Fix a stability optimization in nnet.

theano/tensor/nnet/nnet.py

@@ -1103,14 +1103,6 @@ def local_argmax_pushdown(node):
 def _check_rows_is_arange_len_labels(rows, labels):
     '''Check that 'rows' is the same node as T.arange(labels.shape[0])'''
 
-    # this is admittedly a pretty random thing to have here... but it's not wrong (I think)
-    # and it has the effect of making the advanced_indexing -> crossentropy optimization work
-    # in the case where the labels are float32s casted to integers.  "Why would anyone do that?"
-    # you ask... it is a handy trick for storing labels on a pre-FERMI GPU device so that
-    # logistic regression goes faster.
-    if labels.owner and labels.owner.op == tensor._convert_to_int32:
-        labels = labels.owner.inputs[0]
-
     if rows.owner and isinstance(rows.owner.op, tensor.ARange):
         start, stop, step = rows.owner.inputs
         if getattr(start, 'data', None) != 0: #constants will have data
@@ -1119,11 +1111,12 @@ def _check_rows_is_arange_len_labels(rows, labels):
             return False
         if not stop.owner:
             return False
-        # Not sure if that case happens any more after the introduction
-        # of ShapeOptimizer
+
+        # Not sure if that case happens any more after the introduction of
+        # ShapeOptimizer, but we keep it if ShapeOptimizer is not present
         if isinstance(stop.owner.op, tensor.Subtensor):
             shape_subtensor = stop.owner
-            if shape_subtensor.op.idx_list == [0]:
+            if list(shape_subtensor.op.idx_list) == [0]:
                 shape_var, = shape_subtensor.inputs
                 if shape_var.owner and shape_var.owner.op == tensor._shape:
                     return shape_var.owner.inputs[0] is labels