Changed documentation.

gradient.py

@@ -20,14 +20,6 @@ def _pack_result(arg):
 
 def grad_sources_inputs(sources, graph_inputs):
     """
-    @rtype: dictionary
-    @return: dictionary mapping each result necessary for a source to its gradient.
-
-    @type sources: list
-    @param sources: gradient sources (explained below)
-    @type graph_inputs: list
-    @param graph_inputs: results considered to be constant
-
     A gradient source is a pair (r, g_r), in which r is a result, and g_r is a
     result that is a gradient wrt r.
 
@@ -39,16 +31,16 @@ def grad_sources_inputs(sources, graph_inputs):
     convenience of the L{Op} implementer) depending on the number of inputs and
     outputs.  
 
-    If there is one input and one output:
+    If there is one input and one output::
         op.grad( op.inputs[0], grad(op.outputs[0]))
 
-    If there are several inputs and one output:
+    If there are several inputs and one output::
         op.grad( op.inputs, grad(op.outputs[0]))
 
-    If there is one input and several outputs:
+    If there is one input and several outputs::
         op.grad( op.inputs[0], [grad(o) for o in op.outputs[0]])
 
-    If there are multiple inputs and outputs:
+    If there are multiple inputs and outputs::
         op.grad( op.inputs, [grad(o) for o in op.outputs[0]])
 
     This function expects the L{Op.grad}(...) function to return the gradient
@@ -60,6 +52,13 @@ def grad_sources_inputs(sources, graph_inputs):
     For each input wrt to which an L{Op} is not differentiable, it should return
     None instead of a result instance.
 
+    @type sources: list
+    @param sources: gradient sources (explained below)
+    @type graph_inputs: list
+    @param graph_inputs: results considered to be constant
+
+    @rtype: dictionary
+    @return: dictionary mapping each result necessary for a source to its gradient.
     """
     gmap = {}
     for (r, g_r) in sources: