old_contents: #   Copyright (c) 2018 PaddlePaddle 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 op_test import OpTest
  
  
  class TestSplitOp(OpTest):
      def setUp(self):
          self.op_type = "split"
          axis = 1
          x = np.random.random((4, 5, 6)).astype('float32')
          out = np.split(x, [2, 3], axis)
          self.inputs = {'X': x}
          self.attrs = {'axis': axis, 'sections': [2, 1, 2]}
          self.outputs = {'Out': [('out%d' % i, out[i]) \
              for i in xrange(len(out))]}
  
      def test_check_output(self):
          self.check_output()
  
      def test_check_grad(self):
          self.check_grad(['X'], ['out0', 'out1', 'out2'])
  
  
  if __name__ == '__main__':
      unittest.main()
  
new_contents: #   Copyright (c) 2018 PaddlePaddle 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 op_test import OpTest
  
  
  class TestSplitOp(OpTest):
      def setUp(self):
          axis = 1
          x = np.random.random((4, 5, 6)).astype('float32')
          out = np.split(x, [2, 3], axis)
          self.inputs = {'X': x}
          self.attrs = {'axis': axis, 'sections': [2, 1, 2]}
          self.outputs = {'Out': [('out%d' % i, out[i]) \
              for i in xrange(len(out))]}
  
      def _set_op_type(self):
          self.op_type = "split"
  
      def test_check_output(self):
          self.check_output()
  
      def test_check_grad(self):
          self.check_grad(['X'], ['out0', 'out1', 'out2'])
  
  
  class TestSplitByrefOp(OpTest):
      def _set_op_type(self):
          self.op_type = "split_byref"
  
  
  if __name__ == '__main__':
      unittest.main()
  
subject: add split by ref test