Remove remaining uses of tf.reverse() and remove tf.reverse()

from API. On a subsequent commit tf.reverse() will be reintroduced but
taking a list of integer axes to reverse.
Change: 141325033

7 files changed, 41 insertions, 57 deletions

diff --git a/tensorflow/python/kernel_tests/array_ops_test.py b/tensorflow/python/kernel_tests/array_ops_test.py
index fb81f06472..4757558a9d 100644
--- a/tensorflow/python/kernel_tests/array_ops_test.py
+++ b/tensorflow/python/kernel_tests/array_ops_test.py
@@ -201,48 +201,6 @@ class OperatorShapeTest(test_util.TensorFlowTestCase):
     self.assertEqual(matrix_squeezed.get_shape(), (3))
 
 
-class ReverseTest(test_util.TensorFlowTestCase):
-
-  def testReverse0DimAuto(self):
-    x_np = 4
-    for use_gpu in [False, True]:
-      with self.test_session(use_gpu=use_gpu):
-        x_tf = array_ops.reverse(x_np, []).eval()
-        self.assertAllEqual(x_tf, x_np)
-
-  def _reverse1DimAuto(self, np_dtype):
-    x_np = np.array([1, 2, 3, 4, 5], dtype=np_dtype)
-
-    for use_gpu in [False, True]:
-      with self.test_session(use_gpu=use_gpu):
-        x_tf = array_ops.reverse(x_np, [True]).eval()
-        self.assertAllEqual(x_tf, np.asarray(x_np)[::-1])
-
-  def testReverse1DimAuto(self):
-    for dtype in [np.uint8, np.int8, np.int32, np.int64, np.bool, np.float16,
-                  np.float32, np.float64, np.complex64, np.complex128]:
-      self._reverse1DimAuto(dtype)
-
-  def testUnknownDims(self):
-    data_t = tf.placeholder(tf.float32)
-    dims_known_t = tf.placeholder(tf.bool, shape=[3])
-    reverse_known_t = tf.reverse(data_t, dims_known_t)
-    self.assertEqual(3, reverse_known_t.get_shape().ndims)
-
-    dims_unknown_t = tf.placeholder(tf.bool)
-    reverse_unknown_t = tf.reverse(data_t, dims_unknown_t)
-    self.assertIs(None, reverse_unknown_t.get_shape().ndims)
-
-    data_2d_t = tf.placeholder(tf.float32, shape=[None, None])
-    dims_2d_t = tf.placeholder(tf.bool, shape=[2])
-    reverse_2d_t = tf.reverse(data_2d_t, dims_2d_t)
-    self.assertEqual(2, reverse_2d_t.get_shape().ndims)
-
-    dims_3d_t = tf.placeholder(tf.bool, shape=[3])
-    with self.assertRaisesRegexp(ValueError, "must be rank 3"):
-      tf.reverse(data_2d_t, dims_3d_t)
-
-
 class ReverseV2Test(test_util.TensorFlowTestCase):
 
   def testReverse0DimAuto(self):
diff --git a/tensorflow/python/ops/array_grad.py b/tensorflow/python/ops/array_grad.py
index 7efdb281ae..e0d19bf5ea 100644
--- a/tensorflow/python/ops/array_grad.py
+++ b/tensorflow/python/ops/array_grad.py
@@ -474,7 +474,9 @@ def _ReverseSequenceGrad(op, grad):
 @ops.RegisterGradient("Reverse")
 def _ReverseGrad(op, grad):
   reverse_dims = op.inputs[1]
-  return array_ops.reverse(grad, reverse_dims), None
+  # pylint: disable=protected-access
+  return array_ops._reverse(grad, reverse_dims), None
+  # pylint: enable=protected-access
 
 
 @ops.RegisterGradient("ReverseV2")
diff --git a/tensorflow/python/ops/array_ops.py b/tensorflow/python/ops/array_ops.py
index b9f893aa07..2008cdefea 100644
--- a/tensorflow/python/ops/array_ops.py
+++ b/tensorflow/python/ops/array_ops.py
@@ -60,7 +60,6 @@ or join multiple tensors together.
 @@unstack
 @@unpack
 @@reverse_sequence
-@@reverse
 @@reverse_v2
 @@transpose
 @@extract_image_patches
diff --git a/tensorflow/python/ops/hidden_ops.txt b/tensorflow/python/ops/hidden_ops.txt
index a4aca2b838..4cec78ada2 100644
--- a/tensorflow/python/ops/hidden_ops.txt
+++ b/tensorflow/python/ops/hidden_ops.txt
@@ -15,6 +15,7 @@ Pack
 Pad
 Placeholder
 RefIdentity
+Reverse
 SpaceToBatch
 Split
 SplitV
diff --git a/tensorflow/python/ops/image_ops_impl.py b/tensorflow/python/ops/image_ops_impl.py
index 5397b68b00..639df5d845 100644
--- a/tensorflow/python/ops/image_ops_impl.py
+++ b/tensorflow/python/ops/image_ops_impl.py
@@ -24,6 +24,7 @@ import os
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import tensor_shape
 from tensorflow.python.framework import tensor_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import check_ops
@@ -158,6 +159,25 @@ def _CheckAtLeast3DImage(image):
                      image.get_shape())
 
 
+def fix_image_flip_shape(image, result):
+  """Set the shape to 3 dimensional if we don't know anything else.
+
+  Args:
+    image: original image size
+    result: flipped or transformed image
+
+  Returns:
+    An image whose shape is at least None,None,None.
+  """
+
+  image_shape = image.get_shape()
+  if image_shape == tensor_shape.unknown_shape():
+    result.set_shape([None, None, None])
+  else:
+    result.set_shape(image_shape)
+  return result
+
+
 def random_flip_up_down(image, seed=None):
   """Randomly flips an image vertically (upside down).
 
