2 files changed, 105 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/in_topk_op_test.py b/tensorflow/python/kernel_tests/in_topk_op_test.py
index 4a4686d1b9..37e9a8e3d1 100644
--- a/tensorflow/python/kernel_tests/in_topk_op_test.py
+++ b/tensorflow/python/kernel_tests/in_topk_op_test.py
@@ -20,7 +20,9 @@ from __future__ import print_function
 
 import numpy as np
 
+from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import errors_impl
+from tensorflow.python.ops import gen_nn_ops
 from tensorflow.python.ops import nn_ops
 from tensorflow.python.platform import test
 
@@ -69,6 +71,18 @@ class InTopKTest(test.TestCase):
                                    "target.*out of range"):
         nn_ops.in_top_k(predictions, target, 2).eval()
 
+  def testTensorK(self):
+    predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]]
+    target = [0, 2]
+    k = constant_op.constant(3)
+    np_ans = np.array([False, True])
+    with self.test_session():
+      # TODO (yongtang): The test will be switch to nn_ops.in_top
+      # once nn_ops.in_top points to _in_top_kv2 later
+      precision = gen_nn_ops._in_top_kv2(predictions, target, k)
+      out = precision.eval()
+      self.assertAllClose(np_ans, out)
+      self.assertShapeEqual(np_ans, precision)
 
 if __name__ == "__main__":
   test.main()
diff --git a/tensorflow/python/kernel_tests/relu_op_test.py b/tensorflow/python/kernel_tests/relu_op_test.py
index 63ac743843..8cd1f52d80 100644
--- a/tensorflow/python/kernel_tests/relu_op_test.py
+++ b/tensorflow/python/kernel_tests/relu_op_test.py
@@ -320,6 +320,97 @@ class EluTest(test.TestCase):
     self.assertLess(err, 1e-6)
 
 
+class SeluTest(test.TestCase):
+
+  def _npSelu(self, np_features):
+    scale = 1.0507009873554804934193349852946
+    scale_alpha = 1.7580993408473768599402175208123
+    return np.where(np_features < 0, scale_alpha * (np.exp(np_features) - 1),
+                    scale * np_features)
+
+  def testNpSelu(self):
+    self.assertAllClose(
+        np.array([[-1.0433095, 0.73549069, -0.6917582, 0.3152103 , -0.16730527],
+                 [0.1050701 , -0.45566732, 0.5253505, -0.88505305, 0.9456309]]),
+        self._npSelu(
+            np.array([[-0.9, 0.7, -0.5, 0.3, -0.1], [0.1, -0.3, 0.5, -0.7, 0.9]
+                     ])))
+
+  def _testSelu(self, np_features, use_gpu=False):
+    np_selu = self._npSelu(np_features)
+    with self.test_session(use_gpu=use_gpu):
+      selu = nn_ops.selu(np_features)
+      tf_selu = selu.eval()
+    self.assertAllClose(np_selu, tf_selu)
+    self.assertShapeEqual(np_selu, selu)
+
+  def testNumbers(self):
+    for t in [np.float16, np.float32, np.float64]:
+      self._testSelu(
+          np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t),
+          use_gpu=False)
+      self._testSelu(
+          np.array([[-9, 7, -5, 3, -1], [1, -3, 5, -7, 9]]).astype(t),
+          use_gpu=True)
+
+  def testGradientFloat32(self):
+    with self.test_session():
+      x_val = [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]]
+      x = constant_op.constant(x_val, name="x")
+      y = nn_ops.selu(x, name="selu")
+      x_init = np.asarray(x_val, dtype=np.float32, order="F")
+      err = gradient_checker.compute_gradient_error(
+          x, [2, 5], y, [2, 5], x_init_value=x_init)
+    print("selu (float32) gradient err = ", err)
+    self.assertLess(err, 1e-4)
+
+  def testGradientFloat64(self):
+    with self.test_session():
+      x_val = [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]]
+      x = constant_op.constant(x_val, dtype=dtypes.float64, name="x")
+      y = nn_ops.selu(x, name="selu")
+      x_init = np.asarray(x_val, dtype=np.float64, order="F")
+      err = gradient_checker.compute_gradient_error(
+          x, [2, 5], y, [2, 5], x_init_value=x_init)
+    print("selu (float64) gradient err = ", err)
+    self.assertLess(err, 1e-6)
+
+  def testGradGradFloat32(self):
+    with self.test_session():
+      x = constant_op.constant(
+          [-0.9, -0.7, -0.5, -0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9],
+          shape=[2, 5],
+          name="x")
+      y = nn_ops.selu(x, name="selu")
+      z = gradients_impl.gradients(y, x)
+      x_init = np.asarray(
+          [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]],
+          dtype=np.float32,
+          order="F")
+      err = gradient_checker.compute_gradient_error(
+          x, [2, 5], z[0], [2, 5], x_init_value=x_init)
+    print("selu (float32) gradient of gradient err = ", err)
+    self.assertLess(err, 1e-4)
+
+  def testGradGradFloat64(self):
+    with self.test_session():
+      x = constant_op.constant(
+          [-0.9, -0.7, -0.5, -0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9],
+          shape=[2, 5],
+          dtype=dtypes.float64,
+          name="x")
+      y = nn_ops.selu(x, name="selu")
+      z = gradients_impl.gradients(y, x)
+      x_init = np.asarray(
+          [[-0.9, -0.7, -0.5, -0.3, -0.1], [0.1, 0.3, 0.5, 0.7, 0.9]],
+          dtype=np.float64,
+          order="F")
+      err = gradient_checker.compute_gradient_error(
+          x, [2, 5], z[0], [2, 5], x_init_value=x_init)
+    print("selu (float64) gradient of gradient err = ", err)
+    self.assertLess(err, 1e-6)
+
+
 class CreluTest(test.TestCase):
 
   def testCreluShape(self):