1 files changed, 109 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/reverse_sequence_op_test.py b/tensorflow/python/kernel_tests/reverse_sequence_op_test.py
new file mode 100644
index 0000000000..7cfbcd7946
--- /dev/null
+++ b/tensorflow/python/kernel_tests/reverse_sequence_op_test.py
@@ -0,0 +1,109 @@
+"""Tests for tensorflow.ops.reverse_sequence_op."""
+import tensorflow.python.platform
+
+import numpy as np
+import tensorflow as tf
+
+from tensorflow.python.kernel_tests import gradient_checker as gc
+
+
+class ReverseSequenceTest(tf.test.TestCase):
+
+  def _testReverseSequence(self, x, seq_dim, seq_lengths,
+                           truth, use_gpu=False, expected_err_re=None):
+    with self.test_session(use_gpu=use_gpu):
+      ans = tf.reverse_sequence(x,
+                                seq_dim=seq_dim,
+                                seq_lengths=seq_lengths)
+      if expected_err_re is None:
+        tf_ans = ans.eval()
+        self.assertAllClose(tf_ans, truth, atol=1e-10)
+        self.assertShapeEqual(truth, ans)
+      else:
+        with self.assertRaisesOpError(expected_err_re):
+          ans.eval()
+
+  def _testBothReverseSequence(self, x, seq_dim, seq_lengths,
+                               truth, expected_err_re=None):
+    self._testReverseSequence(x, seq_dim, seq_lengths,
+                              truth, True, expected_err_re)
+    self._testReverseSequence(x, seq_dim, seq_lengths,
+                              truth, False, expected_err_re)
+
+  def _testBasic(self, dtype):
+    x = np.asarray([
+        [[1, 2, 3, 4], [5, 6, 7, 8]],
+        [[9, 10, 11, 12], [13, 14, 15, 16]],
+        [[17, 18, 19, 20], [21, 22, 23, 24]]], dtype=dtype)
+    x = x.reshape(3, 2, 4, 1, 1)
+
+    # reverse dim 2 up to (0:3, none, 0:4) along dim=0
+    seq_dim = 2
+    seq_lengths = np.asarray([3, 0, 4], dtype=np.int64)
+
+    truth = np.asarray(
+        [[[3, 2, 1, 4], [7, 6, 5, 8]],  # reverse 0:3
+         [[9, 10, 11, 12], [13, 14, 15, 16]],  # reverse none
+         [[20, 19, 18, 17], [24, 23, 22, 21]]],  # reverse 0:4 (all)
+        dtype=dtype)
+    truth = truth.reshape(3, 2, 4, 1, 1)
+    self._testBothReverseSequence(x, seq_dim, seq_lengths, truth)
+
+  def testFloatBasic(self):
+    self._testBasic(np.float32)
+
+  def testDoubleBasic(self):
+    self._testBasic(np.float64)
+
+  def testInt32Basic(self):
+    self._testBasic(np.int32)
+
+  def testInt64Basic(self):
+    self._testBasic(np.int64)
+
+  def testSComplexBasic(self):
+    self._testBasic(np.complex64)
+
+  def testFloatReverseSequenceGrad(self):
+    x = np.asarray([
+        [[1, 2, 3, 4], [5, 6, 7, 8]],
+        [[9, 10, 11, 12], [13, 14, 15, 16]],
+        [[17, 18, 19, 20], [21, 22, 23, 24]]], dtype=np.float)
+    x = x.reshape(3, 2, 4, 1, 1)
+
+    # reverse dim 2 up to (0:3, none, 0:4) along dim=0
+    seq_dim = 2
+    seq_lengths = np.asarray([3, 0, 4], dtype=np.int64)
+
+    with self.test_session():
+      input_t = tf.constant(x, shape=x.shape)
+      seq_lengths_t = tf.constant(seq_lengths, shape=seq_lengths.shape)
+      reverse_sequence_out = tf.reverse_sequence(input_t,
+                                                 seq_dim=seq_dim,
+                                                 seq_lengths=seq_lengths_t)
+      err = gc.ComputeGradientError(input_t,
+                                    x.shape,
+                                    reverse_sequence_out,
+                                    x.shape,
+                                    x_init_value=x)
+    print "ReverseSequence gradient error = %g" % err
+    self.assertLess(err, 1e-8)
+
+  def testShapeFunctionEdgeCases(self):
+    # Batch size mismatched between input and seq_lengths.
+    with self.assertRaises(ValueError):
+      tf.reverse_sequence(
+          tf.placeholder(tf.float32, shape=(32, 2, 3)),
+          seq_lengths=tf.placeholder(tf.int64, shape=(33,)),
+          seq_dim=3)
+
+    # seq_dim out of bounds.
+    with self.assertRaisesRegexp(ValueError, "seq_dim must be < input.dims()"):
+      tf.reverse_sequence(
+          tf.placeholder(tf.float32, shape=(32, 2, 3)),
+          seq_lengths=tf.placeholder(tf.int64, shape=(32,)),
+          seq_dim=3)
+
+
+if __name__ == "__main__":
+  tf.test.main()