changed graph.clone_equiv to copy orphans as well as inputs and added Op.clone_with_new_inputs

gof/graph.py

@@ -135,13 +135,14 @@ def clone(i, o, copy_inputs = False):
     return [equiv[output] for output in o]
 
 
-def clone_get_equiv(i, o, copy_inputs = False):
+def clone_get_equiv(i, o, copy_inputs_and_orphans = False):
     """
     i -> list of input Results
     o -> list of output Results
-    copy_inputs -> if True, the inputs will be replaced in the cloned
-                   graph by copies available in the equiv dictionary
-                   returned by the function (copy_inputs defaults to False)
+    copy_inputs_and_orphans -> if True, the inputs and the orphans
+         will be replaced in the cloned graph by copies available in
+         the equiv dictionary returned by the function (copy_inputs
+         defaults to False)
 
     Returns equiv a dictionary mapping each result and op in the
     graph delimited by i and o to a copy (akin to deepcopy's memo).
@@ -150,8 +151,8 @@ def clone_get_equiv(i, o, copy_inputs = False):
     d = {}
 
     for input in i:
-        if copy_inputs:
-            d[input] = copy(input)
+        if copy_inputs_and_orphans:
+            d[input] = input.clone(True)
         else:
             d[input] = input
 
@@ -160,9 +161,13 @@ def clone_get_equiv(i, o, copy_inputs = False):
             return d[result]
         op = result.owner
         if not op:
-            return result
+            if copy_inputs_and_orphans:
+                d[result] = result.clone(True)
             else:
-            new_op = op.__class__(*[clone_helper(input) for input in op.inputs])
+                d[result] = result
+            return d[result]
+        else:
+            new_op = op.clone_with_new_inputs(*[clone_helper(input) for input in op.inputs])
             d[op] = new_op
             for output, new_output in zip(op.outputs, new_op.outputs):
                 d[output] = new_output

gof/op.py

@@ -88,12 +88,21 @@ class Op(object):
         """
         Shallow copy of this Op. The inputs are the exact same, but
         the outputs are recreated because of the one-owner-per-result
-        policy.
+        policy. The default behavior is to call the constructor on
+        this Op's inputs.
 
-        This implementation permits a bottom-up copy of an entire graph.
+        To do a bottom-up copy of a graph, use clone_with_new_inputs.
         """
         return self.__class__(*self.inputs)
 
+    def clone_with_new_inputs(self, *new_inputs):
+        """
+        Returns a clone of this Op that takes different inputs. The
+        default behavior is to call the constructor on the new inputs,
+        but if your Op has additional options or a different constructor
+        you might want to override this.
+        """
+        return self.__class__(*new_inputs)
 
     #
     # String representation