--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pylearn/algorithms/tests/test_stacker.py	Wed Nov 12 21:57:54 2008 -0500
@@ -0,0 +1,43 @@
+
+import models
+import theano
+import numpy
+import time
+
+
+def test_train(mode = theano.Mode('c|py', 'fast_run')):
+
+    reg = models.Stacker([(models.BinRegressor, 'output'), (models.BinRegressor, 'output')],
+                         regularize = False)
+    #print reg.global_update[1].pretty(mode = mode.excluding('inplace'))
+
+    model = reg.make([100, 200, 1],
+                     lr = 0.01,
+                     mode = mode,
+                     seed = 10)
+
+    R = numpy.random.RandomState(100)
+    t1 = time.time()
+    for i in xrange(1001):
+        data = R.random_integers(0, 1, size = (10, 100))
+        targets = data[:, 6].reshape((10, 1))
+        cost = model.update(data, targets)
+        if i % 100 == 0:
+            print i, '\t', cost, '\t', 1*(targets.T == model.classify(data).T)
+    t2 = time.time()
+    return t2 - t1
+
+if __name__ == '__main__':
+    print 'optimized:'
+    t1 = test_train(theano.Mode('c|py', 'fast_run'))
+    print 'time:',t1
+    print
+
+    print 'not optimized:'
+    t2 = test_train(theano.Mode('c|py', 'fast_compile'))
+    print 'time:',t2
+
+
+
+
+