text: # Copyright 2015 The TensorFlow 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.
  # ==============================================================================
  """Tests for IdentityOp."""
  
  import numpy as np
  
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.platform import test
  
  
  class IdentityOpTest(test.TestCase):
  
    def testInt32_6(self):
      value = self.evaluate(array_ops.identity([1, 2, 3, 4, 5, 6]))
      self.assertAllEqual(np.array([1, 2, 3, 4, 5, 6]), value)
  
    def testInt32_2_3(self):
      inp = constant_op.constant([10, 20, 30, 40, 50, 60], shape=[2, 3])
      value = self.evaluate(array_ops.identity(inp))
      self.assertAllEqual(np.array([[10, 20, 30], [40, 50, 60]]), value)
  
    def testString(self):
      source = [b"A", b"b", b"C", b"d", b"E", b"f"]
      value = self.evaluate(array_ops.identity(source))
      self.assertAllEqual(source, value)
  
    def testIdentityShape(self):
      with self.cached_session():
        shape = [2, 3]
        array_2x3 = [[1, 2, 3], [6, 5, 4]]
        tensor = constant_op.constant(array_2x3)
        self.assertEqual(shape, tensor.get_shape())
        self.assertEqual(shape, array_ops.identity(tensor).get_shape())
        self.assertEqual(shape, array_ops.identity(array_2x3).get_shape())
        self.assertEqual(shape,
                         array_ops.identity(np.array(array_2x3)).get_shape())
  
    def testCompositeTensor(self):
      original = sparse_tensor.SparseTensor([[3]], [1.0], [100])
      copied = array_ops.identity(original)
      self.assertAllEqual(original.indices, copied.indices)
      self.assertAllEqual(original.values, copied.values)
      self.assertAllEqual(original.dense_shape, copied.dense_shape)
  
  
  if __name__ == "__main__":
    test.main()
  