if the env variable THEANO_FLAGS have the token local_elemwise_fusion we enable…

theano/tensor/opt.py

@@ -14,7 +14,7 @@ import inplace as I
 import numpy as N
 import operator
 import itertools
-import sys
+import sys, os
 from theano import compile  #to register the optimizer built by this file
 
 from theano.gof.python25 import any, all
@@ -1237,8 +1237,7 @@ def local_elemwise_fusion(node):
     The number of dimension is validated at call time by theano itself.
     TODO:The broadcast flag?
     """
-#    TODO:implement Composite.__eq__ by using CLinker.cmodule_key() to compare the graph.
-#TODO: Merge when nb_clients>1? When this optimisation could introduce duplication of computation? When this will be faster?
+#TODO: Merge with multiple output to merge when an inputs have multiple clients. This can't be done with a local optimiser.
 
     if not isinstance(node.op, T.Elemwise):
         return False
@@ -1305,8 +1304,16 @@ def local_elemwise_fusion(node):
 
 #    print "local_elemwise_fusion: FUSED",nb_elemwise+1,"elemwise!"
     return n.outputs
-         
-#register_specialize(local_elemwise_fusion)
+
+flags=os.getenv('THEANO_FLAGS',None)
+if flags:
+    flags=flags.split(',')
+    if 'local_elemwise_fusion' in flags:
+        print "Will fusion elemwise"
+        register_specialize(local_elemwise_fusion)
+    else:
+        print "Won't fuse elemwise"
+
 # def make_composite(inputs, outputs):
 #     scalar_inputs = [scalar.Scalar(dtype = i.type.dtype)() for i in inputs]
 #     def transform(r):