nnet opt - hacked _check_rows... helper function so that the advanced_indexing

theano/tensor/nnet.py

@@ -923,13 +923,20 @@ 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
             return False
         if getattr(step, 'data', None) != 1: # constant step will have data
             return False
-
         if stop.owner and isinstance(stop.owner.op, tensor.Subtensor):
             shape_subtensor = stop.owner
             if shape_subtensor.op.idx_list == [0]:
@@ -976,6 +983,7 @@ def local_advanced_indexing_crossentropy_onehot(node):
             except:
                 pass
 
+
     if sm is not None and sm.owner and sm.owner.op in (softmax, softmax_with_bias):
         sm_w_bias = local_softmax_with_bias.transform(sm.owner)
         if sm_w_bias: