commit

_test_tensor_opt.py

@@ -102,6 +102,19 @@ from theano.tensor import *
 
 from theano.sandbox  import pprint
 
+class _test_greedy_distribute(unittest.TestCase):
+    def test_main(self):
+        a, b, c, d, x, y, z = matrices('abcdxyz')
+        e = (a/z + b/x) * x * z
+        g = Env([a,b,c,d,x,y,z], [e])
+        print pprint.pp.process(g.outputs[0])
+        mul_canonizer.optimize(g)
+        gof.TopoOptimizer(gof.LocalOptGroup(local_fill_cut, local_fill_lift), order = 'out_to_in').optimize(g)
+        gof.TopoOptimizer(gof.LocalOptGroup(local_greedy_distributor), order = 'out_to_in').optimize(g)
+        print pprint.pp.process(g.outputs[0])
+        
+
+
 class _test_canonize(unittest.TestCase):
 
     def test_muldiv(self):

scalar.py

@@ -615,6 +615,9 @@ class Log(UnaryScalarOp):
     def grad(self, (x, ), (gz, )):
         return gz / x,
     def c_code(self, node, name, (x, ), (z, ), sub):
+        #todo: the version using log2 seems to be very slightly faster
+        # on some machines for some reason, check if it's worth switching
+        #return "%(z)s = log2(%(x)s) * 0.69314718055994529;" % locals()
         return "%(z)s = log(%(x)s);" % locals()
 log = Log(upgrade_to_float, name = 'log')