diff --git a/tensorflow/core/kernels/in_topk_op_gpu.cu.cc b/tensorflow/core/kernels/in_topk_op_gpu.cu.cc
index 44c96f67b26..f701071cb8e 100644
--- a/tensorflow/core/kernels/in_topk_op_gpu.cu.cc
+++ b/tensorflow/core/kernels/in_topk_op_gpu.cu.cc
@@ -100,6 +100,12 @@ struct InTopKFunctor<GPUDevice, T, TargetT> {
         errors::InvalidArgument(
             "Number of targets * number of classes must be less than INT_MAX"));
 
+    if (num_targets == 0 || num_classes == 0) {
+      // Result is empty, so shortcut the rest of the function to avoid
+      // launching kernels with empty input.
+      return;
+    }
+
     // Temporary storage for a mask computed by  `ComputePredictionMaskKernel`.
     Tensor predictions_mask;
     OP_REQUIRES_OK(
diff --git a/tensorflow/python/kernel_tests/in_topk_op_test.py b/tensorflow/python/kernel_tests/in_topk_op_test.py
index 2ef233f8d68..c636cee0dd5 100644
--- a/tensorflow/python/kernel_tests/in_topk_op_test.py
+++ b/tensorflow/python/kernel_tests/in_topk_op_test.py
@@ -28,7 +28,7 @@ from tensorflow.python.platform import test
 class InTopKTest(test.TestCase):
 
   def _validateInTopK(self, predictions, target, k, expected):
-    np_ans = np.array(expected)
+    np_ans = np.array(expected, np.bool)
     with self.cached_session(use_gpu=True):
       precision = nn_ops.in_top_k(predictions, target, k)
       out = self.evaluate(precision)
@@ -66,6 +66,11 @@ class InTopKTest(test.TestCase):
     target = [2, 4]  # must return False for invalid target
     self._validateInTopK(predictions, target, 2, [True, False])
 
+  def testEmpty(self):
+    predictions = np.empty([0, 5])
+    target = np.empty([0], np.int32)
+    self._validateInTopK(predictions, target, 2, [])
+
   def testTensorK(self):
     predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]]
     target = [0, 2]