--- a/mlp.py	Tue May 13 14:28:47 2008 -0400
+++ b/mlp.py	Tue May 13 15:11:24 2008 -0400
@@ -9,7 +9,7 @@
 from theano import tensor as t
 from nnet_ops import *
 import math
-
+from misc import *
 
 class OneHiddenLayerNNetClassifier(OnlineGradientTLearner):
     """
@@ -88,7 +88,7 @@
         self._b2 = t.row('b2')
         self._regularization_term = self._L2_regularizer * (t.sum(self._W1*self._W1) + t.sum(self._W2*self._W2))
         self._output_activations =self._b2+t.dot(t.tanh(self._b1+t.dot(self._input,self._W1.T)),self._W2.T)
-        self._nll,self._output = crossentropy_softmax_1hot(self._output_activations,self._target_vector)
+        self._nll,self._output = crossentropy_softmax_1hot(Print("output_activations")(self._output_activations),self._target_vector)
         self._output_class = t.argmax(self._output,1)
         self._class_error = t.neq(self._output_class,self._target_vector)
         self._minibatch_criterion = self._nll + self._regularization_term / t.shape(self._input)[0]