From 2e88f70ff56f19add121330c7b9c61fbb81e67a5 Mon Sep 17 00:00:00 2001
From: aweers <32593524+aweers@users.noreply.github.com>
Date: Sun, 24 Feb 2019 17:36:05 +0100
Subject: [PATCH] Added ```python for usage examples

---
 tensorflow/python/eager/backprop.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/tensorflow/python/eager/backprop.py b/tensorflow/python/eager/backprop.py
index 694b05c1eea..801e3d6fa56 100644
--- a/tensorflow/python/eager/backprop.py
+++ b/tensorflow/python/eager/backprop.py
@@ -973,13 +973,15 @@ class GradientTape(object):
     definition of a Jacobian.
 
     Example usage:
-
+    
+    ```python
     with tf.GradientTape() as g:
       x  = tf.constant([1.0, 2.0])
       g.watch(x)
       y = x * x
     jacobian = g.jacobian(y, x)
     # jacobian value is [[2., 0.], [0., 4.]]
+    ```
 
     Args:
       target: Tensor to be differentiated.
@@ -1082,12 +1084,14 @@ class GradientTape(object):
     result in the jacobian computation given the independence assumption.
 
     Example usage:
+    ```python
     with tf.GradientTape() as g:
       x = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
       g.watch(x)
       y = x * x
     batch_jacobian = g.batch_jacobian(y, x)
     # batch_jacobian is [[[2,  0], [0,  4]], [[6,  0], [0,  8]]]
+    ```
 
     Args:
       target: A tensor with rank 2 or higher and with shape [b, y1, ..., y_n].