Fix sparse_ops to accept SparseTensorValue anywhere SparseTensor is allowed.

Change: 132478322

1 files changed, 22 insertions, 0 deletions

diff --git a/tensorflow/python/kernel_tests/sparse_reorder_op_test.py b/tensorflow/python/kernel_tests/sparse_reorder_op_test.py
index e9e58f8935..dd5f9a0941 100644
--- a/tensorflow/python/kernel_tests/sparse_reorder_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_reorder_op_test.py
@@ -46,6 +46,16 @@ class SparseReorderTest(tf.test.TestCase):
 
   def testAlreadyInOrder(self):
     with self.test_session(use_gpu=False) as sess:
+      input_val = self._SparseTensorValue_5x6(np.arange(6))
+      sp_output = tf.sparse_reorder(input_val)
+
+      output_val = sess.run(sp_output)
+      self.assertAllEqual(output_val.indices, input_val.indices)
+      self.assertAllEqual(output_val.values, input_val.values)
+      self.assertAllEqual(output_val.shape, input_val.shape)
+
+  def testFeedAlreadyInOrder(self):
+    with self.test_session(use_gpu=False) as sess:
       sp_input = self._SparseTensorPlaceholder()
       input_val = self._SparseTensorValue_5x6(np.arange(6))
       sp_output = tf.sparse_reorder(sp_input)
@@ -59,6 +69,18 @@ class SparseReorderTest(tf.test.TestCase):
     expected_output_val = self._SparseTensorValue_5x6(np.arange(6))
     with self.test_session(use_gpu=False) as sess:
       for _ in range(5):  # To test various random permutations
+        input_val = self._SparseTensorValue_5x6(np.random.permutation(6))
+        sp_output = tf.sparse_reorder(input_val)
+
+        output_val = sess.run(sp_output)
+        self.assertAllEqual(output_val.indices, expected_output_val.indices)
+        self.assertAllEqual(output_val.values, expected_output_val.values)
+        self.assertAllEqual(output_val.shape, expected_output_val.shape)
+
+  def testFeedOutOfOrder(self):
+    expected_output_val = self._SparseTensorValue_5x6(np.arange(6))
+    with self.test_session(use_gpu=False) as sess:
+      for _ in range(5):  # To test various random permutations
         sp_input = self._SparseTensorPlaceholder()
         input_val = self._SparseTensorValue_5x6(np.random.permutation(6))
         sp_output = tf.sparse_reorder(sp_input)