--- a/pylearn/algorithms/cost.py	Wed Jan 21 16:01:16 2009 -0500
+++ b/pylearn/algorithms/cost.py	Wed Jan 21 16:02:07 2009 -0500
@@ -14,12 +14,13 @@
 def quadratic(target, output, axis=1):
     return T.mean(T.sqr(target - output), axis=axis)
 
-def cross_entropy(target, output, axis=1):
+def cross_entropy(target, output, mean_axis=0, sum_axis=1):
     """
     @todo: This is essentially duplicated as nnet_ops.binary_crossentropy
     @warning: OUTPUT and TARGET are reversed in nnet_ops.binary_crossentropy
     """
-    return -T.mean(target * T.log(output) + (1 - target) * T.log(1 - output), axis=axis)
+    XE = target * T.log(output) + (1 - target) * T.log(1 - output)
+    return -T.mean(T.sum(XE, axis=sum_axis),axis=mean_axis)
 
 def KL_divergence(target, output):
     """