--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/algorithms/_test_logistic_regression.py	Wed Oct 22 15:56:53 2008 -0400
@@ -0,0 +1,60 @@
+from logistic_regression import *
+import sys, time
+
+if __name__ == '__main__':
+    pprint.assign(nnet_ops.crossentropy_softmax_1hot_with_bias_dx, printing.FunctionPrinter('xsoftmaxdx'))
+    pprint.assign(nnet_ops.crossentropy_softmax_argmax_1hot_with_bias, printing.FunctionPrinter('nll', 'softmax', 'argmax'))
+    if 1:
+        lrc = Module_Nclass()
+
+        print '================'
+        print lrc.update.pretty()
+        print '================'
+        print lrc.update.pretty(mode = theano.Mode('py', 'fast_run'))
+        print '================'
+#         print lrc.update.pretty(mode = compile.FAST_RUN.excluding('inplace'))
+#         print '================'
+
+#        sys.exit(0)
+
+        lr = lrc.make(10, 2, mode=theano.Mode('c|py', 'fast_run'))
+        #lr = lrc.make(10, 2, mode=compile.FAST_RUN.excluding('fast_run'))
+        #lr = lrc.make(10, 2, mode=theano.Mode('py', 'merge')) #'FAST_RUN')
+
+        data_x = N.random.randn(5, 10)
+        data_y = (N.random.randn(5) > 0)
+
+        t = time.time()
+        for i in xrange(10000):
+            lr.lr = 0.02
+            xe = lr.update(data_x, data_y) 
+            #if i % 100 == 0:
+            #    print i, xe
+
+        print 'training time:', time.time() - t
+        print 'final error', xe
+
+        #print
+        #print 'TRAINED MODEL:'
+        #print lr
+
+    if 0:
+        lrc = Module()
+
+        lr = lrc.make(10, mode=theano.Mode('c|py', 'merge')) #'FAST_RUN')
+
+        data_x = N.random.randn(5, 10)
+        data_y = (N.random.randn(5, 1) > 0)
+
+        for i in xrange(10000):
+            xe = lr.update(data_x, data_y)
+            if i % 100 == 0:
+                print i, xe
+
+        print
+        print 'TRAINED MODEL:'
+        print lr
+
+
+
+