--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/algorithms/sgd.py	Tue Oct 28 00:23:53 2008 -0400
@@ -0,0 +1,14 @@
+
+from theano.compile import module
+from theano import tensor as T
+
+class StochasticGradientDescent(module.FancyModule):
+    def __init__(self, params, gparams, lr=None):
+        super(StochasticGradientDescent, self).__init__()
+
+        self.lr = lr if lr is not None else module.Member(T.dscalar())
+        self.params = params
+        self.gparams = gparams
+
+        self.updates = dict((p, p - self.lr * g) for p, g in zip(self.params, self.gparams))
+

--- a/algorithms/tests/test_aa.py	Tue Oct 28 00:23:13 2008 -0400
+++ b/algorithms/tests/test_aa.py	Tue Oct 28 00:23:53 2008 -0400
@@ -1,5 +1,6 @@
+#from __future__ import absolute_imports
 
-import models
+from pylearn import algorithms as models
 import theano
 import numpy
 import time

--- a/stopper.py	Tue Oct 28 00:23:13 2008 -0400
+++ b/stopper.py	Tue Oct 28 00:23:53 2008 -0400
@@ -54,7 +54,7 @@
             if stp.set_score:
                 stp.score = check()
                 if (stp.score < stp.best_score) and save:
-                    best = save()
+                    best = (save(), stp.iter, stp.score)
         return best