules ( ) name = node [ "name" ] proc_nodes = kwargs [ "proc_nodes" ] inputs = node [ "inputs" ] input_list = [ ] for input_val in inputs : input_list . append ( proc_nodes [ kwargs [ "index_lookup" ] [ input_val [ 0 ] ] ] . name ) sum_node = onnx . helper . make_node ( "Sum" , input_list , [ name ] , name = name ) return [ sum_node ]
short_docstring: Map MXNet's add_n operator attributes to onnx's Sum operator
  and return the created node.
short_docstring_tokens: Map MXNet ' s add_n operator attributes to onnx ' s Sum operator and return the created node .
comment: """Map MXNet's add_n operator attributes to onnx's Sum operator
      and return the created node.
      """