diff --git a/tensorflow/core/api_def/base_api/api_def_RGBToHSV.pbtxt b/tensorflow/core/api_def/base_api/api_def_RGBToHSV.pbtxt
index 08629610ed4..3c41bb697f2 100644
--- a/tensorflow/core/api_def/base_api/api_def_RGBToHSV.pbtxt
+++ b/tensorflow/core/api_def/base_api/api_def_RGBToHSV.pbtxt
@@ -21,5 +21,17 @@ are in `[0,1]`.
 `output[..., 0]` contains hue, `output[..., 1]` contains saturation, and
 `output[..., 2]` contains value. All HSV values are in `[0,1]`. A hue of 0
 corresponds to pure red, hue 1/3 is pure green, and 2/3 is pure blue.
+
+Usage Example:
+
+>>> blue_image = tf.stack([
+...    tf.zeros([5,5]),
+...    tf.zeros([5,5]),
+...    tf.ones([5,5])],
+...    axis=-1)
+>>> blue_hsv_image = tf.image.rgb_to_hsv(blue_image)
+>>> blue_hsv_image[0,0].numpy()
+array([0.6666667, 1. , 1. ], dtype=float32)
+
 END
 }
diff --git a/tensorflow/python/ops/image_grad.py b/tensorflow/python/ops/image_grad.py
index 878ca4d8513..8deac46aa06 100644
--- a/tensorflow/python/ops/image_grad.py
+++ b/tensorflow/python/ops/image_grad.py
@@ -177,17 +177,6 @@ def _RGBToHSVGrad(op, grad):
   separately before adding them in the end. Formulas are given before each
   partial derivative calculation.
 
-  Usage Example:
-
-  >>> rgb_image = tf.stack([ 
-  ...    tf.zeros([5,5]), 
-  ...    tf.zeros([5,5]), 
-  ...    tf.ones([5,5])],
-  ...    axis=-1)
-  >>> hsv_image = tf.image.rgb_to_hsv(rgb_image)
-  >>> hsv_image[1,1].numpy()
-  array([0.6666667, 1. , 1. ], dtype=float32)
-  
   Args:
     op: The `rgb_to_hsv` `Operation` that we are differentiating.
     grad: Gradient with respect to the output of the `rgb_to_hsv` op.