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 tensorflow.ops.tf.gather."""
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import numpy as np
  import tensorflow as tf
  
  
  class GatherTest(tf.test.TestCase):
    use_gpu = False
  
    def testScalar1D(self):
      with self.test_session(use_gpu=self.use_gpu):
        params = tf.constant([0, 1, 2, 3, 7, 5])
        indices = tf.constant(4)
        gather_t = tf.gather(params, indices)
        gather_val = gather_t.eval()
      self.assertAllEqual(7, gather_val)
      self.assertEqual([], gather_t.get_shape())
  
    def testScalar2D(self):
      with self.test_session(use_gpu=self.use_gpu):
        params = tf.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8],
                                       [9, 10, 11], [12, 13, 14]])
        indices = tf.constant(2)
        gather_t = tf.gather(params, indices)
        gather_val = gather_t.eval()
      self.assertAllEqual([6, 7, 8], gather_val)
      self.assertEqual([3], gather_t.get_shape())
  
    def testSimpleTwoD32(self):
      with self.test_session(use_gpu=self.use_gpu):
        params = tf.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8],
                                       [9, 10, 11], [12, 13, 14]])
        indices = tf.constant([0, 4, 0, 2])
        gather_t = tf.gather(params, indices)
        gather_val = gather_t.eval()
      self.assertAllEqual([[0, 1, 2], [12, 13, 14], [0, 1, 2], [6, 7, 8]],
                          gather_val)
      self.assertEqual([4, 3], gather_t.get_shape())
  
    def testHigherRank(self):
      np.random.seed(1)
      shape = (4, 3, 2)
      params = np.random.randn(*shape)
      indices = np.random.randint(shape[0], size=15).reshape(3, 5)
      with self.test_session(use_gpu=self.use_gpu):
        tf_params = tf.constant(params)
        tf_indices = tf.constant(indices)
        gather = tf.gather(tf_params, tf_indices)
        self.assertAllEqual(params[indices], gather.eval())
        self.assertEqual(indices.shape + params.shape[1:], gather.get_shape())
        # Test gradients
        gather_grad = np.random.randn(*gather.get_shape().as_list())
        params_grad, indices_grad = tf.gradients(gather, [tf_params, tf_indices],
                                                 gather_grad)
        self.assertEqual(indices_grad, None)
        self.assertEqual(type(params_grad), tf.IndexedSlices)
        params_grad = tf.convert_to_tensor(params_grad)
        correct_params_grad = np.zeros(shape)
        for i, g in zip(indices.ravel(), gather_grad.reshape((15,) + shape[1:])):
          correct_params_grad[i] += g
        self.assertAllClose(correct_params_grad, params_grad.eval())
  
    def testUnknownIndices(self):
      params = tf.constant([[0, 1, 2]])
      indices = tf.placeholder(tf.int32)
      gather_t = tf.gather(params, indices)
      self.assertEqual(None, gather_t.get_shape())
  
    def testBadIndices(self):
      with self.test_session(use_gpu=False):
        params = [0, 1, 2]
        indices = [[7]]
        gather = tf.gather(params, indices)
        with self.assertRaisesOpError(r"indices\[0,0\] = 7 is not in \[0, 3\)"):
          gather.eval()
  
    def testEmptySlices(self):
      with self.test_session(use_gpu=self.use_gpu):
        for dtype in np.float32, np.float64:
          for itype in np.int32, np.int64:
            params = np.zeros((7, 0), dtype=dtype)
            indices = np.array([3, 4], dtype=itype)
            gather = tf.gather(params, indices)
            self.assertAllEqual(gather.eval(), np.zeros((2, 0)))
  
  
  class GatherGpuTest(GatherTest):
    use_gpu = True
  
  
  if __name__ == "__main__":
    tf.test.main()
  