Update docs for `mark_non_differentiable` method (#17891)

Summary:
The current documentation doesn't reflect the real values of tensors during the backward pass.
This issue is mentioned in https://github.com/pytorch/pytorch/issues/12631
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17891

Differential Revision: D14419949

Pulled By: soumith

fbshipit-source-id: 8b495628c3f017bc880f8096682cd176a53974e5

diff --git a/torch/autograd/function.py b/torch/autograd/function.py
index ea48a4f..89e930a 100644 (file)
--- a/torch/autograd/function.py
+++ b/torch/autograd/function.py
@@ -51,7 +51,8 @@ class _ContextMethodMixin(object):
         This will mark outputs as not requiring gradients, increasing the
         efficiency of backward computation. You still need to accept a gradient
         for each output in :meth:`~Function.backward`, but it's always going to
-        be ``None``.
+        be a zero tensor with the same shape as the shape of a corresponding
+        output.
 
         This is used e.g. for indices returned from a max :class:`Function`.
         """