Merge pull request #373 from lamblin/fix_xent_thing_without_infershape

theano/tensor/tests/mlp_test.py

@@ -306,27 +306,15 @@ def test_mlp():
     theano.printing.debugprint(train_model, print_type=True)
     assert any([isinstance(i.op,T.nnet.CrossentropySoftmax1HotWithBiasDx) for i in train_model.maker.env.toposort()])
 
-    # Now, this case works, too!
-    train_model =theano.function( inputs = [index],
-            updates = updates2,
-            mode=mode.excluding('local_track_shape_i'),
-            givens={
-                x:train_set_x[index*batch_size:(index+1)*batch_size],
-                y:train_set_y[index*batch_size:(index+1)*batch_size]})
-    print
-    print 'MODEL 2'
-    theano.printing.debugprint(train_model, print_type=True)
-    assert any([isinstance(i.op,T.nnet.CrossentropySoftmax1HotWithBiasDx) for i in train_model.maker.env.toposort()])
-
     # Even without FeatureShape
     train_model =theano.function( inputs = [index],
             updates = updates2,
-            mode=mode.excluding('local_shape_to_shape_i'),
+            mode=mode.excluding('ShapeOpt'),
             givens={
                 x:train_set_x[index*batch_size:(index+1)*batch_size],
                 y:train_set_y[index*batch_size:(index+1)*batch_size]})
     print
-    print 'MODEL 3'
+    print 'MODEL 2'
     theano.printing.debugprint(train_model, print_type=True)
     assert any([isinstance(i.op,T.nnet.CrossentropySoftmax1HotWithBiasDx) for i in train_model.maker.env.toposort()])