larroy commented on a change in pull request #15109: [DOC] refine autograd docs
URL: https://github.com/apache/incubator-mxnet/pull/15109#discussion_r292653783
 
 

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 File path: docs/api/python/autograd/autograd.md
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 @@ -76,7 +82,63 @@ Detailed tutorials are available in Part 1 of
 [the MXNet gluon book](http://gluon.mxnet.io/).
 
 
+# Higher order gradient
+
+Some operators support higher order gradients. Meaning that you calculate the 
gradient of the
+gradient. For this the operator's backward must be as well differentiable. 
Some operators support
+differentiating multiple times, and others two, most just once.
+
+For calculating higher order gradients, we can use the `mx.autograd.grad` 
function while recording
+and then call backward, or call `mx.autograd.grad` two times. If we do the 
later is important that
+the first call uses `create_graph=True` and `retain_graph=True` and the second 
call uses
+`create_graph=False` and `retain_graph=True`. Otherwise we will not get the 
results that we want. If
 
 Review comment:
   that's what I understand as well.

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