text: 
  # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
  # distributed with this work for additional information
  # regarding copyright ownership.  The ASF licenses this file
  # to you under the Apache License, Version 2.0 (the
  # "License"); you may not use this file except in compliance
  # with the License.  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing,
  # software distributed under the License is distributed on an
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  # KIND, either express or implied.  See the License for the
  # specific language governing permissions and limitations
  # under the License.
  # pylint: disable=invalid-name, unused-argument
  #
  # This file is part of DNN compiler maintained at 
  # https://github.com/ai-techsystems/dnnCompiler
  
  
  import os, sys
  
  import numpy as np
  separator = os.path.sep
  
  from onnx import *
  sys.path.append(".."+separator+".."+separator+".."+separator+".."+separator+"python/parser")
  from onnx_parser import *
  
  op_name = 'Softplus'
  
  inputs = [helper.make_tensor_value_info("x",TensorProto.FLOAT,(2,3,4))]
  outputs = [helper.make_tensor_value_info("y",TensorProto.FLOAT,(2,3,4))]
  nodes = []
  nodes.append(helper.make_node("Softplus",["x"],["y"]))
  graph = helper.make_graph(nodes, op_name+"_graph", inputs, outputs)
  opset = (OperatorSetIdProto(version=11),)
  model = helper.make_model(graph, opset_imports=opset)
  onnx.checker.check_model(model)
  t_prefix = ".." + separator + "testcases" + separator + op_name + separator + op_name
  g_prefix = ".." + separator + "gold_files" + separator + op_name
  onnx.save(model, t_prefix+".onnx")
  parse(t_prefix+".onnx", g_prefix+".sym", onnx_output_file=t_prefix+".txt")
  