made test of crossentropy optimizations more robust

theano/tensor/tests/test_nnet.py

@@ -217,10 +217,24 @@ class T_CrossentropyCategorical1Hot(unittest.TestCase):
 
         # the function has 9 ops because the dimshuffle and elemwise{second} aren't getting
         # cleaned up as well as we'd like.
-
-        assert env.toposort()[3].op == crossentropy_softmax_argmax_1hot_with_bias
-        assert env.toposort()[8].op == crossentropy_softmax_1hot_with_bias_dx 
-        assert len(env.toposort()) == 9  #shorthand for actually checking what I really 
+        has_cx1hot = False
+        has_cx1hotdx = False
+        has_softmax = False
+        has_softmaxdx = False
+        for node in env.toposort():
+            if node.op == crossentropy_softmax_argmax_1hot_with_bias:
+                has_cx1hot = True
+            if node.op == crossentropy_softmax_1hot_with_bias_dx :
+                has_cx1hotdx = True
+            if node.op == softmax:
+                has_softmax = True
+            if node.op == softmax_grad:
+                has_softmaxdx = True
+
+        assert has_cx1hot
+        assert has_cx1hotdx
+        assert not has_softmax
+        assert not has_softmaxdx
 
 def test_argmax_pushdown():
     x = tensor.dmatrix()