Merge pull request #673 from nouiz/fusion

theano/tensor/opt.py

@@ -4395,9 +4395,11 @@ def local_elemwise_fusion_op(OP, max_input_fct=lambda node: 1024):
 
             # We should not check the number of inputs here
             # As fusing op don't always change the number of input.
+            # If a variable is used as multiple into to the same node,
+            # we still want to fusion. So we take the set.
             if (i.owner and
                 isinstance(i.owner.op, OP) and
-                len(i.clients) == 1):
+                len(set([n for n, idx in i.clients])) == 1):
 
                 do_fusion = True
                 try:

theano/tensor/tests/test_opt.py

@@ -887,13 +887,9 @@ class test_fusion(unittest.TestCase):
 
             # Cases where the same input is reused many times.
             (theano.tensor.mul(fx,fx,fx,fx),(fx,),(fxv,),1,fxv*fxv*fxv*fxv,'float32'),
-            # TODO: This case is not fused!
-            (theano.tensor.mul(fx,ftanx,ftanx),(fx,),(fxv,),2,fxv*numpy.tan(fxv)*numpy.tan(fxv),'float32'),
-            # TODO: This case is not fused!
-            (theano.tensor.mul(fx,ftanx,ftanx,fx),(fx,),(fxv,),2,fxv*numpy.tan(fxv)*numpy.tan(fxv)*fxv,'float32'),
-            # The next case test when one variable appear as many inputs to an op.
-            # In the past, this was not fused. (TODO) Now it is partially fused.
-            (theano.tensor.mul(ftanx,ftanx,fx+fy),(fx,fy),(fxv,fyv),2,numpy.tan(fxv)*numpy.tan(fxv)*(fxv+fyv),'float32'),
+            (theano.tensor.mul(fx,ftanx,ftanx),(fx,),(fxv,),1,fxv*numpy.tan(fxv)*numpy.tan(fxv),'float32'),
+            (theano.tensor.mul(fx,ftanx,ftanx,fx),(fx,),(fxv,),1,fxv*numpy.tan(fxv)*numpy.tan(fxv)*fxv,'float32'),
+            (theano.tensor.mul(ftanx,ftanx,fx+fy),(fx,fy),(fxv,fyv),1,numpy.tan(fxv)*numpy.tan(fxv)*(fxv+fyv),'float32'),
             ]
         if slice:
             cases = cases[slice]