text: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  
  # Copyright 2021 Tianmian Tech. All Rights Reserved.
  # 
  # Licensed 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.
  
  # Copyright 2019 The FATE Authors. All Rights Reserved.
  # 
  # Licensed 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.
  
  
  
  import unittest
  
  import numpy as np
  
  from kernel.optimizer import activation
  
  
  class TestConvergeFunction(unittest.TestCase):
      def test_numeric_stability(self):
          x_list = np.linspace(-709, 709, 10000)
  
          # Original function
          # a = 1. / (1. + np.exp(-x))
          for x in x_list:
              a1 = 1. / (1. + np.exp(-x))
              a2 = activation.sigmoid(x)
              self.assertTrue(np.abs(a1 - a2) < 1e-5)
  
  
  if __name__ == '__main__':
      unittest.main()
  