code: def convert_logistic_regression_output(node, **kwargs):
      
      name = node["name"]
      input1_idx = kwargs["index_lookup"][node["inputs"][0][0]]
      input1 = kwargs["proc_nodes"][input1_idx]
      sigmoid_node = onnx.helper.make_node(
          "Sigmoid",
          [input1.name],
          [name],
          name=name
      )
      return [sigmoid_node]
docs: Map MXNet's SoftmaxOutput operator attributes to onnx's Softmax operator
      and return the created node.