@@ -179,8 +199,10 @@ def random_flip_up_down(image, seed=None):
   image = ops.convert_to_tensor(image, name='image')
   _Check3DImage(image, require_static=False)
   uniform_random = random_ops.random_uniform([], 0, 1.0, seed=seed)
-  mirror = math_ops.less(array_ops.pack([uniform_random, 1.0, 1.0]), 0.5)
-  return array_ops.reverse(image, mirror)
+  mirror_cond = math_ops.less(uniform_random, .5)
+  stride = array_ops.where(mirror_cond, -1, 1)
+  result = image[::stride, :, :]
+  return fix_image_flip_shape(image, result)
 
 
 def random_flip_left_right(image, seed=None):
@@ -204,8 +226,10 @@ def random_flip_left_right(image, seed=None):
   image = ops.convert_to_tensor(image, name='image')
   _Check3DImage(image, require_static=False)
   uniform_random = random_ops.random_uniform([], 0, 1.0, seed=seed)
-  mirror = math_ops.less(array_ops.pack([1.0, uniform_random, 1.0]), 0.5)
-  return array_ops.reverse(image, mirror)
+  mirror_cond = math_ops.less(uniform_random, .5)
+  stride = array_ops.where(mirror_cond, -1, 1)
+  result = image[:, ::stride, :]
+  return fix_image_flip_shape(image, result)
 
 
 def flip_left_right(image):
@@ -227,7 +251,7 @@ def flip_left_right(image):
   """
   image = ops.convert_to_tensor(image, name='image')
   _Check3DImage(image, require_static=False)
-  return array_ops.reverse(image, [False, True, False])
+  return fix_image_flip_shape(image, image[:, ::-1, :])
 
 
 def flip_up_down(image):
@@ -249,7 +273,7 @@ def flip_up_down(image):
   """
   image = ops.convert_to_tensor(image, name='image')
   _Check3DImage(image, require_static=False)
-  return array_ops.reverse(image, [True, False, False])
+  return fix_image_flip_shape(image, array_ops.reverse_v2(image, [0]))
 
 
 def rot90(image, k=1, name=None):
@@ -271,13 +295,13 @@ def rot90(image, k=1, name=None):
     k = math_ops.mod(k, 4)
 
     def _rot90():
-      return array_ops.transpose(array_ops.reverse(image, [False, True, False]),
+      return array_ops.transpose(array_ops.reverse_v2(image, [1]),
                                  [1, 0, 2])
     def _rot180():
-      return array_ops.reverse(image, [True, True, False])
+      return array_ops.reverse_v2(image, [0, 1])
     def _rot270():
-      return array_ops.reverse(array_ops.transpose(image, [1, 0, 2]),
-                               [False, True, False])
+      return array_ops.reverse_v2(array_ops.transpose(image, [1, 0, 2]),
+                                  [1])
     cases = [(math_ops.equal(k, 1), _rot90),
              (math_ops.equal(k, 2), _rot180),
              (math_ops.equal(k, 3), _rot270)]
diff --git a/tensorflow/python/ops/math_grad.py b/tensorflow/python/ops/math_grad.py
index 9ba05f0a24..e4d42a4311 100644
--- a/tensorflow/python/ops/math_grad.py
+++ b/tensorflow/python/ops/math_grad.py
@@ -921,7 +921,7 @@ def _CastGrad(op, grad):
 def _FFTSizeForGrad(grad, rank):
   return math_ops.reduce_prod(
       array_ops.slice(
-          array_ops.reverse(array_ops.shape(grad), (True,)), (0,), (rank,)))
+          array_ops.reverse_v2(array_ops.shape(grad), [0]), (0,), (rank,)))
 
 
 @ops.RegisterGradient("FFT")
diff --git a/tensorflow/python/ops/nn_ops.py b/tensorflow/python/ops/nn_ops.py
index 666fb3f475..bb55249ff0 100644
--- a/tensorflow/python/ops/nn_ops.py
+++ b/tensorflow/python/ops/nn_ops.py
@@ -2077,8 +2077,8 @@ def erosion2d(value, kernel, strides, rates, padding, name=None):
   with ops.name_scope(name, "erosion2d", [value, kernel]) as name:
     # Reduce erosion to dilation by duality.
     return math_ops.neg(gen_nn_ops.dilation2d(input=math_ops.neg(value),
-                                              filter=array_ops.reverse(
-                                                  kernel, [True, True, False]),
+                                              filter=array_ops.reverse_v2(
+                                                  kernel, [0, 1]),
                                               strides=strides,
                                               rates=rates,
                                               padding=padding,