--- a/test_mlp.py	Tue May 13 19:37:29 2008 -0400
+++ b/test_mlp.py	Tue May 13 20:10:03 2008 -0400
@@ -1,6 +1,7 @@
 
 from mlp import *
 import dataset
+import nnet_ops
 
 
 from functools import partial
@@ -64,5 +65,40 @@
     for fieldname in output_ds.fieldNames():
         print fieldname+"=",output_ds[fieldname]
 
-test0()
+def test1():
+    nnet = ManualNNet(2, 10,3,.1,1000)
+    training_set = dataset.ArrayDataSet(numpy.array([[0, 0, 0],
+                                                     [0, 1, 1],
+                                                     [1, 0, 1],
+                                                     [1, 1, 1]]),
+                                        {'input':slice(2),'target':2})
+    fprop=nnet(training_set)
+
+    output_ds = fprop(training_set)
+
+    for fieldname in output_ds.fieldNames():
+        print fieldname+"=",output_ds[fieldname]
 
+def test2():
+    training_set = dataset.ArrayDataSet(numpy.array([[0, 0, 0],
+                                                     [0, 1, 1],
+                                                     [1, 0, 1],
+                                                     [1, 1, 1]]),
+                                        {'input':slice(2),'target':2})
+    nin, nhid=2, 10
+    def sigm_layer(input):
+        W1 = t.matrix('W1')
+        b1 = t.vector('b1')
+        return (nnet_ops.sigmoid(b1 + t.dot(input, W1)),
+                [W1, b1],
+                [(numpy.random.rand(nin, nhid) -0.5) * 0.001, numpy.zeros(nhid)])
+    nnet = ManualNNet(nin, nhid, 3, .1, 1000, hidden_layer=sigm_layer)
+    fprop=nnet(training_set)
+
+    output_ds = fprop(training_set)
+
+    for fieldname in output_ds.fieldNames():
+        print fieldname+"=",output_ds[fieldname]
+test1()
+test2()
+