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 common; # DNNC path setup
  
  import deepC.dnnc as dc
  import numpy as np
  import unittest
  
  # warning given if np_a contain nan values.negative values inside the log, which gives nan with real numbers.
  
  class LogTest(unittest.TestCase):
      def setUp(self):
          self.len = 24
          self.np_a = np.random.randint(low=2,high=10000,size=self.len)
          self.dc_a = dc.array(list(self.np_a));
  
      def test_Log1D (self):
          npr = np.log(self.np_a)
          dcr = dc.log(self.dc_a)
          np.testing.assert_allclose(npr, np.array(dcr.data()).astype(np.float32),
                  rtol=1e-3, atol=1e-3)
  
      def test_Log2D (self):
          np_a = np.reshape(self.np_a, (6,4))
          dc_a = dc.reshape(self.dc_a, (6,4));
          npr = np.log(np_a)
          dcr = dc.log(dc_a);
          np.testing.assert_allclose(npr.flatten(), np.array(dcr.data()).astype(np.float32),
                  rtol=1e-3, atol=1e-3)
  
      def test_Log3D (self):
          np_a = np.reshape(self.np_a, (2,4,3))
          dc_a = dc.reshape(self.dc_a, (2,4,3));
          npr = np.log(np_a)
          dcr = dc.log(dc_a);
  
          np.testing.assert_allclose(npr.flatten(), np.array(dcr.data()).astype(np.float32),
                  rtol=1e-3, atol=1e-3)
  
      def test_Log4D (self):
          np_a = np.reshape(self.np_a, (2,2,2,3))
          dc_a = dc.reshape(self.dc_a, (2,2,2,3));
          npr = np.log(np_a)
          dcr = dc.log(dc_a);
          np.testing.assert_allclose(npr.flatten(), np.array(dcr.data()).astype(np.float32),
                  rtol=1e-3, atol=1e-3)
  
  if __name__ == '__main__':
      unittest.main()
      
  