Add example of when .data can be unsafe

_posts/2018-04-22-0_4_0-migration-guide.md

@@ -86,6 +86,41 @@ True
 
 However, ``.data`` can be unsafe in some cases. Any changes on ``x.data`` wouldn't be tracked by ``autograd``, and the computed gradients would be incorrect if ``x`` is needed in a backward pass. A safer alternative is to use [``x.detach()``](http://pytorch.org/docs/master/autograd.html#torch.Tensor.detach), which also returns a ``Tensor`` that shares data with ``requires_grad=False``, but will have its in-place changes reported by ``autograd`` if ``x`` is needed in backward.
 
+Here is an example of the difference between ``.data`` and ``x.detach()`` (and why we recommend using ``detach`` in general).
+
+If you use ``Tensor.detach()``, the gradient computation is guaranteed to be correct.
+
+```
+>>> a = torch.tensor([1,2,3.], requires_grad = True)
+>>> out = a.sigmoid()
+>>> c = out.detach()
+>>> c.zero_()
+tensor([ 0.,  0.,  0.])
+
+>>> out  # modified by c.zero_() !!
+tensor([ 0.,  0.,  0.])
+
+>>> out.sum().backward()  # Requires the original value of out, but that was overwritten by c.zero_()
+RuntimeError: one of the variables needed for gradient computation has been modified by an 
+```
+
+However, using ``Tensor.data`` can be unsafe and can easly result in incorrect gradients 
+when a tensor is required for gradient computation but modified in-place.
+
+```
+>>> a = torch.tensor([1,2,3.], requires_grad = True)
+>>> out = a.sigmoid()
+>>> c = out.data
+>>> c.zero_()
+tensor([ 0.,  0.,  0.])
+
+>>> out  # out  was modified by c.zero_()
+tensor([ 0.,  0.,  0.])
+
+>>> out.sum().backward()
+>>> a.grad  # The result is very, very wrong because `out` changed!
+tensor([ 0.,  0.,  0.])
+```
 
 ## Support for 0-dimensional (scalar) Tensors