fix a comment in LinearFunction.backward(...)

sccbhxc · sccbhxc · commit cc56d97260ca · 2018-04-13T21:53:34.000+08:00
diff --git a/docs/0.1.12/_sources/notes/extending.rst.txt b/docs/0.1.12/_sources/notes/extending.rst.txt
@@ -56,7 +56,7 @@ additional comments::
         # This function has only a single output, so it gets only one gradient
         def backward(self, grad_output):
             # This is a pattern that is very convenient - at the top of backward
-            # unpack saved_tensors and initialize all gradients w.r.t. inputs to
+            # unpack saved_variables and initialize all gradients w.r.t. inputs to
             # None. Thanks to the fact that additional trailing Nones are
             # ignored, the return statement is simple even when the function has
             # optional inputs.
diff --git a/docs/0.3.0/_sources/notes/extending.rst.txt b/docs/0.3.0/_sources/notes/extending.rst.txt
@@ -56,7 +56,7 @@ additional comments::
         @staticmethod
         def backward(ctx, grad_output):
             # This is a pattern that is very convenient - at the top of backward
-            # unpack saved_tensors and initialize all gradients w.r.t. inputs to
+            # unpack saved_variables and initialize all gradients w.r.t. inputs to
             # None. Thanks to the fact that additional trailing Nones are
             # ignored, the return statement is simple even when the function has
             # optional inputs.
diff --git a/docs/master/_sources/notes/extending.rst.txt b/docs/master/_sources/notes/extending.rst.txt
@@ -56,7 +56,7 @@ additional comments::
         @staticmethod
         def backward(ctx, grad_output):
             # This is a pattern that is very convenient - at the top of backward
-            # unpack saved_tensors and initialize all gradients w.r.t. inputs to
+            # unpack saved_variables and initialize all gradients w.r.t. inputs to
             # None. Thanks to the fact that additional trailing Nones are
             # ignored, the return statement is simple even when the function has
             # optional inputs.
diff --git a/docs/stable/_sources/notes/extending.rst.txt b/docs/stable/_sources/notes/extending.rst.txt
@@ -56,7 +56,7 @@ additional comments::
         @staticmethod
         def backward(ctx, grad_output):
             # This is a pattern that is very convenient - at the top of backward
-            # unpack saved_tensors and initialize all gradients w.r.t. inputs to
+            # unpack saved_variables and initialize all gradients w.r.t. inputs to
             # None. Thanks to the fact that additional trailing Nones are
             # ignored, the return statement is simple even when the function has
             # optional inputs.
