# HG changeset patch
# User Joseph Turian <turian@gmail.com>
# Date 1225208431 14400
# Node ID 32509c479e2d0b66ac574dbf4e902691cab078ac
# Parent  4f3c66146f170d5481cc4ce22a8006c92ea72252
Added test_daa.py

diff -r 4f3c66146f17 -r 32509c479e2d algorithms/tests/test_daa.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/algorithms/tests/test_daa.py	Tue Oct 28 11:40:31 2008 -0400
@@ -0,0 +1,48 @@
+#!/usr/bin/python
+
+from pylearn import algorithms as models
+import theano
+import numpy
+import time
+
+
+def test_train_daa(mode = theano.Mode('c|py', 'fast_run')):
+
+    ndaa = 3
+    daa = models.Stacker([(models.SigmoidXEDenoisingAA, 'hidden')] * ndaa + [(models.BinRegressor, 'output')],
+                         regularize = False)
+
+    model = daa.make([4, 20, 20, 20, 1],
+                     lr = 0.01,
+                     mode = mode,
+                     seed = 10)
+
+    model.layers[0].noise_level = 0.3
+    model.layers[1].noise_level = 0.3
+    model.layers[2].noise_level = 0.3
+
+    # Update the first hidden layer
+    model.local_update[0]([[0, 1, 0, 1]])
+    model.local_update[1]([[0, 1, 0, 1]])
+    model.local_update[2]([[0, 1, 0, 1]])
+
+    model.update([[0, 1, 0, 1]], [[0]])
+    print model.classify([[0, 1, 0, 1]])
+
+
+
+
+
+if __name__ == '__main__':
+#    print 'optimized:'
+#    t1 = test_train_daa(theano.Mode('py', 'fast_compile'))
+#    t1 = test_train_daa(theano.Mode('c|py', 'fast_run'))
+#    print 'time:',t1
+#    print
+
+#    print 'not optimized:'
+#    t2 = test_train_daa(theano.Mode('c|py', 'fast_compile'))
+##    print 'time:',t2
+
+#    test_train_daa(theano.compile.Mode('c&py', 'merge'))
+    test_train_daa(theano.compile.Mode('c|py', 'merge'))