fixed test of canonize that was modifying global mode variables

theano/tensor/tests/test_opt.py

@@ -246,6 +246,8 @@ class test_canonize(unittest.TestCase):
         #We must be sure that the Canonizer is working, but that we don't have other
         # optimisation that could hide bug in the Canonizer as local_elemwise_fusion
         mode=compile.mode.predefined_modes[compile.mode.default_mode]
+        old_optimizer = mode._optimizer
+        try:
             mode._optimizer=gof.Query(["canonicalize"])
             mode._optimizer=mode._optimizer.excluding('local_elemwise_fusion')
             for id, [g, sym_inputs, val_inputs, nb_elemwise, out_dtype] in enumerate(cases):
@@ -256,6 +258,8 @@ class test_canonize(unittest.TestCase):
                 out = f(*val_inputs)
                 assert(len(f.maker.env.toposort())==nb_elemwise)
                 assert(out_dtype==out.dtype)
+        finally:
+            mode._optimizer = old_optimizer
 
     def test_elemwise_multiple_inputs_optimisation2(self):
         """
@@ -367,6 +371,8 @@ class test_canonize(unittest.TestCase):
         #We must be sure that the Canonizer is working, but that we don't have other
         # optimisation that could hide bug in the Canonizer as local_elemwise_fusion
         mode=compile.mode.predefined_modes[compile.mode.default_mode]
+        old_optimizer = mode._optimizer
+        try:
             mode._optimizer=gof.Query(["canonicalize"])
             mode._optimizer=mode._optimizer.excluding('local_elemwise_fusion')
 
@@ -416,7 +422,7 @@ class test_canonize(unittest.TestCase):
                             #must broadcast as their is a dimshuffle in the computation
 
                                                            ((dx/dv)/dx,[dx,dv],[dxv,dvv],2,'float64'),
-#topo:            [Elemwise{inv,no_inplace}(<TensorType(float64, row)>), Elemwise{second,no_inplace}(x, Elemwise{inv,no_inplace}.0)]
+    #topo:            [Elemwise{inv,no_inplace}(<TensorType(float64, row)>), Elemwise{second,no_inplace}(x, Elemwise{inv,no_inplace}.0)]
                                                            ((fx/fv)/fx,[fx,fv],[fxv,fvv],2,'float32'),
                 #topo:[Elemwise{inv,no_inplace}(<TensorType(float32, row)>), Elemwise{second,no_inplace}(x, Elemwise{inv,no_inplace}.0)]
                 ]):
@@ -491,6 +497,8 @@ class test_canonize(unittest.TestCase):
                 topo=f.maker.env.toposort()
                 assert len(topo)==0
                 assert(out_dtype==out.dtype)
+        finally:
+            mode._optimizer = old_optimizer
 
 
     def test_multiple_case_that_fail(self):
@@ -510,10 +518,12 @@ class test_canonize(unittest.TestCase):
         #We must be sure that the Canonizer is working, but that we don't have other
         # optimisation that could hide bug in the Canonizer as local_elemwise_fusion
         mode=compile.mode.predefined_modes[compile.mode.default_mode]
+        old_optimizer = mode._optimizer
+        try:
             mode._optimizer=gof.Query(["canonicalize"])
             mode._optimizer=mode._optimizer.excluding('local_elemwise_fusion')
 
-#test fail!
+    #test fail!
             #test x / y / z -> x / (y * z)
             for (g, sym_inputs, val_inputs, out_dtype) in [
                                                            ((dx/dy)/dz,[dx,dy,dz],[dxv,dyv,dzv],'float64'),
@@ -548,6 +558,9 @@ class test_canonize(unittest.TestCase):
                 assert len(topo[0].inputs)==1
                 assert(out_dtype==out.dtype)
 
+        finally:
+            mode._optimizer = old_optimizer
+
     def test_dont_merge_if_multiple_client(self):
         """ test those case take from the comment in Canonizer
         """
@@ -571,9 +584,15 @@ def test_local_shape_lift_dot():
         for y in [fvector, fmatrix]:
             i = x()
             j = y()
+            print 'I SHAPE', i.type.shape
+            print 'J SHAPE', j.type.shape
             d = shape(dot(i,j))
+            if x is fvector and y is fvector:
+                assert d == ()
+            else:
                 g = Env([i,j], [d])
                 gof.TopoOptimizer(gof.LocalOptGroup(local_shape_lift_dot), order='out_to_in').optimize(g)
+                print pprint(g.outputs[0]), args_to_result[(x,y)]
                 assert pprint(g.outputs[0]) == args_to_result[(x,y)]
         
 #     def test_plusmin(self):
@@ -982,8 +1001,10 @@ class test_fusion(unittest.TestCase):
         #Follow up. Clinker do the same... second cause?
         mode2=compile.Mode(linker(), copy.copy(compile.mode.OPT_FAST_RUN))
 #        mode2=copy.copy(compile.mode.predefined_modes['FAST_RUN'])
+        old_optimizer = mode2._optimizer
+        try:
             mode2._optimizer=mode2._optimizer.excluding('local_elemwise_fusion')
-#        mode2=compile.Mode(gof.OpWiseCLinker(allow_gc=True), compile.mode.OPT_FAST_COMPILE)
+    #        mode2=compile.Mode(gof.OpWiseCLinker(allow_gc=True), compile.mode.OPT_FAST_COMPILE)
 
             if s is None:
                 s=slice(0,49)
@@ -997,8 +1018,10 @@ class test_fusion(unittest.TestCase):
             print "times2 FAST_RUN optimisation without local_elemwise_fusion"
             print times2, times2.min(), times2.max(), times2.sum()
             d=times2/times1
-#        d.sort()
+    #        d.sort()
             print "times2/times1",d,d.min(), d.max(), d.mean(), d.std()
+        finally:
+            mode2._optimizer = old_optimizer
 
     def speed_fusion_gpu(self):
         import theano_cuda_ndarray as tcn