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diff --git a/tensorflow/contrib/image/python/ops/single_image_random_dot_stereograms.py b/tensorflow/contrib/image/python/ops/single_image_random_dot_stereograms.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.
+# ==============================================================================
+"""Python layer for image_ops."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from tensorflow.contrib.util import loader
+from tensorflow.python.framework import ops
+from tensorflow.python.platform import resource_loader
+
+_sirds_ops = loader.load_op_library(
+    resource_loader.get_path_to_datafile(
+        "_single_image_random_dot_stereograms.so"))
+
+def single_image_random_dot_stereograms(
+    depth_values,
+    hidden_surface_removal=None,
+    convergence_dots_size=None,
+    dots_per_inch=None,
+    eye_separation=None, mu=None,
+    normalize=None, normalize_max=None,
+    normalize_min=None,
+    border_level=None,
+    number_colors=None,
+    output_image_shape=None,
+    output_data_window=None):
+  """Output a RandomDotStereogram Tensor for export via encode_PNG/JPG OP.
+
+  Given the 2-D tensor 'depth_values' with encoded Z values, this operation
+  will encode 3-D data into a 2-D image.  The output of this Op is suitable
+  for the encode_PNG/JPG ops.  Be careful with image compression as this may
+  corrupt the encode 3-D data witin the image.
+
+  Based upon [this paper](http://www.learningace.com/doc/4331582/b6ab058d1e206d68ab60e4e1ead2fe6e/sirds-paper).
+
+  This outputs a SIRDS image as picture_out.png:
+
+  ```python
+  img=[[1,2,3,3,2,1],
+       [1,2,3,4,5,2],
+       [1,2,3,4,5,3],
+       [1,2,3,4,5,4],
+       [6,5,4,4,5,5]]
+  session = tf.InteractiveSession()
+  sirds = single_image_random_dot_stereograms(
+      img,
+      convergence_dots_size=8,
+      number_colors=256,normalize=True)
+
+  out = sirds.eval()
+  png = tf.image.encode_png(out).eval()
+  with open('picture_out.png', 'wb') as f:
+    f.write(png)
+  ```
+
+  Args:
+    depth_values: A `Tensor`. Must be one of the following types: 
+      `float64`, `float32`, `int64`, `int32`.  Z values of data to encode
+      into 'output_data_window' window, lower further away {0.0 floor(far),
+      1.0 ceiling(near) after norm}, must be 2-D tensor
+    hidden_surface_removal: An optional `bool`. Defaults to `True`.
+      Activate hidden surface removal
+    convergence_dots_size: An optional `int`. Defaults to `8`.
+      Black dot size in pixels to help view converge image, drawn on bottom
+      of the image
+    dots_per_inch: An optional `int`. Defaults to `72`.
+      Output device in dots/inch
+    eye_separation: An optional `float`. Defaults to `2.5`.
+      Separation between eyes in inches
+    mu: An optional `float`. Defaults to `0.3333`.
+      Depth of field, Fraction of viewing distance (eg. 1/3 = 0.3333)
+    normalize: An optional `bool`. Defaults to `True`.
+      Normalize input data to [0.0, 1.0] 
+    normalize_max: An optional `float`. Defaults to `-100`.
+      Fix MAX value for Normalization (0.0) - if < MIN, autoscale
+    normalize_min: An optional `float`. Defaults to `100`.
+      Fix MIN value for Normalization (0.0) - if > MAX, autoscale
+    border_level: An optional `float`. Defaults to `0`.
+      Value of bord in depth 0.0 {far} to 1.0 {near} 
+    number_colors: An optional `int`. Defaults to `256`. 2 (Black &
+      White), 256 (grayscale), and Numbers > 256 (Full Color) are
+      supported
+    output_image_shape: An optional `tf.TensorShape` or list of `ints`. 
+      Defaults to shape `[1024, 768, 1]`. Defines output shape of returned
+      image in '[X,Y, Channels]' 1-grayscale, 3 color; channels will be
+      updated to 3 if number_colors > 256
+    output_data_window: An optional `tf.TensorShape` or list of `ints`.
+      Defaults to `[1022, 757]`. Size of "DATA" window, must be equal to or
+      smaller than `output_image_shape`, will be centered and use
+      `convergence_dots_size` for best fit to avoid overlap if possible
+
+  Returns:
+    A `Tensor` of type `uint8` of shape 'output_image_shape' with encoded
+    'depth_values'
+  """
+
+  result = _sirds_ops.single_image_random_dot_stereograms(
+      depth_values=depth_values,
+      hidden_surface_removal=hidden_surface_removal,
+      convergence_dots_size=convergence_dots_size,
+      dots_per_inch=dots_per_inch,
+      eye_separation=eye_separation, mu=mu,
+      normalize=normalize,
+      normalize_max=normalize_max,
+      normalize_min=normalize_min,
+      border_level=border_level,
+      number_colors=number_colors,
+      output_image_shape=output_image_shape,
+      output_data_window=output_data_window)
+  return result
+
+ops.NotDifferentiable("SingleImageRandomDotStereograms")