Merge changes from github.

PiperOrigin-RevId: 194031845

1 files changed, 47 insertions, 8 deletions

diff --git a/tensorflow/python/kernel_tests/manip_ops_test.py b/tensorflow/python/kernel_tests/manip_ops_test.py
index b8200ac0cb..f31426713c 100644
--- a/tensorflow/python/kernel_tests/manip_ops_test.py
+++ b/tensorflow/python/kernel_tests/manip_ops_test.py
@@ -20,8 +20,10 @@ from __future__ import print_function
 import numpy as np
 
 from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import errors_impl
 from tensorflow.python.framework import test_util
+from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import gradient_checker
 from tensorflow.python.ops import manip_ops
 from tensorflow.python.platform import test as test_lib
@@ -88,41 +90,78 @@ class RollTest(test_util.TensorFlowTestCase):
         x = np.random.rand(3, 2, 1, 1).astype(t)
         self._testAll(x + 1j * x, [2, 1, 1, 0], [0, 3, 1, 2])
 
+  def testNegativeAxis(self):
+    self._testAll(np.random.randint(-100, 100, (5)).astype(np.int32), 3, -1)
+    self._testAll(np.random.randint(-100, 100, (4, 4)).astype(np.int32), 3, -2)
+    # Make sure negative axis shoudl be 0 <= axis + dims < dims
+    with self.test_session():
+      with self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
+                                   "is out of range"):
+        manip_ops.roll(np.random.randint(-100, 100, (4, 4)).astype(np.int32),
+                       3, -10).eval()
+
+  def testInvalidInputShape(self):
+    # The input should be 1-D or higher, checked in shape function.
+    with self.assertRaisesRegexp(
+        ValueError, "Shape must be at least rank 1 but is rank 0"):
+      manip_ops.roll(7, 1, 0)
+
   def testRollInputMustVectorHigherRaises(self):
-    tensor = 7
+    # The input should be 1-D or higher, checked in kernel.
+    tensor = array_ops.placeholder(dtype=dtypes.int32)
     shift = 1
     axis = 0
     with self.test_session():
       with self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
                                    "input must be 1-D or higher"):
-        manip_ops.roll(tensor, shift, axis).eval()
+        manip_ops.roll(tensor, shift, axis).eval(feed_dict={tensor: 7})
+
+  def testInvalidAxisShape(self):
+    # The axis should be a scalar or 1-D, checked in shape function.
+    with self.assertRaisesRegexp(
+        ValueError, "Shape must be at most rank 1 but is rank 2"):
+      manip_ops.roll([[1, 2], [3, 4]], 1, [[0, 1]])
 
   def testRollAxisMustBeScalarOrVectorRaises(self):
+    # The axis should be a scalar or 1-D, checked in kernel.
     tensor = [[1, 2], [3, 4]]
     shift = 1
-    axis = [[0, 1]]
+    axis = array_ops.placeholder(dtype=dtypes.int32)
     with self.test_session():
       with self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
                                    "axis must be a scalar or a 1-D vector"):
-        manip_ops.roll(tensor, shift, axis).eval()
+        manip_ops.roll(tensor, shift, axis).eval(feed_dict={axis: [[0, 1]]})
+
+  def testInvalidShiftShape(self):
+    # The shift should be a scalar or 1-D, checked in shape function.
+    with self.assertRaisesRegexp(
+        ValueError, "Shape must be at most rank 1 but is rank 2"):
+      manip_ops.roll([[1, 2], [3, 4]], [[0, 1]], 1)
 
   def testRollShiftMustBeScalarOrVectorRaises(self):
+    # The shift should be a scalar or 1-D, checked in kernel.
     tensor = [[1, 2], [3, 4]]
-    shift = [[0, 1]]
+    shift = array_ops.placeholder(dtype=dtypes.int32)
     axis = 1
     with self.test_session():
       with self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
                                    "shift must be a scalar or a 1-D vector"):
-        manip_ops.roll(tensor, shift, axis).eval()
+        manip_ops.roll(tensor, shift, axis).eval(feed_dict={shift: [[0, 1]]})
+
+  def testInvalidShiftAndAxisNotEqualShape(self):
+    # The shift and axis must be same size, checked in shape function.
+    with self.assertRaisesRegexp(ValueError, "both shapes must be equal"):
+      manip_ops.roll([[1, 2], [3, 4]], [1], [0, 1])
 
   def testRollShiftAndAxisMustBeSameSizeRaises(self):
+    # The shift and axis must be same size, checked in kernel.
     tensor = [[1, 2], [3, 4]]
-    shift = [1]
+    shift = array_ops.placeholder(dtype=dtypes.int32)
     axis = [0, 1]
     with self.test_session():
       with self.assertRaisesRegexp(errors_impl.InvalidArgumentError,
                                    "shift and axis must have the same size"):
-        manip_ops.roll(tensor, shift, axis).eval()
+        manip_ops.roll(tensor, shift, axis).eval(feed_dict={shift: [1]})
 
   def testRollAxisOutOfRangeRaises(self):
     tensor = [1, 2]