bugfix in mul canonizer regarding int div

theano/tensor/opt.py

@@ -452,8 +452,15 @@ class Canonizer(gof.LocalOptimizer):
         a / (b / c) -> ([a, c], [b])
         log(x) -> ([log(x)], [])
         x**y -> ([x**y], [])
+
         """
 
+        # This function is recursive.
+        # The idea is that there is a get_num_denum recursion in which the internal ops are all
+        # one of (main, inverse, reciprocal, DimShuffle) and the internal data nodes all have
+        # the dtype of the 'input' argument. The leaf-Variables of the graph covered by the
+        # recursion may be of any Variable type.
+
         if input.owner is None or input.owner.op not in [self.main, self.inverse, self.reciprocal]:
             if input.owner and isinstance(input.owner.op, T.DimShuffle):
                 # If input is a DimShuffle of some input which does something like this:
@@ -489,8 +496,13 @@ class Canonizer(gof.LocalOptimizer):
         denum = []
         parent = input.owner
 
-        # We get the (num, denum) pairs for each input
-        pairs = [self.get_num_denum(input) for input in parent.inputs]
+
+        # We get the (num, denum) pairs for each input (input2) *to* input that has the same
+        # type as this one.
+        pairs = [self.get_num_denum(input2)
+                if (getattr(input2.type, 'dtype', None) == input.type.dtype) 
+                else ([input2], [])
+                for input2 in parent.inputs ]
 
         if parent.op == self.main:
             # If we have main(x, y), numx, denumx, numy and denumy
@@ -683,20 +695,6 @@ class Canonizer(gof.LocalOptimizer):
         out = node.outputs[0]
         assert len(node.outputs) == 1
 
-        # I'm not sure if this is actually needed but the following
-        # block of code puts into "reorg" whether or not we are going
-        # to change the structure of the graph. For example if we have
-        # inverse operating on an inverse, we can make it so that only
-        # one inverse is used, so we'll reorganize that.
-        iops = set(input.owner.op for input in inputs if input.owner)
-        reorg = False
-        if op == self.main:
-            reorg = len(iops.intersection([self.main, self.inverse, self.reciprocal])) != 0
-        elif op == self.inverse:
-            reorg = len(iops.intersection([self.inverse, self.reciprocal])) != 0
-        elif op == self.reciprocal:
-            reorg = len(iops.intersection([self.inverse, self.reciprocal])) != 0
-
         # Here we make the canonical version of the graph around this node
         # See the documentation of get_num_denum and simplify
         orig_num, orig_denum = self.get_num_denum(node.outputs[0])
@@ -706,9 +704,8 @@ class Canonizer(gof.LocalOptimizer):
         def same(x, y):
             return len(x) == len(y) and all(N.all(xe == ye) for xe, ye in zip(x, y))
 
-        if not reorg and same(orig_num, num) and same(orig_denum, denum):
+        if same(orig_num, num) and same(orig_denum, denum):
             # We return False if there are no changes
-            # TODO: what's the purpose of reorg? isn't same() sufficient?
             return False
 
         new = self.merge_num_denum(num, denum)

theano/tensor/tests/test_opt.py

@@ -177,6 +177,14 @@ class test_canonize(unittest.TestCase):
         mul_canonizer.optimize(g)
         gof.TopoOptimizer(gof.LocalOptGroup(local_fill_cut, local_fill_lift), order = 'out_to_in').optimize(g)
         print pprint(g.outputs[0])
+
+
+def test_mixeddiv():
+    """Test that int division is preserved"""
+    i = iscalar()
+    d = dscalar()
+    assert 0 == function([i,d], d*(i/(i+1)))(3, 1.0)
+
         
 #     def test_plusmin(self):
 #         x, y, z = inputs()