Added specialize optimization local_sum_mul_by_scalar

theano/tensor/opt.py

@@ -880,6 +880,37 @@ def local_neg_to_mul(node):
         return [T.mul(-1, node.inputs[0])]
 register_canonicalize(local_neg_to_mul)
 
+@register_specialize
+@gof.local_optimizer([])
+def local_sum_mul_by_scalar(node):
+    """sum(scalar * smth) -> scalar * sum(smth)
+    """
+    # TODO: if the the thing inside the Sum is a division, 
+    # we should get at the numerator....
+    if isinstance(node.op, T.Sum):
+        thing_summed, = node.inputs
+        if thing_summed.owner and thing_summed.owner.op == T.mul:
+            terms = thing_summed.owner.inputs
+            scalars = [t.dimshuffle() for t in terms if numpy.all(t.type.broadcastable)]
+            non_scalars = [t for t in terms if not numpy.all(t.broadcastable)]
+            if scalars:
+                if len(scalars) > 1:
+                    if len(non_scalars) > 1:
+                        return [T.mul(T.mul(*scalars), node.op(T.mul(*non_scalars)))]
+                    elif len(non_scalars) == 1:
+                        return [T.mul(T.mul(*scalars), node.op(non_scalars[0]))]
+                    else:
+                        return [T.mul(*scalars)]
+                else:
+                    if len(non_scalars) > 1:
+                        return [T.mul(scalars[0], node.op(T.mul(*non_scalars)))]
+                    elif len(non_scalars) == 1:
+                        return [T.mul(scalars[0], node.op(non_scalars[0]))]
+                    else:
+                        return [scalars[0]]
+        if thing_summed.owner and thing_summed.owner.op == T.neg:
+            return [T.neg(node.op(thing_summed.owner.inputs[0]))]
+
 @gof.local_optimizer([T.mul])
 def local_mul_to_neg(node):
     if node.op == T.mul and N.all(local_mul_canonizer.get_constant(node.inputs[0]) == -1.0):