Rename more argument names to be consistent with NumPy.

Create temporary dummy arguments with old names at the end in preparation for
deprecation.
Change: 140675930

1 files changed, 57 insertions, 39 deletions

diff --git a/tensorflow/python/kernel_tests/reverse_sequence_op_test.py b/tensorflow/python/kernel_tests/reverse_sequence_op_test.py
index fbfad8327e..ca6b198fa8 100644
--- a/tensorflow/python/kernel_tests/reverse_sequence_op_test.py
+++ b/tensorflow/python/kernel_tests/reverse_sequence_op_test.py
@@ -25,13 +25,17 @@ import tensorflow as tf
 
 class ReverseSequenceTest(tf.test.TestCase):
 
-  def _testReverseSequence(self, x, batch_dim, seq_dim, seq_lengths,
-                           truth, use_gpu=False, expected_err_re=None):
+  def _testReverseSequence(self,
+                           x,
+                           batch_axis,
+                           seq_axis,
+                           seq_lengths,
+                           truth,
+                           use_gpu=False,
+                           expected_err_re=None):
     with self.test_session(use_gpu=use_gpu):
-      ans = tf.reverse_sequence(x,
-                                batch_dim=batch_dim,
-                                seq_dim=seq_dim,
-                                seq_lengths=seq_lengths)
+      ans = tf.reverse_sequence(
+          x, batch_axis=batch_axis, seq_axis=seq_axis, seq_lengths=seq_lengths)
       if expected_err_re is None:
         tf_ans = ans.eval()
         self.assertAllClose(tf_ans, truth, atol=1e-10)
@@ -40,12 +44,17 @@ class ReverseSequenceTest(tf.test.TestCase):
         with self.assertRaisesOpError(expected_err_re):
           ans.eval()
 
-  def _testBothReverseSequence(self, x, batch_dim, seq_dim, seq_lengths,
-                               truth, expected_err_re=None):
-    self._testReverseSequence(x, batch_dim, seq_dim, seq_lengths,
-                              truth, True, expected_err_re)
-    self._testReverseSequence(x, batch_dim, seq_dim, seq_lengths,
-                              truth, False, expected_err_re)
+  def _testBothReverseSequence(self,
+                               x,
+                               batch_axis,
+                               seq_axis,
+                               seq_lengths,
+                               truth,
+                               expected_err_re=None):
+    self._testReverseSequence(x, batch_axis, seq_axis, seq_lengths, truth, True,
+                              expected_err_re)
+    self._testReverseSequence(x, batch_axis, seq_axis, seq_lengths, truth,
+                              False, expected_err_re)
 
   def _testBasic(self, dtype, len_dtype=np.int64):
     x = np.asarray([
@@ -66,9 +75,9 @@ class ReverseSequenceTest(tf.test.TestCase):
     truth_orig = truth_orig.reshape(3, 2, 4, 1, 1)
     truth = truth_orig.transpose([2, 1, 0, 3, 4])  # permute axes 0 <=> 2
 
-    seq_dim = 0    # permute seq_dim and batch_dim (originally 2 and 0, resp.)
-    batch_dim = 2
-    self._testBothReverseSequence(x, batch_dim, seq_dim, seq_lengths, truth)
+    seq_axis = 0  # permute seq_axis and batch_axis (originally 2 and 0, resp.)
+    batch_axis = 2
+    self._testBothReverseSequence(x, batch_axis, seq_axis, seq_lengths, truth)
 
   def testSeqLengthInt32(self):
     self._testBasic(np.float32, np.int32)
@@ -100,17 +109,18 @@ class ReverseSequenceTest(tf.test.TestCase):
     x = x.transpose([2, 1, 0, 3, 4])  # transpose axes 0 <=> 2
 
     # reverse dim 0 up to (0:3, none, 0:4) along dim=2
-    seq_dim = 0
-    batch_dim = 2
+    seq_axis = 0
+    batch_axis = 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,
-                                                 batch_dim=batch_dim,
-                                                 seq_dim=seq_dim,
-                                                 seq_lengths=seq_lengths_t)
+      reverse_sequence_out = tf.reverse_sequence(
+          input_t,
+          batch_axis=batch_axis,
+          seq_axis=seq_axis,
+          seq_lengths=seq_lengths_t)
       err = tf.test.compute_gradient_error(input_t,
                                            x.shape,
                                            reverse_sequence_out,
@@ -121,41 +131,49 @@ class ReverseSequenceTest(tf.test.TestCase):
 
   def testShapeFunctionEdgeCases(self):
     t = tf.reverse_sequence(
-        tf.placeholder(tf.float32, shape=None),
-        seq_lengths=tf.placeholder(tf.int64, shape=(32,)),
-        batch_dim=0, seq_dim=1)
+        tf.placeholder(
+            tf.float32, shape=None),
+        seq_lengths=tf.placeholder(
+            tf.int64, shape=(32,)),
+        batch_axis=0,
+        seq_axis=1)
     self.assertIs(t.get_shape().ndims, None)
 
     # 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)
+          tf.placeholder(
+              tf.float32, shape=(32, 2, 3)),
+          seq_lengths=tf.placeholder(
+              tf.int64, shape=(33,)),
+          seq_axis=3)
 
-    # seq_dim out of bounds.
+    # seq_axis out of bounds.
     with self.assertRaisesRegexp(ValueError, "seq_dim must be < input rank"):
       tf.reverse_sequence(
-          tf.placeholder(tf.float32, shape=(32, 2, 3)),
-          seq_lengths=tf.placeholder(tf.int64, shape=(32,)),
-          seq_dim=3)
+          tf.placeholder(
+              tf.float32, shape=(32, 2, 3)),
+          seq_lengths=tf.placeholder(
+              tf.int64, shape=(32,)),
+          seq_axis=3)
 
-    # batch_dim out of bounds.
+    # batch_axis out of bounds.
     with self.assertRaisesRegexp(
         ValueError, "batch_dim must be < input rank"):
       tf.reverse_sequence(
-          tf.placeholder(tf.float32, shape=(32, 2, 3)),
-          seq_lengths=tf.placeholder(tf.int64, shape=(32,)),
-          seq_dim=0,
-          batch_dim=3)
+          tf.placeholder(
+              tf.float32, shape=(32, 2, 3)),
+          seq_lengths=tf.placeholder(
+              tf.int64, shape=(32,)),
+          seq_axis=0,
+          batch_axis=3)
 
     with self.test_session():
       inputs = tf.placeholder(tf.float32, shape=(32, 2, 3))
       seq_lengths = tf.placeholder(tf.int64, shape=(32,))
       output = tf.reverse_sequence(
-          inputs,
-          seq_lengths=seq_lengths,
-          seq_dim=0)  # batch_dim default is 0
+          inputs, seq_lengths=seq_lengths,
+          seq_axis=0)  # batch_axis default is 0
       with self.assertRaisesOpError("batch_dim == seq_dim"):
         output.eval(feed_dict={inputs: np.random.rand(32, 2, 3),
                                seq_lengths: xrange(32)})