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diff --git a/tensorflow/python/kernel_tests/decode_image_op_test.py b/tensorflow/python/kernel_tests/decode_image_op_test.py
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+++ b/tensorflow/python/kernel_tests/decode_image_op_test.py
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+# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for decode_image."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os.path
+import numpy as np
+import tensorflow as tf
+
+# Double-quote usage here is intentional to make internal path rewriting easier.
+prefix_path = os.path.join("tensorflow", "core", "lib")
+
+class DecodeImageOpTest(tf.test.TestCase):
+
+  def testGif(self):
+    # Read some real GIFs
+    path = os.path.join(prefix_path, 'gif', 'testdata', 'scan.gif')
+    WIDTH = 20
+    HEIGHT = 40
+    STRIDE = 5
+    shape = (12, HEIGHT, WIDTH, 3)
+
+    with self.test_session(use_gpu=True) as sess:
+      gif0 = tf.read_file(path)
+      image0 = tf.image.decode_image(gif0)
+      image1 = tf.image.decode_gif(gif0)
+      gif0, image0, image1 = sess.run([gif0, image0, image1])
+
+      self.assertEqual(image0.shape, shape)
+      self.assertAllEqual(image0, image1)
+
+      for frame_idx, frame in enumerate(image0):
+        gt = np.zeros(shape[1:], dtype=np.uint8)
+        start = frame_idx * STRIDE
+        end = (frame_idx + 1) * STRIDE
+        if end <= WIDTH:
+          gt[:, start:end, :] = 255
+        else:
+          start -= WIDTH
+          end -= WIDTH
+          gt[start:end, :, :] = 255
+
+        self.assertAllClose(frame, gt)
+
+        bad_channels = tf.image.decode_image(gif0, channels=1)
+        with self.assertRaises(tf.errors.InvalidArgumentError):
+          bad_channels.eval()
+
+
+  def testJpeg(self):
+    # Read a real jpeg and verify shape
+    path = os.path.join(prefix_path, 'jpeg', 'testdata', 'jpeg_merge_test1.jpg')
+    with self.test_session(use_gpu=True) as sess:
+      jpeg0 = tf.read_file(path)
+      image0 = tf.image.decode_image(jpeg0)
+      image1 = tf.image.decode_jpeg(jpeg0)
+      jpeg0, image0, image1 = sess.run([jpeg0, image0, image1])
+      self.assertEqual(len(jpeg0), 3771)
+      self.assertEqual(image0.shape, (256, 128, 3))
+      self.assertAllEqual(image0, image1)
+
+  def testPng(self):
+    # Read some real PNGs, converting to different channel numbers
+    inputs = [(1, 'lena_gray.png')]
+    for channels_in, filename in inputs:
+      for channels in 0, 1, 3:
+        with self.test_session(use_gpu=True) as sess:
+          path = os.path.join(prefix_path, 'png', 'testdata', filename)
+          png0 = tf.read_file(path)
+          image0 = tf.image.decode_image(png0, channels=channels)
+          image1 = tf.image.decode_png(png0, channels=channels)
+          png0, image0, image1 = sess.run([png0, image0, image1])
+          self.assertEqual(image0.shape, (26, 51, channels or channels_in))
+          self.assertAllEqual(image0, image1)
+
+  def testInvalidBytes(self):
+    image_bytes = b'ThisIsNotAnImage!'
+    decode = tf.image.decode_image(image_bytes)
+    with self.test_session():
+      with self.assertRaises(tf.errors.InvalidArgumentError):
+        decode.eval()
+
+  def testInvalidChannels(self):
+    image_bytes = b'unused'
+    with self.assertRaises(ValueError):
+      decode = tf.image.decode_image(image_bytes, channels=4)
+
+
+if __name__ == "__main__":
+  tf.test.main()